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Sample records for models estimated meta-relative

  1. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

    Directory of Open Access Journals (Sweden)

    Tashkova Katerina

    2011-10-01

    Full Text Available Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA, particle-swarm optimization (PSO, and differential evolution (DE, as well as a local-search derivative-based algorithm 717 (A717 to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE clearly and significantly outperform the local derivative-based method (A717. Among the three meta-heuristics, differential evolution (DE performs best in terms of the objective function, i.e., reconstructing the output, and in terms of

  2. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis.

    Science.gov (United States)

    Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo

    2011-10-11

    We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and

  3. Instance Selection for Classifier Performance Estimation in Meta Learning

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    Marcin Blachnik

    2017-11-01

    Full Text Available Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be informative to allow the precise estimation of prediction accuracy. In this paper, a new type of metadata descriptors is analyzed. These descriptors are based on the compression level obtained from the instance selection methods at the data-preprocessing stage. To verify their suitability, two types of experiments on real-world datasets have been conducted. In the first one, 11 instance selection methods were examined in order to validate the compression–accuracy relation for three classifiers: k-nearest neighbors (kNN, support vector machine (SVM, and random forest. From this analysis, two methods are recommended (instance-based learning type 2 (IB2, and edited nearest neighbor (ENN which are then compared with the state-of-the-art metaset descriptors. The obtained results confirm that the two suggested compression-based meta-features help to predict accuracy of the base model much more accurately than the state-of-the-art solution.

  4. Instance Selection for Classifier Performance Estimation in Meta Learning

    OpenAIRE

    Marcin Blachnik

    2017-01-01

    Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be inform...

  5. Estimating required information size by quantifying diversity in random-effects model meta-analyses

    DEFF Research Database (Denmark)

    Wetterslev, Jørn; Thorlund, Kristian; Brok, Jesper

    2009-01-01

    an intervention effect suggested by trials with low-risk of bias. METHODS: Information size calculations need to consider the total model variance in a meta-analysis to control type I and type II errors. Here, we derive an adjusting factor for the required information size under any random-effects model meta......-analysis. RESULTS: We devise a measure of diversity (D2) in a meta-analysis, which is the relative variance reduction when the meta-analysis model is changed from a random-effects into a fixed-effect model. D2 is the percentage that the between-trial variability constitutes of the sum of the between...... and interpreted using several simulations and clinical examples. In addition we show mathematically that diversity is equal to or greater than inconsistency, that is D2 >or= I2, for all meta-analyses. CONCLUSION: We conclude that D2 seems a better alternative than I2 to consider model variation in any random...

  6. A random effects meta-analysis model with Box-Cox transformation.

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    Yamaguchi, Yusuke; Maruo, Kazushi; Partlett, Christopher; Riley, Richard D

    2017-07-19

    In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. The

  7. A random effects meta-analysis model with Box-Cox transformation

    Directory of Open Access Journals (Sweden)

    Yusuke Yamaguchi

    2017-07-01

    Full Text Available Abstract Background In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. Methods We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. Results A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and

  8. Meta-analysis of choice set generation effects on route choice model estimates and predictions

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo

    2012-01-01

    are applied for model estimation and results are compared to the ‘true model estimates’. Last, predictions from the simulation of models estimated with objective choice sets are compared to the ‘postulated predicted routes’. A meta-analytical approach allows synthesizing the effect of judgments......Large scale applications of behaviorally realistic transport models pose several challenges to transport modelers on both the demand and the supply sides. On the supply side, path-based solutions to the user assignment equilibrium problem help modelers in enhancing the route choice behavior...... modeling, but require them to generate choice sets by selecting a path generation technique and its parameters according to personal judgments. This paper proposes a methodology and an experimental setting to provide general indications about objective judgments for an effective route choice set generation...

  9. Using structural equation modeling for network meta-analysis.

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    Tu, Yu-Kang; Wu, Yun-Chun

    2017-07-14

    Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison

  10. A meta-model based approach for rapid formability estimation of continuous fibre reinforced components

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    Zimmerling, Clemens; Dörr, Dominik; Henning, Frank; Kärger, Luise

    2018-05-01

    Due to their high mechanical performance, continuous fibre reinforced plastics (CoFRP) become increasingly important for load bearing structures. In many cases, manufacturing CoFRPs comprises a forming process of textiles. To predict and optimise the forming behaviour of a component, numerical simulations are applied. However, for maximum part quality, both the geometry and the process parameters must match in mutual regard, which in turn requires numerous numerically expensive optimisation iterations. In both textile and metal forming, a lot of research has focused on determining optimum process parameters, whilst regarding the geometry as invariable. In this work, a meta-model based approach on component level is proposed, that provides a rapid estimation of the formability for variable geometries based on pre-sampled, physics-based draping data. Initially, a geometry recognition algorithm scans the geometry and extracts a set of doubly-curved regions with relevant geometry parameters. If the relevant parameter space is not part of an underlying data base, additional samples via Finite-Element draping simulations are drawn according to a suitable design-table for computer experiments. Time saving parallel runs of the physical simulations accelerate the data acquisition. Ultimately, a Gaussian Regression meta-model is built from the data base. The method is demonstrated on a box-shaped generic structure. The predicted results are in good agreement with physics-based draping simulations. Since evaluations of the established meta-model are numerically inexpensive, any further design exploration (e.g. robustness analysis or design optimisation) can be performed in short time. It is expected that the proposed method also offers great potential for future applications along virtual process chains: For each process step along the chain, a meta-model can be set-up to predict the impact of design variations on manufacturability and part performance. Thus, the method is

  11. Beta-binomial model for meta-analysis of odds ratios.

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    Bakbergenuly, Ilyas; Kulinskaya, Elena

    2017-05-20

    In meta-analysis of odds ratios (ORs), heterogeneity between the studies is usually modelled via the additive random effects model (REM). An alternative, multiplicative REM for ORs uses overdispersion. The multiplicative factor in this overdispersion model (ODM) can be interpreted as an intra-class correlation (ICC) parameter. This model naturally arises when the probabilities of an event in one or both arms of a comparative study are themselves beta-distributed, resulting in beta-binomial distributions. We propose two new estimators of the ICC for meta-analysis in this setting. One is based on the inverted Breslow-Day test, and the other on the improved gamma approximation by Kulinskaya and Dollinger (2015, p. 26) to the distribution of Cochran's Q. The performance of these and several other estimators of ICC on bias and coverage is studied by simulation. Additionally, the Mantel-Haenszel approach to estimation of ORs is extended to the beta-binomial model, and we study performance of various ICC estimators when used in the Mantel-Haenszel or the inverse-variance method to combine ORs in meta-analysis. The results of the simulations show that the improved gamma-based estimator of ICC is superior for small sample sizes, and the Breslow-Day-based estimator is the best for n⩾100. The Mantel-Haenszel-based estimator of OR is very biased and is not recommended. The inverse-variance approach is also somewhat biased for ORs≠1, but this bias is not very large in practical settings. Developed methods and R programs, provided in the Web Appendix, make the beta-binomial model a feasible alternative to the standard REM for meta-analysis of ORs. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

  12. A statistical method to base nutrient recommendations on meta-analysis of intake and health-related status biomarkers.

    Directory of Open Access Journals (Sweden)

    Hilko van der Voet

    Full Text Available Nutrient recommendations in use today are often derived from relatively old data of few studies with few individuals. However, for many nutrients, including vitamin B-12, extensive data have now become available from both observational studies and randomized controlled trials, addressing the relation between intake and health-related status biomarkers. The purpose of this article is to provide new methodology for dietary planning based on dose-response data and meta-analysis. The methodology builds on existing work, and is consistent with current methodology and measurement error models for dietary assessment. The detailed purposes of this paper are twofold. Firstly, to define a Population Nutrient Level (PNL for dietary planning in groups. Secondly, to show how data from different sources can be combined in an extended meta-analysis of intake-status datasets for estimating PNL as well as other nutrient intake values, such as the Average Nutrient Requirement (ANR and the Individual Nutrient Level (INL. For this, a computational method is presented for comparing a bivariate lognormal distribution to a health criterion value. Procedures to meta-analyse available data in different ways are described. Example calculations on vitamin B-12 requirements were made for four models, assuming different ways of estimating the dose-response relation, and different values of the health criterion. Resulting estimates of ANRs and less so for INLs were found to be sensitive to model assumptions, whereas estimates of PNLs were much less sensitive to these assumptions as they were closer to the average nutrient intake in the available data.

  13. Applying the Business Process and Practice Alignment Meta-model: Daily Practices and Process Modelling

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    Ventura Martins Paula

    2017-03-01

    Full Text Available Background: Business Process Modelling (BPM is one of the most important phases of information system design. Business Process (BP meta-models allow capturing informational and behavioural aspects of business processes. Unfortunately, standard BP meta-modelling approaches focus just on process description, providing different BP models. It is not possible to compare and identify related daily practices in order to improve BP models. This lack of information implies that further research in BP meta-models is needed to reflect the evolution/change in BP. Considering this limitation, this paper introduces a new BP meta-model designed by Business Process and Practice Alignment Meta-model (BPPAMeta-model. Our intention is to present a meta-model that addresses features related to the alignment between daily work practices and BP descriptions. Objectives: This paper intends to present a metamodel which is going to integrate daily work information into coherent and sound process definitions. Methods/Approach: The methodology employed in the research follows a design-science approach. Results: The results of the case study are related to the application of the proposed meta-model to align the specification of a BP model with work practices models. Conclusions: This meta-model can be used within the BPPAM methodology to specify or improve business processes models based on work practice descriptions.

  14. A Bayesian Nonparametric Meta-Analysis Model

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    Karabatsos, George; Talbott, Elizabeth; Walker, Stephen G.

    2015-01-01

    In a meta-analysis, it is important to specify a model that adequately describes the effect-size distribution of the underlying population of studies. The conventional normal fixed-effect and normal random-effects models assume a normal effect-size population distribution, conditionally on parameters and covariates. For estimating the mean overall…

  15. A Meta-Meta-Analysis: Empirical Review of Statistical Power, Type I Error Rates, Effect Sizes, and Model Selection of Meta-Analyses Published in Psychology

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    Cafri, Guy; Kromrey, Jeffrey D.; Brannick, Michael T.

    2010-01-01

    This article uses meta-analyses published in "Psychological Bulletin" from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual…

  16. Influence diagnostics in meta-regression model.

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    Shi, Lei; Zuo, ShanShan; Yu, Dalei; Zhou, Xiaohua

    2017-09-01

    This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum likelihood estimation methods in meta-regression are considered, respectively, to derive the results. Internal and external residual and leverage measure are defined. The local influence analysis based on case-weights perturbation scheme, responses perturbation scheme, covariate perturbation scheme, and within-variance perturbation scheme are explored. We introduce a method by simultaneous perturbing responses, covariate, and within-variance to obtain the local influence measure, which has an advantage of capable to compare the influence magnitude of influential studies from different perturbations. An example is used to illustrate the proposed methodology. Copyright © 2017 John Wiley & Sons, Ltd.

  17. Reliability Modeling of Electromechanical System with Meta-Action Chain Methodology

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    Genbao Zhang

    2018-01-01

    Full Text Available To establish a more flexible and accurate reliability model, the reliability modeling and solving algorithm based on the meta-action chain thought are used in this thesis. Instead of estimating the reliability of the whole system only in the standard operating mode, this dissertation adopts the structure chain and the operating action chain for the system reliability modeling. The failure information and structure information for each component are integrated into the model to overcome the given factors applied in the traditional modeling. In the industrial application, there may be different operating modes for a multicomponent system. The meta-action chain methodology can estimate the system reliability under different operating modes by modeling the components with varieties of failure sensitivities. This approach has been identified by computing some electromechanical system cases. The results indicate that the process could improve the system reliability estimation. It is an effective tool to solve the reliability estimation problem in the system under various operating modes.

  18. Meta-modeling of the pesticide fate model MACRO for groundwater exposure assessments using artificial neural networks

    Science.gov (United States)

    Stenemo, Fredrik; Lindahl, Anna M. L.; Gärdenäs, Annemieke; Jarvis, Nicholas

    2007-08-01

    Several simple index methods that use easily accessible data have been developed and included in decision-support systems to estimate pesticide leaching across larger areas. However, these methods often lack important process descriptions (e.g. macropore flow), which brings into question their reliability. Descriptions of macropore flow have been included in simulation models, but these are too complex and demanding for spatial applications. To resolve this dilemma, a neural network simulation meta-model of the dual-permeability macropore flow model MACRO was created for pesticide groundwater exposure assessment. The model was parameterized using pedotransfer functions that require as input the clay and sand content of the topsoil and subsoil, and the topsoil organic carbon content. The meta-model also requires the topsoil pesticide half-life and the soil organic carbon sorption coefficient as input. A fully connected feed-forward multilayer perceptron classification network with two hidden layers, linked to fully connected feed-forward multilayer perceptron neural networks with one hidden layer, trained on sub-sets of the target variable, was shown to be a suitable meta-model for the intended purpose. A Fourier amplitude sensitivity test showed that the model output (the 80th percentile average yearly pesticide concentration at 1 m depth for a 20 year simulation period) was sensitive to all input parameters. The two input parameters related to pesticide characteristics (i.e. soil organic carbon sorption coefficient and topsoil pesticide half-life) were the most influential, but texture in the topsoil was also quite important since it was assumed to control the mass exchange coefficient that regulates the strength of macropore flow. This is in contrast to models based on the advection-dispersion equation where soil texture is relatively unimportant. The use of the meta-model is exemplified with a case-study where the spatial variability of pesticide leaching is

  19. Psychological career meta-capacities in relation to employees ...

    African Journals Online (AJOL)

    A canonical correlation analysis indicated a significant overall relationship between the psychological career meta-capacities and the retention- related dispositions. Structural equation modelling indicated a good fit of the data with the canonical correlation-derived measurement model. In the employment equity context, the ...

  20. Outdoor Air Pollution and COPD-Related Emergency Department Visits, Hospital Admissions, and Mortality: A Meta-Analysis.

    Science.gov (United States)

    DeVries, Rebecca; Kriebel, David; Sama, Susan

    2017-02-01

    A systematic literature review was performed to identify all peer-reviewed literature quantifying the association between short-term exposures of particulate matter <2.5 microns (PM 2.5 ), nitrogen dioxide (NO 2 ), and sulfur dioxide (SO 2 ) and COPD-related emergency department (ED) visits, hospital admissions (HA), and mortality. These results were then pooled for each pollutant through meta-analyses with a random effects model. Subgroup meta-analyses were explored to study the effects of selected lag/averaging times and health outcomes. A total of 37 studies satisfied our inclusion criteria, contributing to a total of approximately 1,115,000 COPD-related acute events (950,000 HAs, 80,000 EDs, and 130,000 deaths) to our meta-estimates. An increase in PM 2.5 of 10 ug/m 3 was associated with a 2.5% (95% CI: 1.6-3.4%) increased risk of COPD-related ED and HA, an increase of 10 ug/m 3 in NO 2 was associated with a 4.2% (2.5-6.0%) increase, and an increase of 10 ug/m 3 in SO 2 was associated with a 2.1% (0.7-3.5%) increase. The strength of these pooled effect estimates, however, varied depending on the selected lag/averaging time between exposure and outcome. Similar pooled effects were estimated for each pollutant and COPD-related mortality. These results suggest an ongoing threat to the health of COPD patients from both outdoor particulates and gaseous pollutants. Ambient outdoor concentrations of PM 2.5 , NO 2 , and SO 2 were significantly and positively associated with both COPD-related morbidity and mortality.

  1. Meta-analysis of amino acid stable nitrogen isotope ratios for estimating trophic position in marine organisms.

    Science.gov (United States)

    Nielsen, Jens M; Popp, Brian N; Winder, Monika

    2015-07-01

    Estimating trophic structures is a common approach used to retrieve information regarding energy pathways, predation, and competition in complex ecosystems. The application of amino acid (AA) compound-specific nitrogen (N) isotope analysis (CSIA) is a relatively new method used to estimate trophic position (TP) and feeding relationships in diverse organisms. Here, we conducted the first meta-analysis of δ(15)N AA values from measurements of 359 marine species covering four trophic levels, and compared TP estimates from AA-CSIA to literature values derived from food items, gut or stomach content analysis. We tested whether the AA trophic enrichment factor (TEF), or the (15)N enrichment among different individual AAs is constant across trophic levels and whether inclusion of δ(15)N values from multiple AAs improves TP estimation. For the TEF of glutamic acid relative to phenylalanine (Phe) we found an average value of 6.6‰ across all taxa, which is significantly lower than the commonly applied 7.6‰. We found that organism feeding ecology influences TEF values of several trophic AAs relative to Phe, with significantly higher TEF values for herbivores compared to omnivores and carnivores, while TEF values were also significantly lower for animals excreting urea compared to ammonium. Based on the comparison of multiple model structures using the metadata of δ(15)N AA values we show that increasing the number of AAs in principle improves precision in TP estimation. This meta-analysis clarifies the advantages and limitations of using individual δ(15)N AA values as tools in trophic ecology and provides a guideline for the future application of AA-CSIA to food web studies.

  2. University Students' Meta-Modelling Knowledge

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    Krell, Moritz; Krüger, Dirk

    2017-01-01

    Background: As one part of scientific meta-knowledge, students' meta-modelling knowledge should be promoted on different educational levels such as primary school, secondary school and university. This study focuses on the assessment of university students' meta-modelling knowledge using a paper-pencil questionnaire. Purpose: The general purpose…

  3. Estimating the price elasticity of beer: meta-analysis of data with heterogeneity, dependence, and publication bias.

    Science.gov (United States)

    Nelson, Jon P

    2014-01-01

    Precise estimates of price elasticities are important for alcohol tax policy. Using meta-analysis, this paper corrects average beer elasticities for heterogeneity, dependence, and publication selection bias. A sample of 191 estimates is obtained from 114 primary studies. Simple and weighted means are reported. Dependence is addressed by restricting number of estimates per study, author-restricted samples, and author-specific variables. Publication bias is addressed using funnel graph, trim-and-fill, and Egger's intercept model. Heterogeneity and selection bias are examined jointly in meta-regressions containing moderator variables for econometric methodology, primary data, and precision of estimates. Results for fixed- and random-effects regressions are reported. Country-specific effects and sample time periods are unimportant, but several methodology variables help explain the dispersion of estimates. In models that correct for selection bias and heterogeneity, the average beer price elasticity is about -0.20, which is less elastic by 50% compared to values commonly used in alcohol tax policy simulations. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. An improved method for bivariate meta-analysis when within-study correlations are unknown.

    Science.gov (United States)

    Hong, Chuan; D Riley, Richard; Chen, Yong

    2018-03-01

    Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the

  5. Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

    Science.gov (United States)

    Spiliopoulou, Athina; Nagy, Reka; Bermingham, Mairead L.; Huffman, Jennifer E.; Hayward, Caroline; Vitart, Veronique; Rudan, Igor; Campbell, Harry; Wright, Alan F.; Wilson, James F.; Pong-Wong, Ricardo; Agakov, Felix; Navarro, Pau; Haley, Chris S.

    2015-01-01

    We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge. PMID:25918167

  6. Association between SERPING1 rs2511989 polymorphism and age-related macular degeneration: Meta-analysis

    Directory of Open Access Journals (Sweden)

    Yi Dong

    2015-04-01

    Full Text Available AIM: To investigate the association between SERPING1 rs2511989 (G>A polymorphism and age-related macular degeneration (AMD. METHODS: A number of electronic databases (up to July 15, 2014 were searched independently by two investigators. A Meta-analysis was performed on the association between SERPING1 rs2511989 polymorphism and AMD. Pooled odds ratios (ORs with 95% confidence intervals (CIs were estimated. RESULTS: Eight studies with 16 cohorts consisting of 9163 cases and 6813 controls were included in this Meta-analysis. There was no significant association between rs2511989 polymorphism and AMD under all genetic models in overall estimates (A vs G: OR= 0.938, 95%CI =0.858-1.025; AA vs GG:OR =0.871, 95%CI =0.719-1.056; AG vs GG: OR =0.944, 95%CI =0.845-1.054; AA+AG vs GG: OR =0.927, 95% CI =0.823-1.044; AA vs AG+GG: OR =0.890, 95%CI =0.780-1.034. Cumulative Meta-analyses also showed a trend of no association between rs2511989 polymorphism and AMD as information accumulated by year. Subgroup analysis and Meta-regression analysis indicated that age-matching status was the main source of heterogeneity. Sensitivity analysis found the results in overall comparisons and subgroup comparisons of white subjects under the allele model were found to have significantly statistical differences after studies deviating from Hardy-Weinberg equilibrium (HWE were excluded (overall: OR=0.918, 95%CI = 0.844-0.999, P =0.049; whites: OR =0.901, 95%CI = 0.817-0.994, P =0.038. However, the results were not sufficiently robust for further sensitivity analysis and statistical differences disappeared on applying Bonferroni correction (with a significance level set at 0.05/25. CONCLUSION: This Meta-analysis indicates that SERPING1 rs2511989 polymorphism and AMD tend to have no association with each other. Age matching status is a big confounding factor, and more studies with subtle designs are warranted in future.

  7. One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information.

    Science.gov (United States)

    Hua, Hairui; Burke, Danielle L; Crowther, Michael J; Ensor, Joie; Tudur Smith, Catrin; Riley, Richard D

    2017-02-28

    Stratified medicine utilizes individual-level covariates that are associated with a differential treatment effect, also known as treatment-covariate interactions. When multiple trials are available, meta-analysis is used to help detect true treatment-covariate interactions by combining their data. Meta-regression of trial-level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta-analyses are preferable to examine interactions utilizing individual-level information. However, one-stage IPD models are often wrongly specified, such that interactions are based on amalgamating within- and across-trial information. We compare, through simulations and an applied example, fixed-effect and random-effects models for a one-stage IPD meta-analysis of time-to-event data where the goal is to estimate a treatment-covariate interaction. We show that it is crucial to centre patient-level covariates by their mean value in each trial, in order to separate out within-trial and across-trial information. Otherwise, bias and coverage of interaction estimates may be adversely affected, leading to potentially erroneous conclusions driven by ecological bias. We revisit an IPD meta-analysis of five epilepsy trials and examine age as a treatment effect modifier. The interaction is -0.011 (95% CI: -0.019 to -0.003; p = 0.004), and thus highly significant, when amalgamating within-trial and across-trial information. However, when separating within-trial from across-trial information, the interaction is -0.007 (95% CI: -0.019 to 0.005; p = 0.22), and thus its magnitude and statistical significance are greatly reduced. We recommend that meta-analysts should only use within-trial information to examine individual predictors of treatment effect and that one-stage IPD models should separate within-trial from across-trial information to avoid ecological bias. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd

  8. Meta-analysis a structural equation modeling approach

    CERN Document Server

    Cheung, Mike W-L

    2015-01-01

    Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the impo

  9. Estimating Predictive Variance for Statistical Gas Distribution Modelling

    International Nuclear Information System (INIS)

    Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo

    2009-01-01

    Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.

  10. Association of vitamin C with the risk of age-related cataract: a meta-analysis.

    Science.gov (United States)

    Wei, Lin; Liang, Ge; Cai, Chunmei; Lv, Jin

    2016-05-01

    Whether vitamin C is a protective factor for age-related cataract remains unclear. Thus, we conducted a meta-analysis to summarize the evidence from epidemiological studies of vitamin C and the risk of age-related cataract. Pertinent studies were identified by searching in PubMed and in Webscience. The random effect model was used to combine the results. Meta-regression and subgroups analyses were used to explore potential sources of between-study heterogeneity. Publication bias was estimated using Egger's regression asymmetry test. Finally, 15 articles with 20 studies for vitamin C intake and eight articles with 10 studies for serum ascorbate were included in this meta-analysis. The relative risk (RR) and 95% confidence interval of cataract for the highest versus the lowest category of vitamin C intake was 0.814 (0.707-0.938), and the associations were significant in America and Asia. Significant association of cataract risk with highest versus the lowest category of serum ascorbate was found in general [0.704 (0.564-0.879)]. Inverse associations were also found between serum ascorbate and nuclear cataract and posterior subcapsular cataract. Higher vitamin C intake and serum ascorbate might be inversely associated with risk of cataract. Vitamin C intake should be advocated for the primary prevention of cataract. © 2015 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

  11. Affective mapping: An activation likelihood estimation (ALE) meta-analysis.

    Science.gov (United States)

    Kirby, Lauren A J; Robinson, Jennifer L

    2017-11-01

    Functional neuroimaging has the spatial resolution to explain the neural basis of emotions. Activation likelihood estimation (ALE), as opposed to traditional qualitative meta-analysis, quantifies convergence of activation across studies within affective categories. Others have used ALE to investigate a broad range of emotions, but without the convenience of the BrainMap database. We used the BrainMap database and analysis resources to run separate meta-analyses on coordinates reported for anger, anxiety, disgust, fear, happiness, humor, and sadness. Resultant ALE maps were compared to determine areas of convergence between emotions, as well as to identify affect-specific networks. Five out of the seven emotions demonstrated consistent activation within the amygdala, whereas all emotions consistently activated the right inferior frontal gyrus, which has been implicated as an integration hub for affective and cognitive processes. These data provide the framework for models of affect-specific networks, as well as emotional processing hubs, which can be used for future studies of functional or effective connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Random effects coefficient of determination for mixed and meta-analysis models.

    Science.gov (United States)

    Demidenko, Eugene; Sargent, James; Onega, Tracy

    2012-01-01

    The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, [Formula: see text], that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If [Formula: see text] is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of [Formula: see text] apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects-the model can be estimated using the dummy variable approach. We derive explicit formulas for [Formula: see text] in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine.

  13. A meta-analysis of motivational interviewing process: Technical, relational, and conditional process models of change.

    Science.gov (United States)

    Magill, Molly; Apodaca, Timothy R; Borsari, Brian; Gaume, Jacques; Hoadley, Ariel; Gordon, Rebecca E F; Tonigan, J Scott; Moyers, Theresa

    2018-02-01

    In the present meta-analysis, we test the technical and relational hypotheses of Motivational Interviewing (MI) efficacy. We also propose an a priori conditional process model where heterogeneity of technical path effect sizes should be explained by interpersonal/relational (i.e., empathy, MI Spirit) and intrapersonal (i.e., client treatment seeking status) moderators. A systematic review identified k = 58 reports, describing 36 primary studies and 40 effect sizes (N = 3,025 participants). Statistical methods calculated the inverse variance-weighted pooled correlation coefficient for the therapist to client and the client to outcome paths across multiple target behaviors (i.e., alcohol use, other drug use, other behavior change). Therapist MI-consistent skills were correlated with more client change talk (r = .55, p technical hypothesis was supported. Specifically, proportion MI consistency was related to higher proportion change talk (r = .11, p = .004) and higher proportion change talk was related to reductions in risk behavior at follow up (r = -.16, p technical hypothesis path effect sizes was partially explained by inter- and intrapersonal moderators. This meta-analysis provides additional support for the technical hypothesis of MI efficacy; future research on the relational hypothesis should occur in the field rather than in the context of clinical trials. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  14. Standardizing effect size from linear regression models with log-transformed variables for meta-analysis.

    Science.gov (United States)

    Rodríguez-Barranco, Miguel; Tobías, Aurelio; Redondo, Daniel; Molina-Portillo, Elena; Sánchez, María José

    2017-03-17

    Meta-analysis is very useful to summarize the effect of a treatment or a risk factor for a given disease. Often studies report results based on log-transformed variables in order to achieve the principal assumptions of a linear regression model. If this is the case for some, but not all studies, the effects need to be homogenized. We derived a set of formulae to transform absolute changes into relative ones, and vice versa, to allow including all results in a meta-analysis. We applied our procedure to all possible combinations of log-transformed independent or dependent variables. We also evaluated it in a simulation based on two variables either normally or asymmetrically distributed. In all the scenarios, and based on different change criteria, the effect size estimated by the derived set of formulae was equivalent to the real effect size. To avoid biased estimates of the effect, this procedure should be used with caution in the case of independent variables with asymmetric distributions that significantly differ from the normal distribution. We illustrate an application of this procedure by an application to a meta-analysis on the potential effects on neurodevelopment in children exposed to arsenic and manganese. The procedure proposed has been shown to be valid and capable of expressing the effect size of a linear regression model based on different change criteria in the variables. Homogenizing the results from different studies beforehand allows them to be combined in a meta-analysis, independently of whether the transformations had been performed on the dependent and/or independent variables.

  15. Bayesian meta-analysis models for microarray data: a comparative study

    Directory of Open Access Journals (Sweden)

    Song Joon J

    2007-03-01

    Full Text Available Abstract Background With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods. Results Two Bayesian meta-analysis models for microarray data have recently been introduced. The first model combines standardized gene expression measures across studies into an overall mean, accounting for inter-study variability, while the second combines probabilities of differential expression without combining expression values. Both models produce the gene-specific posterior probability of differential expression, which is the basis for inference. Since the standardized expression integration model includes inter-study variability, it may improve accuracy of results versus the probability integration model. However, due to the small number of studies typical in microarray meta-analyses, the variability between studies is challenging to estimate. The probability integration model eliminates the need to model variability between studies, and thus its implementation is more straightforward. We found in simulations of two and five studies that combining probabilities outperformed combining standardized gene expression measures for three comparison values: the percent of true discovered genes in meta-analysis versus individual studies; the percent of true genes omitted in meta-analysis versus separate studies, and the number of true discovered genes for fixed levels of Bayesian false discovery. We identified similar results when pooling two independent studies of Bacillus subtilis. We assumed that each study was produced from the same microarray platform with only two conditions: a treatment and control, and that the data sets

  16. Urinary neutrophil gelatinase-associated lipocalin for diagnosis and estimating activity in lupus nephritis: a meta-analysis.

    Science.gov (United States)

    Fang, Y G; Chen, N N; Cheng, Y B; Sun, S J; Li, H X; Sun, F; Xiang, Y

    2015-12-01

    Urinary neutrophil gelatinase-associated lipocalin (uNGAL) is relatively specific in lupus nephritis (LN) patients. However, its diagnostic value has not been evaluated. The aim of this review was to determine the value of uNGAL for diagnosis and estimating activity in LN. A comprehensive search was performed on PubMed, EMBASE, Web of Knowledge, Cochrane electronic databases through December 2014. Meta-analysis of sensitivity and specificity was performed with a random-effects model. Additionally, summary receiver operating characteristic (SROC) curves and area under the curve (AUC) values were calculated. Fourteen studies were selected for this review. With respect to diagnosing LN, the pooled sensitivity and specificity were 73.6% (95% confidence interval (CI), 61.9-83.3) and 78.1% (95% CI, 69.0-85.6), respectively. The SROC-AUC value was 0.8632. Regarding estimating LN activity, the pooled sensitivity and specificity were 66.2% (95% CI, 60.4-71.7) and 62.1% (95% CI, 57.9-66.3), respectively. The SROC-AUC value was 0.7583. In predicting renal flares, the pooled sensitivity and specificity were 77.5% (95% CI, 68.1-85.1) and 65.3% (95% CI, 60.0-70.3), respectively. The SROC-AUC value was 0.7756. In conclusion, this meta-analysis indicates that uNGAL has relatively fair sensitivity and specificity in diagnosing LN, estimating LN activity and predicting renal flares, suggesting that uNGAL is a potential biomarker in diagnosing LN and monitoring LN activity. © The Author(s) 2015.

  17. Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

    Science.gov (United States)

    Jacobs, Perke; Viechtbauer, Wolfgang

    2017-06-01

    Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  18. Health-Related Lifestyle Factors and Sexual Dysfunction: A Meta-Analysis of Population-Based Research.

    Science.gov (United States)

    Allen, Mark S; Walter, Emma E

    2018-04-01

    Sexual dysfunction is a common problem among men and women and is associated with negative individual functioning, relationship difficulties, and lower quality of life. To determine the magnitude of associations between 6 health-related lifestyle factors (cigarette smoking, alcohol intake, physical activity, diet, caffeine, and cannabis use) and 3 common sexual dysfunctions (erectile dysfunction, premature ejaculation, and female sexual dysfunction). A comprehensive literature search of 10 electronic databases identified 89 studies that met the inclusion criteria (452 effect sizes; N = 348,865). Pooled mean effects (for univariate, age-adjusted, and multivariable-adjusted estimates) were computed using inverse-variance weighted random-effects meta-analysis and moderation by study and population characteristics were tested using random-effects meta-regression. Mean effect sizes from 92 separate meta-analyses provided evidence that health-related lifestyle factors are important for sexual dysfunction. Cigarette smoking (past and current), alcohol intake, and physical activity had dose-dependent associations with erectile dysfunction. Risk of erectile dysfunction increased with greater cigarette smoking and decreased with greater physical activity. Alcohol had a curvilinear association such that moderate intake was associated with a lower risk of erectile dysfunction. Participation in physical activity was associated with a lower risk of female sexual dysfunction. There was some evidence that a healthy diet was related to a lower risk of erectile dysfunction and female sexual dysfunction, and caffeine intake was unrelated to erectile dysfunction. Publication bias appeared minimal and findings were similar for clinical and non-clinical samples. Modification of lifestyle factors would appear to be a useful low-risk approach to decreasing the risk of erectile dysfunction and female sexual dysfunction. Strengths include the testing of age-adjusted and multivariable

  19. Bayesian nonparametric meta-analysis using Polya tree mixture models.

    Science.gov (United States)

    Branscum, Adam J; Hanson, Timothy E

    2008-09-01

    Summary. A common goal in meta-analysis is estimation of a single effect measure using data from several studies that are each designed to address the same scientific inquiry. Because studies are typically conducted in geographically disperse locations, recent developments in the statistical analysis of meta-analytic data involve the use of random effects models that account for study-to-study variability attributable to differences in environments, demographics, genetics, and other sources that lead to heterogeneity in populations. Stemming from asymptotic theory, study-specific summary statistics are modeled according to normal distributions with means representing latent true effect measures. A parametric approach subsequently models these latent measures using a normal distribution, which is strictly a convenient modeling assumption absent of theoretical justification. To eliminate the influence of overly restrictive parametric models on inferences, we consider a broader class of random effects distributions. We develop a novel hierarchical Bayesian nonparametric Polya tree mixture (PTM) model. We present methodology for testing the PTM versus a normal random effects model. These methods provide researchers a straightforward approach for conducting a sensitivity analysis of the normality assumption for random effects. An application involving meta-analysis of epidemiologic studies designed to characterize the association between alcohol consumption and breast cancer is presented, which together with results from simulated data highlight the performance of PTMs in the presence of nonnormality of effect measures in the source population.

  20. Meta Analysis for Benefits Transfer – Toward Value Estimates for Some Outputs of Multifunctional Agriculture

    OpenAIRE

    Randall, Alan; Kidder, Ayuna; Chen, Ding-Rong

    2008-01-01

    As a contribution to valuing the outputs of multifunctional agriculture, we report three new meta analyses estimating value functions for agricultural conservation program impacts on water quality, wetlands, and upland habitat and open space. As is often the case in valuation, where methods have yet to be standardized, the data sets are relatively small and noisy. With a clear objective of benefits transfer, we seek robust parameter estimates for key RHS variables, even at the cost of some lo...

  1. Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses?

    Science.gov (United States)

    McAuley, L; Pham, B; Tugwell, P; Moher, D

    2000-10-07

    The inclusion of only a subset of all available evidence in a meta-analysis may introduce biases and threaten its validity; this is particularly likely if the subset of included studies differ from those not included, which may be the case for published and grey literature (unpublished studies, with limited distribution). We set out to examine whether exclusion of grey literature, compared with its inclusion in meta-analysis, provides different estimates of the effectiveness of interventions assessed in randomised trials. From a random sample of 135 meta-analyses, we identified and retrieved 33 publications that included both grey and published primary studies. The 33 publications contributed 41 separate meta-analyses from several disease areas. General characteristics of the meta-analyses and associated studies and outcome data at the trial level were collected. We explored the effects of the inclusion of grey literature on the quantitative results using logistic-regression analyses. 33% of the meta-analyses were found to include some form of grey literature. The grey literature, when included, accounts for between 4.5% and 75% of the studies in a meta-analysis. On average, published work, compared with grey literature, yielded significantly larger estimates of the intervention effect by 15% (ratio of odds ratios=1.15 [95% CI 1.04-1.28]). Excluding abstracts from the analysis further compounded the exaggeration (1.33 [1.10-1.60]). The exclusion of grey literature from meta-analyses can lead to exaggerated estimates of intervention effectiveness. In general, meta-analysts should attempt to identify, retrieve, and include all reports, grey and published, that meet predefined inclusion criteria.

  2. Pain anticipation: an activation likelihood estimation meta-analysis of brain imaging studies.

    Science.gov (United States)

    Palermo, Sara; Benedetti, Fabrizio; Costa, Tommaso; Amanzio, Martina

    2015-05-01

    The anticipation of pain has been investigated in a variety of brain imaging studies. Importantly, today there is no clear overall picture of the areas that are involved in different studies and the exact role of these regions in pain expectation remains especially unexploited. To address this issue, we used activation likelihood estimation meta-analysis to analyze pain anticipation in several neuroimaging studies. A total of 19 functional magnetic resonance imaging were included in the analysis to search for the cortical areas involved in pain anticipation in human experimental models. During anticipation, activated foci were found in the dorsolateral prefrontal, midcingulate and anterior insula cortices, medial and inferior frontal gyri, inferior parietal lobule, middle and superior temporal gyrus, thalamus, and caudate. Deactivated foci were found in the anterior cingulate, superior frontal gyrus, parahippocampal gyrus and in the claustrum. The results of the meta-analytic connectivity analysis provide an overall view of the brain responses triggered by the anticipation of a noxious stimulus. Such a highly distributed perceptual set of self-regulation may prime brain regions to process information where emotion, action and perception as well as their related subcategories play a central role. Not only do these findings provide important information on the neural events when anticipating pain, but also they may give a perspective into nocebo responses, whereby negative expectations may lead to pain worsening. © 2014 Wiley Periodicals, Inc.

  3. MISTRAL : A Language for Model Transformations in the MOF Meta-modeling Architecture

    NARCIS (Netherlands)

    Kurtev, Ivan; van den Berg, Klaas; Aßmann, Uwe; Aksit, Mehmet; Rensink, Arend

    2005-01-01

    n the Meta Object Facility (MOF) meta-modeling architecture a number of model transformation scenarios can be identified. It could be expected that a meta-modeling architecture will be accompanied by a transformation technology supporting the model transformation scenarios in a uniform way. Despite

  4. A joint frailty-copula model between tumour progression and death for meta-analysis.

    Science.gov (United States)

    Emura, Takeshi; Nakatochi, Masahiro; Murotani, Kenta; Rondeau, Virginie

    2017-12-01

    Dependent censoring often arises in biomedical studies when time to tumour progression (e.g., relapse of cancer) is censored by an informative terminal event (e.g., death). For meta-analysis combining existing studies, a joint survival model between tumour progression and death has been considered under semicompeting risks, which induces dependence through the study-specific frailty. Our paper here utilizes copulas to generalize the joint frailty model by introducing additional source of dependence arising from intra-subject association between tumour progression and death. The practical value of the new model is particularly evident for meta-analyses in which only a few covariates are consistently measured across studies and hence there exist residual dependence. The covariate effects are formulated through the Cox proportional hazards model, and the baseline hazards are nonparametrically modeled on a basis of splines. The estimator is then obtained by maximizing a penalized log-likelihood function. We also show that the present methodologies are easily modified for the competing risks or recurrent event data, and are generalized to accommodate left-truncation. Simulations are performed to examine the performance of the proposed estimator. The method is applied to a meta-analysis for assessing a recently suggested biomarker CXCL12 for survival in ovarian cancer patients. We implement our proposed methods in R joint.Cox package.

  5. Procedure-related risk of miscarriage following amniocentesis and chorionic villus sampling: a systematic review and meta-analysis.

    Science.gov (United States)

    Akolekar, R; Beta, J; Picciarelli, G; Ogilvie, C; D'Antonio, F

    2015-01-01

    To estimate procedure-related risks of miscarriage following amniocentesis and chorionic villus sampling (CVS) based on a systematic review of the literature and a meta-analysis. A search of MEDLINE, EMBASE, CINHAL and The Cochrane Library (2000-2014) was performed to review relevant citations reporting procedure-related complications of amniocentesis and CVS. Only studies reporting data on more than 1000 procedures were included in this review to minimize the effect of bias from smaller studies. Heterogeneity between studies was estimated using Cochran's Q, the I(2) statistic and Egger bias. Meta-analysis of proportions was used to derive weighted pooled estimates for the risk of miscarriage before 24 weeks' gestation. Incidence-rate difference meta-analysis was used to estimate pooled procedure-related risks. The weighted pooled risks of miscarriage following invasive procedures were estimated from analysis of controlled studies including 324 losses in 42 716 women who underwent amniocentesis and 207 losses in 8899 women who underwent CVS. The risk of miscarriage prior to 24 weeks in women who underwent amniocentesis and CVS was 0.81% (95% CI, 0.58-1.08%) and 2.18% (95% CI, 1.61-2.82%), respectively. The background rates of miscarriage in women from the control group that did not undergo any procedures were 0.67% (95% CI, 0.46-0.91%) for amniocentesis and 1.79% (95% CI, 0.61-3.58%) for CVS. The weighted pooled procedure-related risks of miscarriage for amniocentesis and CVS were 0.11% (95% CI, -0.04 to 0.26%) and 0.22% (95% CI, -0.71 to 1.16%), respectively. The procedure-related risks of miscarriage following amniocentesis and CVS are much lower than are currently quoted. Copyright © 2014 ISUOG. Published by John Wiley & Sons Ltd.

  6. Kaplan-Meier survival analysis overestimates cumulative incidence of health-related events in competing risk settings: a meta-analysis.

    Science.gov (United States)

    Lacny, Sarah; Wilson, Todd; Clement, Fiona; Roberts, Derek J; Faris, Peter; Ghali, William A; Marshall, Deborah A

    2018-01-01

    Kaplan-Meier survival analysis overestimates cumulative incidence in competing risks (CRs) settings. The extent of overestimation (or its clinical significance) has been questioned, and CRs methods are infrequently used. This meta-analysis compares the Kaplan-Meier method to the cumulative incidence function (CIF), a CRs method. We searched MEDLINE, EMBASE, BIOSIS Previews, Web of Science (1992-2016), and article bibliographies for studies estimating cumulative incidence using the Kaplan-Meier method and CIF. For studies with sufficient data, we calculated pooled risk ratios (RRs) comparing Kaplan-Meier and CIF estimates using DerSimonian and Laird random effects models. We performed stratified meta-analyses by clinical area, rate of CRs (CRs/events of interest), and follow-up time. Of 2,192 identified abstracts, we included 77 studies in the systematic review and meta-analyzed 55. The pooled RR demonstrated the Kaplan-Meier estimate was 1.41 [95% confidence interval (CI): 1.36, 1.47] times higher than the CIF. Overestimation was highest among studies with high rates of CRs [RR = 2.36 (95% CI: 1.79, 3.12)], studies related to hepatology [RR = 2.60 (95% CI: 2.12, 3.19)], and obstetrics and gynecology [RR = 1.84 (95% CI: 1.52, 2.23)]. The Kaplan-Meier method overestimated the cumulative incidence across 10 clinical areas. Using CRs methods will ensure accurate results inform clinical and policy decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. The Impact of Uncertainty on Investment. A Meta-Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Koetse, M.J. [Department of Spatial Economics, Vrije Universiteit Amsterdam (Netherlands); De Groot, Henri L.F. [Tinbergen Institute, Amsterdam (Netherlands); Florax, R.J.G.M. [Department of Agricultural Economics, Purdue University, West Lafayette (United States)

    2006-07-01

    In this paper we perform a meta-analysis on empirical estimates of the impact between investment and uncertainty. Since the outcomes of primary studies are largely incomparable with respect to the magnitude of the effect, our analysis focuses on the direction and statistical significance of the relationship. The standard approach in this situation is to estimate an ordered probit model on a categorical estimate, defined in terms of the direction of the effect. The estimates are transformed into marginal effects, in order to represent the changes in the probability of finding a negative significant, insignificant, and positive significant estimate. Although a meta-analysis generally does not allow for inferences on the correctness of model specifications in primary studies, our results give clear directions for model building in empirical investment research. For example, not including factor prices in investment models may seriously affect the model outcomes. Furthermore, we find that Q models produce more negative significant estimates than other models do, ceteris paribus. The outcome of a study is also affected by the type of data used in a primary study. Although it is clear that meta-analysis cannot always give decisive insights into the explanations for the variation in empirical outcomes, our meta-analysis shows that we can explain to a large extent why empirical estimates of the investment uncertainty relationship differ.

  8. Evaluation of Workflow Management Systems - A Meta Model Approach

    Directory of Open Access Journals (Sweden)

    Michael Rosemann

    1998-11-01

    Full Text Available The automated enactment of processes through the use of workflow management systems enables the outsourcing of the control flow from application systems. By now a large number of systems, that follow different workflow paradigms, are available. This leads to the problem of selecting the appropriate workflow management system for a given situation. In this paper we outline the benefits of a meta model approach for the evaluation and comparison of different workflow management systems. After a general introduction on the topic of meta modeling the meta models of the workflow management systems WorkParty (Siemens Nixdorf and FlowMark (IBM are compared as an example. These product specific meta models can be generalized to meta reference models, which helps to specify a workflow methodology. Exemplary, an organisational reference meta model is presented, which helps users in specifying their requirements for a workflow management system.

  9. Meta-analysis in clinical trials revisited.

    Science.gov (United States)

    DerSimonian, Rebecca; Laird, Nan

    2015-11-01

    In this paper, we revisit a 1986 article we published in this Journal, Meta-Analysis in Clinical Trials, where we introduced a random-effects model to summarize the evidence about treatment efficacy from a number of related clinical trials. Because of its simplicity and ease of implementation, our approach has been widely used (with more than 12,000 citations to date) and the "DerSimonian and Laird method" is now often referred to as the 'standard approach' or a 'popular' method for meta-analysis in medical and clinical research. The method is especially useful for providing an overall effect estimate and for characterizing the heterogeneity of effects across a series of studies. Here, we review the background that led to the original 1986 article, briefly describe the random-effects approach for meta-analysis, explore its use in various settings and trends over time and recommend a refinement to the method using a robust variance estimator for testing overall effect. We conclude with a discussion of repurposing the method for Big Data meta-analysis and Genome Wide Association Studies for studying the importance of genetic variants in complex diseases. Published by Elsevier Inc.

  10. Hydropower externalities: A meta-analysis

    International Nuclear Information System (INIS)

    Mattmann, Matteo; Logar, Ivana; Brouwer, Roy

    2016-01-01

    This paper presents a meta-analysis of existing research related to the economic valuation of the external effects of hydropower. A database consisting of 81 observations derived from 29 studies valuing the non-market impacts of hydropower electricity generation is constructed with the main aim to quantify and explain the economic values for positive and negative hydropower externalities. Different meta-regression model specifications are used to test the robustness of significant determinants of non-market values, including different types of hydropower impacts. The explanatory and predictive power of the estimated models is relatively high. Whilst controlling for sample and study characteristics, we find significant evidence for public aversion towards deteriorations of landscape, vegetation and wildlife caused by hydropower projects. There is however only weak evidence of willingness to pay for mitigating these effects. The main positive externality of hydropower generation, the avoidance of greenhouse gas emission, positively influences welfare estimates when combined with the share of hydropower in national energy production. Sensitivity to scope is detected, but not linked to specific externalities or non-market valuation methods. - Highlights: • A global meta-analysis of valuation studies of hydropower externalities is presented. • Positive and negative externalities are distinguished. • Welfare losses due to environmental deteriorations outweigh gains of GHG reductions. • There is only weak evidence of public WTP for mitigating negative externalities. • The non-market values of hydropower externalities are sensitive to scope.

  11. A software complex intended for constructing applied models and meta-models on the basis of mathematical programming principles

    Directory of Open Access Journals (Sweden)

    Михаил Юрьевич Чернышов

    2013-12-01

    Full Text Available A software complex (SC elaborated by the authors on the basis of the language LMPL and representing a software tool intended for synthesis of applied software models and meta-models constructed on the basis of mathematical programming (MP principles is described. LMPL provides for an explicit form of declarative representation of MP-models, presumes automatic constructing and transformation of models and the capability of adding external software packages. The following software versions of the SC have been implemented: 1 a SC intended for representing the process of choosing an optimal hydroelectric power plant model (on the principles of meta-modeling and 2 a SC intended for representing the logic-sense relations between the models of a set of discourse formations in the discourse meta-model.

  12. Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions

    International Nuclear Information System (INIS)

    Konakli, Katerina; Sudret, Bruno

    2016-01-01

    The growing need for uncertainty analysis of complex computational models has led to an expanding use of meta-models across engineering and sciences. The efficiency of meta-modeling techniques relies on their ability to provide statistically-equivalent analytical representations based on relatively few evaluations of the original model. Polynomial chaos expansions (PCE) have proven a powerful tool for developing meta-models in a wide range of applications; the key idea thereof is to expand the model response onto a basis made of multivariate polynomials obtained as tensor products of appropriate univariate polynomials. The classical PCE approach nevertheless faces the “curse of dimensionality”, namely the exponential increase of the basis size with increasing input dimension. To address this limitation, the sparse PCE technique has been proposed, in which the expansion is carried out on only a few relevant basis terms that are automatically selected by a suitable algorithm. An alternative for developing meta-models with polynomial functions in high-dimensional problems is offered by the newly emerged low-rank approximations (LRA) approach. By exploiting the tensor–product structure of the multivariate basis, LRA can provide polynomial representations in highly compressed formats. Through extensive numerical investigations, we herein first shed light on issues relating to the construction of canonical LRA with a particular greedy algorithm involving a sequential updating of the polynomial coefficients along separate dimensions. Specifically, we examine the selection of optimal rank, stopping criteria in the updating of the polynomial coefficients and error estimation. In the sequel, we confront canonical LRA to sparse PCE in structural-mechanics and heat-conduction applications based on finite-element solutions. Canonical LRA exhibit smaller errors than sparse PCE in cases when the number of available model evaluations is small with respect to the input

  13. Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions

    Energy Technology Data Exchange (ETDEWEB)

    Konakli, Katerina, E-mail: konakli@ibk.baug.ethz.ch; Sudret, Bruno

    2016-09-15

    The growing need for uncertainty analysis of complex computational models has led to an expanding use of meta-models across engineering and sciences. The efficiency of meta-modeling techniques relies on their ability to provide statistically-equivalent analytical representations based on relatively few evaluations of the original model. Polynomial chaos expansions (PCE) have proven a powerful tool for developing meta-models in a wide range of applications; the key idea thereof is to expand the model response onto a basis made of multivariate polynomials obtained as tensor products of appropriate univariate polynomials. The classical PCE approach nevertheless faces the “curse of dimensionality”, namely the exponential increase of the basis size with increasing input dimension. To address this limitation, the sparse PCE technique has been proposed, in which the expansion is carried out on only a few relevant basis terms that are automatically selected by a suitable algorithm. An alternative for developing meta-models with polynomial functions in high-dimensional problems is offered by the newly emerged low-rank approximations (LRA) approach. By exploiting the tensor–product structure of the multivariate basis, LRA can provide polynomial representations in highly compressed formats. Through extensive numerical investigations, we herein first shed light on issues relating to the construction of canonical LRA with a particular greedy algorithm involving a sequential updating of the polynomial coefficients along separate dimensions. Specifically, we examine the selection of optimal rank, stopping criteria in the updating of the polynomial coefficients and error estimation. In the sequel, we confront canonical LRA to sparse PCE in structural-mechanics and heat-conduction applications based on finite-element solutions. Canonical LRA exhibit smaller errors than sparse PCE in cases when the number of available model evaluations is small with respect to the input

  14. Avoiding Boundary Estimates in Hierarchical Linear Models through Weakly Informative Priors

    Science.gov (United States)

    Chung, Yeojin; Rabe-Hesketh, Sophia; Gelman, Andrew; Dorie, Vincent; Liu, Jinchen

    2012-01-01

    Hierarchical or multilevel linear models are widely used for longitudinal or cross-sectional data on students nested in classes and schools, and are particularly important for estimating treatment effects in cluster-randomized trials, multi-site trials, and meta-analyses. The models can allow for variation in treatment effects, as well as…

  15. Neural model of gene regulatory network: a survey on supportive meta-heuristics.

    Science.gov (United States)

    Biswas, Surama; Acharyya, Sriyankar

    2016-06-01

    Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through various mathematical and computational schemes and reported in survey articles. Neural and neuro-fuzzy models have been the focus of attraction in bioinformatics. Predominant use of meta-heuristic algorithms in training neural models has proved its excellence. Considering these facts, this paper is organized to survey neural modelling schemes of GRN and the efficacy of meta-heuristic algorithms towards parameter learning (i.e. weighting connections) within the model. This survey paper renders two different structure-related approaches to infer GRN which are global structure approach and substructure approach. It also describes two neural modelling schemes, such as artificial neural network/recurrent neural network based modelling and neuro-fuzzy modelling. The meta-heuristic algorithms applied so far to learn the structure and parameters of neutrally modelled GRN have been reviewed here.

  16. Interval estimation of the overall treatment effect in a meta-analysis of a few small studies with zero events.

    Science.gov (United States)

    Pateras, Konstantinos; Nikolakopoulos, Stavros; Mavridis, Dimitris; Roes, Kit C B

    2018-03-01

    When a meta-analysis consists of a few small trials that report zero events, accounting for heterogeneity in the (interval) estimation of the overall effect is challenging. Typically, we predefine meta-analytical methods to be employed. In practice, data poses restrictions that lead to deviations from the pre-planned analysis, such as the presence of zero events in at least one study arm. We aim to explore heterogeneity estimators behaviour in estimating the overall effect across different levels of sparsity of events. We performed a simulation study that consists of two evaluations. We considered an overall comparison of estimators unconditional on the number of observed zero cells and an additional one by conditioning on the number of observed zero cells. Estimators that performed modestly robust when (interval) estimating the overall treatment effect across a range of heterogeneity assumptions were the Sidik-Jonkman, Hartung-Makambi and improved Paul-Mandel. The relative performance of estimators did not materially differ between making a predefined or data-driven choice. Our investigations confirmed that heterogeneity in such settings cannot be estimated reliably. Estimators whose performance depends strongly on the presence of heterogeneity should be avoided. The choice of estimator does not need to depend on whether or not zero cells are observed.

  17. Statistical methodology for estimating the mean difference in a meta-analysis without study-specific variance information.

    Science.gov (United States)

    Sangnawakij, Patarawan; Böhning, Dankmar; Adams, Stephen; Stanton, Michael; Holling, Heinz

    2017-04-30

    Statistical inference for analyzing the results from several independent studies on the same quantity of interest has been investigated frequently in recent decades. Typically, any meta-analytic inference requires that the quantity of interest is available from each study together with an estimate of its variability. The current work is motivated by a meta-analysis on comparing two treatments (thoracoscopic and open) of congenital lung malformations in young children. Quantities of interest include continuous end-points such as length of operation or number of chest tube days. As studies only report mean values (and no standard errors or confidence intervals), the question arises how meta-analytic inference can be developed. We suggest two methods to estimate study-specific variances in such a meta-analysis, where only sample means and sample sizes are available in the treatment arms. A general likelihood ratio test is derived for testing equality of variances in two groups. By means of simulation studies, the bias and estimated standard error of the overall mean difference from both methodologies are evaluated and compared with two existing approaches: complete study analysis only and partial variance information. The performance of the test is evaluated in terms of type I error. Additionally, we illustrate these methods in the meta-analysis on comparing thoracoscopic and open surgery for congenital lung malformations and in a meta-analysis on the change in renal function after kidney donation. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  18. A meta-analytic investigation of the relation between interpersonal attraction and enacted behavior.

    Science.gov (United States)

    Montoya, R Matthew; Kershaw, Christine; Prosser, Julie L

    2018-05-07

    We present a meta-analysis that investigated the relation between self-reported interpersonal attraction and enacted behavior. Our synthesis focused on (a) identifying the behaviors related to attraction; (b) evaluating the efficacy of models of the relation between attraction and behavior; (c) testing the impact of several moderators, including evaluative threat salience, cognitive appraisal salience, and the sex composition of the social interaction; and (d) investigating the degree of agreement between the meta-analytic findings and an ethnographic analysis. Using a multilevel modeling approach, an analysis of 309 effect sizes (N = 5,422) revealed a significant association (z = .20) between self-reported attraction and enacted behavior. Key findings include: (a) that the specific behaviors associated with attraction (e.g., eye contact, smiling, laughter, mimicry) are those behaviors research has linked to the development of trust/rapport; (b) direct behaviors (e.g., physical proximity, talking to), compared with indirect behaviors (e.g., eye contact, smiling, mimicry), were more strongly related to self-reported attraction; and (c) evaluative threat salience (e.g., fear of rejection) reduced the magnitude of the relation between direct behavior and affective attraction. Moreover, an ethnographic analysis revealed consistency between the behaviors identified by the meta-analysis and those behaviors identified by ethnographers as predictive of attraction. We discuss the implications of our findings for models of the relation between attraction and behavior, for the behavioral expressions of emotions, and for how attraction is measured and conceptualized. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  19. Providing the meta-model of development of competency using the meta-ethnography approach: Part 2. Synthesis of the available competency development models

    Directory of Open Access Journals (Sweden)

    Shahram Yazdani

    2016-12-01

    Full Text Available Background and Purpose: ConsideringBackground and Purpose: Considering the importance and necessity of competency-based education at a global level and with respect to globalization and the requirement of minimum competencies in medical fields, medical education communities and organizations worldwide have tried to determine the competencies, present frameworks and education models to respond to be sure of the ability of all graduates. In the literature, we observed numerous competency development models that refer to the same issues with different terminologies. It seems that evaluation and synthesis of all these models can finally result in designing a comprehensive meta-model for competency development.Methods: Meta-ethnography is a useful method for synthesis of qualitative research that is used to develop models that interpret the results in several studies. Considering that the aim of this study is to ultimately provide a competency development meta-model, in the previous section of the study, the literature review was conducted to achieve competency development models. Models obtained through the search were studied in details, and the key concepts of the models and overarching concepts were extracted in this section, models’ concepts were reciprocally translated and the available competency development models were synthesized.Results: A presentation of the competency development meta-model and providing a redefinition of the Dreyfus brothers model.Conclusions: Given the importance of competency-based education at a global level and the need to review curricula and competency-based curriculum design, it is required to provide competency development as well as meta-model to be the basis for curriculum development. As there are a variety of competency development models available, in this study, it was tried to develop the curriculum using them.Keywords: Meta-ethnography, Competency development, Meta-model, Qualitative synthesis

  20. Estimation and uncertainty of reversible Markov models.

    Science.gov (United States)

    Trendelkamp-Schroer, Benjamin; Wu, Hao; Paul, Fabian; Noé, Frank

    2015-11-07

    Reversibility is a key concept in Markov models and master-equation models of molecular kinetics. The analysis and interpretation of the transition matrix encoding the kinetic properties of the model rely heavily on the reversibility property. The estimation of a reversible transition matrix from simulation data is, therefore, crucial to the successful application of the previously developed theory. In this work, we discuss methods for the maximum likelihood estimation of transition matrices from finite simulation data and present a new algorithm for the estimation if reversibility with respect to a given stationary vector is desired. We also develop new methods for the Bayesian posterior inference of reversible transition matrices with and without given stationary vector taking into account the need for a suitable prior distribution preserving the meta-stable features of the observed process during posterior inference. All algorithms here are implemented in the PyEMMA software--http://pyemma.org--as of version 2.0.

  1. Schistosomiasis and water resources development: systematic review, meta-analysis, and estimates of people at risk.

    Science.gov (United States)

    Steinmann, Peter; Keiser, Jennifer; Bos, Robert; Tanner, Marcel; Utzinger, Jürg

    2006-07-01

    An estimated 779 million people are at risk of schistosomiasis, of whom 106 million (13.6%) live in irrigation schemes or in close proximity to large dam reservoirs. We identified 58 studies that examined the relation between water resources development projects and schistosomiasis, primarily in African settings. We present a systematic literature review and meta-analysis with the following objectives: (1) to update at-risk populations of schistosomiasis and number of people infected in endemic countries, and (2) to quantify the risk of water resources development and management on schistosomiasis. Using 35 datasets from 24 African studies, our meta-analysis showed pooled random risk ratios of 2.4 and 2.6 for urinary and intestinal schistosomiasis, respectively, among people living adjacent to dam reservoirs. The risk ratio estimate for studies evaluating the effect of irrigation on urinary schistosomiasis was in the range 0.02-7.3 (summary estimate 1.1) and that on intestinal schistosomiasis in the range 0.49-23.0 (summary estimate 4.7). Geographic stratification showed important spatial differences, idiosyncratic to the type of water resources development. We conclude that the development and management of water resources is an important risk factor for schistosomiasis, and hence strategies to mitigate negative effects should become integral parts in the planning, implementation, and operation of future water projects.

  2. Simulation-based estimation of mean and standard deviation for meta-analysis via Approximate Bayesian Computation (ABC).

    Science.gov (United States)

    Kwon, Deukwoo; Reis, Isildinha M

    2015-08-12

    When conducting a meta-analysis of a continuous outcome, estimated means and standard deviations from the selected studies are required in order to obtain an overall estimate of the mean effect and its confidence interval. If these quantities are not directly reported in the publications, they must be estimated from other reported summary statistics, such as the median, the minimum, the maximum, and quartiles. We propose a simulation-based estimation approach using the Approximate Bayesian Computation (ABC) technique for estimating mean and standard deviation based on various sets of summary statistics found in published studies. We conduct a simulation study to compare the proposed ABC method with the existing methods of Hozo et al. (2005), Bland (2015), and Wan et al. (2014). In the estimation of the standard deviation, our ABC method performs better than the other methods when data are generated from skewed or heavy-tailed distributions. The corresponding average relative error (ARE) approaches zero as sample size increases. In data generated from the normal distribution, our ABC performs well. However, the Wan et al. method is best for estimating standard deviation under normal distribution. In the estimation of the mean, our ABC method is best regardless of assumed distribution. ABC is a flexible method for estimating the study-specific mean and standard deviation for meta-analysis, especially with underlying skewed or heavy-tailed distributions. The ABC method can be applied using other reported summary statistics such as the posterior mean and 95 % credible interval when Bayesian analysis has been employed.

  3. Vitamin E and risk of age-related cataract: a meta-analysis.

    Science.gov (United States)

    Zhang, Yufei; Jiang, Wenjie; Xie, Zhutian; Wu, Wenlong; Zhang, Dongfeng

    2015-10-01

    We conducted a meta-analysis to evaluate the relationship between vitamin E and age-related cataract (ARC). The fixed- or random-effect model was selected based on heterogeneity. Meta-regression was used to explore potential sources of between-study heterogeneity. Publication bias was evaluated using Begg's test. The dose-response relationship was assessed by a restricted cubic spline model. Relevant studies were identified by a search of PubMed and the Cochrane Library to May 2014, without language restrictions. Studies involved samples of people of all ages. Dietary vitamin E intake, dietary and supplemental vitamin E intake, and high serum tocopherol levels were significantly associated with decreased risk of ARC, the pooled relative risk was 0·73 (95% CI 0·58, 0·92), 0·86 (95% CI 0·75, 0·99) and 0·77 (95% CI 0·66, 0·91), respectively. Supplemental vitamin E intake was non-significantly associated with ARC risk (relative risk=0·92; 95% CI 0·78, 1·07). The findings from dose-response analysis showed evidence of a non-linear association between dietary vitamin E intake and ARC. The risk of ARC decreased with dietary vitamin E intake from 7 mg/d (relative risk=0·94; 95% CI 0·90, 0·97). The findings of the meta-analysis indicated that dietary vitamin E intake, dietary and supplemental vitamin E intake, and high level of serum tocopherol might be significantly associated with reduced ARC risk.

  4. The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R.

    Science.gov (United States)

    Vogelgesang, Felicitas; Schlattmann, Peter; Dewey, Marc

    2018-05-01

    Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity - the two outcomes of interest in meta-analyses of diagnostic accuracy studies - utilizing random effects. Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach. Schattauer GmbH.

  5. A meta-model for computer executable dynamic clinical safety checklists.

    Science.gov (United States)

    Nan, Shan; Van Gorp, Pieter; Lu, Xudong; Kaymak, Uzay; Korsten, Hendrikus; Vdovjak, Richard; Duan, Huilong

    2017-12-12

    Safety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. This is due to the lack of a formal representation format that is both understandable by clinical experts and executable by computer programs. We developed a dynamic checklist meta-model with a three-step approach. Dynamic checklist modeling requirements were extracted by performing a domain analysis. Then, existing modeling approaches and tools were investigated with the purpose of reusing these languages. Finally, the meta-model was developed by eliciting domain concepts and their hierarchies. The feasibility of using the meta-model was validated by two case studies. The meta-model was mapped to specific modeling languages according to the requirements of hospitals. Using the proposed meta-model, a comprehensive coronary artery bypass graft peri-operative checklist set and a percutaneous coronary intervention peri-operative checklist set have been developed in a Dutch hospital and a Chinese hospital, respectively. The result shows that it is feasible to use the meta-model to facilitate the modeling and execution of dynamic checklists. We proposed a novel meta-model for the dynamic checklist with the purpose of facilitating creating dynamic checklists. The meta-model is a framework of reusing existing modeling languages and tools to model dynamic checklists. The feasibility of using the meta-model is validated by implementing a use case in the system.

  6. Work-related stress and Type 2 diabetes: systematic review and meta-analysis.

    Science.gov (United States)

    Cosgrove, M P; Sargeant, L A; Caleyachetty, R; Griffin, S J

    2012-04-01

    Work-related psychosocial stress has been hypothesized to increase the individual risk of Type 2 diabetes; however, observational epidemiological studies investigating the association between work-related psychosocial stress and Type 2 diabetes have provided an inconsistent picture. To evaluate whether work-related psychosocial stress (defined by a work-related stress model or by long work hours) is associated with the risk of Type 2 diabetes. A systematic review of the literature was conducted until March 2010. Studies eligible for inclusion were published observational epidemiological studies of adult participants in community or occupational settings if they had a measure of work-related stress on a validated scale or a measure of work hours or overtime assessed prior to, or at the same time as, assessment of Type 2 diabetes status. Where possible, meta-analysis was conducted to obtain summary odds ratios of the association. We located nine studies (four prospective, one case-control and four cross-sectional). The meta-analyses did not show any statistically significant associations between any individual aspect of work-related psychosocial stress or job strain and risk of Type 2 diabetes. The specific hypothesis that a working environment characterized by high psychosocial stress is directly associated with increased risk of Type 2 diabetes could not be supported from the meta-analysis.

  7. Modeling and understanding of effects of randomness in arrays of resonant meta-atoms

    DEFF Research Database (Denmark)

    Tretyakov, Sergei A.; Albooyeh, Mohammad; Alitalo, Pekka

    2013-01-01

    In this review presentation we will discuss approaches to modeling and understanding electromagnetic properties of 2D and 3D lattices of small resonant particles (meta-atoms) in transition from regular (periodic) to random (amorphous) states. Nanostructured metasurfaces (2D) and metamaterials (3D......) are arrangements of optically small but resonant particles (meta-atoms). We will present our results on analytical modeling of metasurfaces with periodical and random arrangements of electrically and magnetically resonant meta-atoms with identical or random sizes, both for the normal and oblique-angle excitations....... We show how the electromagnetic response of metasurfaces is related to the statistical parameters of the structure. Furthermore, we will discuss the phenomenon of anti-resonance in extracted effective parameters of metamaterials and clarify its relation to the periodicity (or amorphous nature...

  8. Estimation of natural age of menopause in Iranian women: A meta-analysis study

    Directory of Open Access Journals (Sweden)

    Abdolreza Rajaeefard

    2011-10-01

    Full Text Available Introduction: The mean age of menopause have been reported at the age of 51 in the world and regarding the increase in life expectancy in many countries more than a third of the life time of women i s in menopause period. The importance of menopause is due to its relationship with various diseases and quality of life. The present study was conducted to estimate the average natural age of menopause in women based on a meta-analysis study. Material and Methods: In a meta-analysis study on all the existing articles in the natural age o f menopause in Iran, 21 articles were selected based on inclusion criteria. Begg and Egger tests fo r publication bias and Cochrane test were used to determine the heterogeneity among samples. ???? estimate of mean calculated based on Random effect model in Stata11 software. Results: The publication bias assumption was rejected by Begg and Egger tests with significant value s equal to 0.174 and 0.446 respectively. There was a heterogeneity among samples (Q=4626.3, df=20 , P<0.001. So based on random effect model the mean age of menopause was calculated as 48.183 with 95 % CI=47.457-48.91. Conclusion: The average age of natural menopause in Iranian women is favorable to some places of Middle East, but is less compared with developed countries and the world mean. Because of the importance of this period in women, educational programs seem to be necessary.

  9. Gender-specific estimates of COPD prevalence: a systematic review and meta-analysis

    Directory of Open Access Journals (Sweden)

    Ntritsos G

    2018-05-01

    Full Text Available Georgios Ntritsos,1 Jacob Franek,2 Lazaros Belbasis,1 Maria A Christou,1 Georgios Markozannes,1 Pablo Altman,3 Robert Fogel,3 Tobias Sayre,2 Evangelia E Ntzani,1 Evangelos Evangelou1,4 1Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece; 2Doctor Evidence, Client Solutions, Santa Monica, CA, USA; 3Global Medical Affairs, Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA; 4Department of Epidemiology and Biostatistics, Imperial College London, London, UK Rationale: COPD has been perceived as being a disease of older men. However, >7 million women are estimated to live with COPD in the USA alone. Despite a growing body of literature suggesting an increasing burden of COPD in women, the evidence is limited. Objectives: To assess and synthesize the available evidence among population-based epidemiologic studies and calculate the global prevalence of COPD in men and women. Materials and methods: A systematic review and meta-analysis reporting gender-specific prevalence of COPD was undertaken. Gender-specific prevalence estimates were abstracted from relevant studies. Associated patient characteristics as well as custom variables pertaining to the diagnostic method and other important epidemiologic covariates were also collected. A Bayesian random-effects meta-analysis was performed investigating gender-specific prevalence of COPD stratified by age, geography, calendar time, study setting, diagnostic method, and disease severity. Measurements and main results: Among 194 eligible studies, summary prevalence was 9.23% (95% credible interval [CrI]: 8.16%–10.36% in men and 6.16% (95% CrI: 5.41%–6.95% in women. Gender prevalences varied widely by the World Health Organization Global Burden of Disease subregions, with the highest female prevalence found in North America (8.07% vs 7.30% and in participants in urban settings (13.03% vs 8.34%. Meta

  10. Automated generation of node-splitting models for assessment of inconsistency in network meta-analysis.

    Science.gov (United States)

    van Valkenhoef, Gert; Dias, Sofia; Ades, A E; Welton, Nicky J

    2016-03-01

    Network meta-analysis enables the simultaneous synthesis of a network of clinical trials comparing any number of treatments. Potential inconsistencies between estimates of relative treatment effects are an important concern, and several methods to detect inconsistency have been proposed. This paper is concerned with the node-splitting approach, which is particularly attractive because of its straightforward interpretation, contrasting estimates from both direct and indirect evidence. However, node-splitting analyses are labour-intensive because each comparison of interest requires a separate model. It would be advantageous if node-splitting models could be estimated automatically for all comparisons of interest. We present an unambiguous decision rule to choose which comparisons to split, and prove that it selects only comparisons in potentially inconsistent loops in the network, and that all potentially inconsistent loops in the network are investigated. Moreover, the decision rule circumvents problems with the parameterisation of multi-arm trials, ensuring that model generation is trivial in all cases. Thus, our methods eliminate most of the manual work involved in using the node-splitting approach, enabling the analyst to focus on interpreting the results. © 2015 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.

  11. The relative pose estimation of aircraft based on contour model

    Science.gov (United States)

    Fu, Tai; Sun, Xiangyi

    2017-02-01

    This paper proposes a relative pose estimation approach based on object contour model. The first step is to obtain a two-dimensional (2D) projection of three-dimensional (3D)-model-based target, which will be divided into 40 forms by clustering and LDA analysis. Then we proceed by extracting the target contour in each image and computing their Pseudo-Zernike Moments (PZM), thus a model library is constructed in an offline mode. Next, we spot a projection contour that resembles the target silhouette most in the present image from the model library with reference of PZM; then similarity transformation parameters are generated as the shape context is applied to match the silhouette sampling location, from which the identification parameters of target can be further derived. Identification parameters are converted to relative pose parameters, in the premise that these values are the initial result calculated via iterative refinement algorithm, as the relative pose parameter is in the neighborhood of actual ones. At last, Distance Image Iterative Least Squares (DI-ILS) is employed to acquire the ultimate relative pose parameters.

  12. Effects of stimulus type and strategy on mental rotation network:an Activation Likelihood Estimation meta-analysis

    Directory of Open Access Journals (Sweden)

    Barbara eTomasino

    2016-01-01

    Full Text Available We could predict how an object would look like if we were to see it from different viewpoints. The brain network governing mental rotation (MR has been studied using a variety of stimuli and tasks instructions. By using activation likelihood estimation (ALE meta-analysis we tested whether different MR networks can be modulated by the type of stimulus (body vs. non body parts or by the type of tasks instructions (motor imagery-based vs. non-motor imagery-based MR instructions. Testing for the bodily and non-bodily stimulus axis revealed a bilateral sensorimotor activation for bodily-related as compared to non bodily-related stimuli and a posterior right lateralized activation for non bodily-related as compared to bodily-related stimuli. A top-down modulation of the network was exerted by the MR tasks instructions frame with a bilateral (preferentially sensorimotor left network for motor imagery- vs. non-motor imagery-based MR instructions and the latter activating a preferentially posterior right occipito-temporal-parietal network. The present quantitative meta-analysis summarizes and amends previous descriptions of the brain network related to MR and shows how it is modulated by top-down and bottom-up experimental factors.

  13. Implementation and use of Gaussian process meta model for sensitivity analysis of numerical models: application to a hydrogeological transport computer code

    International Nuclear Information System (INIS)

    Marrel, A.

    2008-01-01

    In the studies of environmental transfer and risk assessment, numerical models are used to simulate, understand and predict the transfer of pollutant. These computer codes can depend on a high number of uncertain input parameters (geophysical variables, chemical parameters, etc.) and can be often too computer time expensive. To conduct uncertainty propagation studies and to measure the importance of each input on the response variability, the computer code has to be approximated by a meta model which is build on an acceptable number of simulations of the code and requires a negligible calculation time. We focused our research work on the use of Gaussian process meta model to make the sensitivity analysis of the code. We proposed a methodology with estimation and input selection procedures in order to build the meta model in the case of a high number of inputs and with few simulations available. Then, we compared two approaches to compute the sensitivity indices with the meta model and proposed an algorithm to build prediction intervals for these indices. Afterwards, we were interested in the choice of the code simulations. We studied the influence of different sampling strategies on the predictiveness of the Gaussian process meta model. Finally, we extended our statistical tools to a functional output of a computer code. We combined a decomposition on a wavelet basis with the Gaussian process modelling before computing the functional sensitivity indices. All the tools and statistical methodologies that we developed were applied to the real case of a complex hydrogeological computer code, simulating radionuclide transport in groundwater. (author) [fr

  14. Baseline micronuclei frequency in children: estimates from meta- and pooled analyses

    DEFF Research Database (Denmark)

    Neri, Monica; Ceppi, Marcello; Knudsen, Lisbeth E

    2005-01-01

    the statistical power of studies and to assess the quality of data. In this article, we provide estimates of the baseline frequency of MN in children, conducting a meta-analysis of MN frequency reported by field studies in children and a pooled analysis of individual data [available from published studies...

  15. Clinical outcomes after estimated versus calculated activity of radioiodine for the treatment of hyperthyroidism: systematic review and meta-analysis.

    Science.gov (United States)

    de Rooij, A; Vandenbroucke, J P; Smit, J W A; Stokkel, M P M; Dekkers, O M

    2009-11-01

    Despite the long experience with radioiodine for hyperthyroidism, controversy remains regarding the optimal method to determine the activity that is required to achieve long-term euthyroidism. To compare the effect of estimated versus calculated activity of radioiodine in hyperthyroidism. Design Systematic review and meta-analysis. We searched the databases Medline, EMBASE, Web of Science, and Cochrane Library for randomized and nonrandomized studies, comparing the effect of activity estimation methods with dosimetry for hyperthyroidism. The main outcome measure was the frequency of treatment success, defined as persistent euthyroidism after radioiodine treatment at the end of follow-up in the dose estimated and calculated dosimetry group. Furthermore, we assessed the cure rates of hyperthyroidism. Three randomized and five nonrandomized studies, comparing the effect of estimated versus calculated activity of radioiodine on clinical outcomes for the treatment of hyperthyroidism, were included. The weighted mean relative frequency of successful treatment outcome (euthyroidism) was 1.03 (95% confidence interval (CI) 0.91-1.16) for estimated versus calculated activity; the weighted mean relative frequency of cure of hyperthyroidism (eu- or hypothyroidism) was 1.03 (95% CI 0.96-1.10). Subgroup analysis showed a relative frequency of euthyroidism of 1.03 (95% CI 0.84-1.26) for Graves' disease and of 1.05 (95% CI 0.91-1.19) for toxic multinodular goiter. The two main methods used to determine the activity in the treatment of hyperthyroidism with radioiodine, estimated and calculated, resulted in an equally successful treatment outcome. However, the heterogeneity of the included studies is a strong limitation that prevents a definitive conclusion from this meta-analysis.

  16. Anatomical likelihood estimation meta-analysis of grey and white matter anomalies in autism spectrum disorders

    Directory of Open Access Journals (Sweden)

    Thomas P. DeRamus

    2015-01-01

    Full Text Available Autism spectrum disorders (ASD are characterized by impairments in social communication and restrictive, repetitive behaviors. While behavioral symptoms are well-documented, investigations into the neurobiological underpinnings of ASD have not resulted in firm biomarkers. Variability in findings across structural neuroimaging studies has contributed to difficulty in reliably characterizing the brain morphology of individuals with ASD. These inconsistencies may also arise from the heterogeneity of ASD, and wider age-range of participants included in MRI studies and in previous meta-analyses. To address this, the current study used coordinate-based anatomical likelihood estimation (ALE analysis of 21 voxel-based morphometry (VBM studies examining high-functioning individuals with ASD, resulting in a meta-analysis of 1055 participants (506 ASD, and 549 typically developing individuals. Results consisted of grey, white, and global differences in cortical matter between the groups. Modeled anatomical maps consisting of concentration, thickness, and volume metrics of grey and white matter revealed clusters suggesting age-related decreases in grey and white matter in parietal and inferior temporal regions of the brain in ASD, and age-related increases in grey matter in frontal and anterior-temporal regions. White matter alterations included fiber tracts thought to play key roles in information processing and sensory integration. Many current theories of pathobiology ASD suggest that the brains of individuals with ASD may have less-functional long-range (anterior-to-posterior connections. Our findings of decreased cortical matter in parietal–temporal and occipital regions, and thickening in frontal cortices in older adults with ASD may entail altered cortical anatomy, and neurodevelopmental adaptations.

  17. Bayesian mixture modeling of significant p values: A meta-analytic method to estimate the degree of contamination from H₀.

    Science.gov (United States)

    Gronau, Quentin Frederik; Duizer, Monique; Bakker, Marjan; Wagenmakers, Eric-Jan

    2017-09-01

    Publication bias and questionable research practices have long been known to corrupt the published record. One method to assess the extent of this corruption is to examine the meta-analytic collection of significant p values, the so-called p -curve (Simonsohn, Nelson, & Simmons, 2014a). Inspired by statistical research on false-discovery rates, we propose a Bayesian mixture model analysis of the p -curve. Our mixture model assumes that significant p values arise either from the null-hypothesis H ₀ (when their distribution is uniform) or from the alternative hypothesis H1 (when their distribution is accounted for by a simple parametric model). The mixture model estimates the proportion of significant results that originate from H ₀, but it also estimates the probability that each specific p value originates from H ₀. We apply our model to 2 examples. The first concerns the set of 587 significant p values for all t tests published in the 2007 volumes of Psychonomic Bulletin & Review and the Journal of Experimental Psychology: Learning, Memory, and Cognition; the mixture model reveals that p values higher than about .005 are more likely to stem from H ₀ than from H ₁. The second example concerns 159 significant p values from studies on social priming and 130 from yoked control studies. The results from the yoked controls confirm the findings from the first example, whereas the results from the social priming studies are difficult to interpret because they are sensitive to the prior specification. To maximize accessibility, we provide a web application that allows researchers to apply the mixture model to any set of significant p values. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  18. Examining the Job-Related, Psychological, and Physical Outcomes of Workplace Sexual Harassment: A Meta-Analytic Review

    Science.gov (United States)

    Chan, Darius K-S.; Lam, Chun Bun; Chow, Suk Yee; Cheung, Shu Fai

    2008-01-01

    This study was designed to examine the job-related, psychological, and physical outcomes of sexual harassment in the workplace. Using a meta-analytic approach, we analyzed findings from 49 primary studies, with a total sample size of 89,382, to obtain estimates of the population mean effect size of the association between sexual harassment and…

  19. Effect of Risk of Bias on the Effect Size of Meta-Analytic Estimates in Randomized Controlled Trials in Periodontology and Implant Dentistry

    Science.gov (United States)

    Faggion, Clovis Mariano; Wu, Yun-Chun; Scheidgen, Moritz; Tu, Yu-Kang

    2015-01-01

    Background Risk of bias (ROB) may threaten the internal validity of a clinical trial by distorting the magnitude of treatment effect estimates, although some conflicting information on this assumption exists. Objective The objective of this study was evaluate the effect of ROB on the magnitude of treatment effect estimates in randomized controlled trials (RCTs) in periodontology and implant dentistry. Methods A search for Cochrane systematic reviews (SRs), including meta-analyses of RCTs published in periodontology and implant dentistry fields, was performed in the Cochrane Library in September 2014. Random-effect meta-analyses were performed by grouping RCTs with different levels of ROBs in three domains (sequence generation, allocation concealment, and blinding of outcome assessment). To increase power and precision, only SRs with meta-analyses including at least 10 RCTs were included. Meta-regression was performed to investigate the association between ROB characteristics and the magnitudes of intervention effects in the meta-analyses. Results Of the 24 initially screened SRs, 21 SRs were excluded because they did not include at least 10 RCTs in the meta-analyses. Three SRs (two from periodontology field) generated information for conducting 27 meta-analyses. Meta-regression did not reveal significant differences in the relationship of the ROB level with the size of treatment effect estimates, although a trend for inflated estimates was observed in domains with unclear ROBs. Conclusion In this sample of RCTs, high and (mainly) unclear risks of selection and detection biases did not seem to influence the size of treatment effect estimates, although several confounders might have influenced the strength of the association. PMID:26422698

  20. Random-Effects Models for Meta-Analytic Structural Equation Modeling: Review, Issues, and Illustrations

    Science.gov (United States)

    Cheung, Mike W.-L.; Cheung, Shu Fai

    2016-01-01

    Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…

  1. Introduction, comparison, and validation of Meta-Essentials: A free and simple tool for meta-analysis.

    Science.gov (United States)

    Suurmond, Robert; van Rhee, Henk; Hak, Tony

    2017-12-01

    We present a new tool for meta-analysis, Meta-Essentials, which is free of charge and easy to use. In this paper, we introduce the tool and compare its features to other tools for meta-analysis. We also provide detailed information on the validation of the tool. Although free of charge and simple, Meta-Essentials automatically calculates effect sizes from a wide range of statistics and can be used for a wide range of meta-analysis applications, including subgroup analysis, moderator analysis, and publication bias analyses. The confidence interval of the overall effect is automatically based on the Knapp-Hartung adjustment of the DerSimonian-Laird estimator. However, more advanced meta-analysis methods such as meta-analytical structural equation modelling and meta-regression with multiple covariates are not available. In summary, Meta-Essentials may prove a valuable resource for meta-analysts, including researchers, teachers, and students. © 2017 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.

  2. On the Multilevel Nature of Meta-Analysis: A Tutorial, Comparison of Software Programs, and Discussion of Analytic Choices.

    Science.gov (United States)

    Pastor, Dena A; Lazowski, Rory A

    2018-01-01

    The term "multilevel meta-analysis" is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term "multilevel meta-analysis" is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analytic choices, not between meta-analytic models, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed.

  3. Meta-Analyses of the Associations of Respiratory Health Effectswith Dampness and Mold in Homes

    Energy Technology Data Exchange (ETDEWEB)

    Fisk, William J.; Lei-Gomez, Quanhong; Mendell, Mark J.

    2006-01-01

    The Institute of Medicine (IOM) of the National Academy of Sciences recently completed a critical review of the scientific literature pertaining to the association of indoor dampness and mold contamination with adverse health effects. In this paper, we report the results of quantitative meta-analysis of the studies reviewed in the IOM report. We developed point estimates and confidence intervals (CIs) to summarize the association of several respiratory and asthma-related health outcomes with the presence of dampness and mold in homes. The odds ratios and confidence intervals from the original studies were transformed to the log scale and random effect models were applied to the log odds ratios and their variance. Models were constructed both accounting for the correlation between multiple results within the studies analyzed and ignoring such potential correlation. Central estimates of ORs for the health outcomes ranged from 1.32 to 2.10, with most central estimates between 1.3 and 1.8. Confidence intervals (95%) excluded unity except in two of 28 instances, and in most cases the lower bound of the CI exceeded 1.2. In general, the two meta-analysis methods produced similar estimates for ORs and CIs. Based on the results of the meta-analyses, building dampness and mold are associated with approximately 30% to 80% increases in a variety of respiratory and asthma-related health outcomes. The results of these meta-analyses reinforce the IOM's recommendation that actions be taken to prevent and reduce building dampness problems.

  4. Estimating the Global Incidence of Aneurysmal Subarachnoid Hemorrhage: A Systematic Review for Central Nervous System Vascular Lesions and Meta-Analysis of Ruptured Aneurysms.

    Science.gov (United States)

    Hughes, Joshua D; Bond, Kamila M; Mekary, Rania A; Dewan, Michael C; Rattani, Abbas; Baticulon, Ronnie; Kato, Yoko; Azevedo-Filho, Hildo; Morcos, Jacques J; Park, Kee B

    2018-04-09

    There is increasing acknowledgement that surgical care is important in global health initiatives. In particular, neurosurgical care is as limited as 1 per 10 million people in parts of the world. We performed a systematic literature review to examine the worldwide incidence of central nervous system vascular lesions and a meta-analysis of aneurysmal subarachnoid hemorrhage (aSAH) to define the disease burden and inform neurosurgical global health efforts. A systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to estimate the global epidemiology of central nervous system vascular lesions, including unruptured and ruptured aneurysms, arteriovenous malformations, cavernous malformations, dural arteriovenous fistulas, developmental venous anomalies, and vein of Galen malformations. Results were organized by World Health Organization regions. After literature review, because of a lack of data from particular World Health Organization regions, we determined we could only provide an estimate of aSAH. Using data from studies with aSAH and 12 high-quality stroke studies from regions lacking data, we meta-analyzed the yearly crude incidence of aSAH per 100,000 persons. Estimates were generated via random-effects models. From an initial yield of 1492 studies, 46 manuscripts on aSAH incidence were included. The final meta-analysis included 58 studies from 31 different countries. We estimated the global crude incidence for aSAH to be 6.67 per 100,000 persons with a wide variation across WHO regions from 0.71 to 12.38 per 100,000 persons. Worldwide, almost 500,000 individuals will suffer from aSAH each year, with almost two-thirds in low- and middle-income countries. Copyright © 2018 Elsevier Inc. All rights reserved.

  5. MetaGaAP: A Novel Pipeline to Estimate Community Composition and Abundance from Non-Model Sequence Data

    Directory of Open Access Journals (Sweden)

    Christopher Noune

    2017-02-01

    Full Text Available Next generation sequencing and bioinformatic approaches are increasingly used to quantify microorganisms within populations by analysis of ‘meta-barcode’ data. This approach relies on comparison of amplicon sequences of ‘barcode’ regions from a population with public-domain databases of reference sequences. However, for many organisms relevant ‘barcode’ regions may not have been identified and large databases of reference sequences may not be available. A workflow and software pipeline, ‘MetaGaAP,’ was developed to identify and quantify genotypes through four steps: shotgun sequencing and identification of polymorphisms in a metapopulation to identify custom ‘barcode’ regions of less than 30 polymorphisms within the span of a single ‘read’, amplification and sequencing of the ‘barcode’, generation of a custom database of polymorphisms, and quantitation of the relative abundance of genotypes. The pipeline and workflow were validated in a ‘wild type’ Alphabaculovirus isolate, Helicoverpa armigera single nucleopolyhedrovirus (HaSNPV-AC53 and a tissue-culture derived strain (HaSNPV-AC53-T2. The approach was validated by comparison of polymorphisms in amplicons and shotgun data, and by comparison of predicted dominant and co-dominant genotypes with Sanger sequences. The computational power required to generate and search the database effectively limits the number of polymorphisms that can be included in a barcode to 30 or less. The approach can be used in quantitative analysis of the ecology and pathology of non-model organisms.

  6. META-COMMUNICATION FOR REFLECTIVE ONLINE CONVERSATIONS: Models for Distance Education

    Directory of Open Access Journals (Sweden)

    Yasin OZARSLAN

    2012-01-01

    Full Text Available “Meta Communication” is the process between message designers when they are talking about the learning process, as distinguished from their articulation of the “substantive” learning, itself. Therefore, it is important to understand how to design reflective online conversations and how to implement a diverse milieu for prospective online learners so that they are able to transfer their information, knowledge, and learning from theoretical forms to real life experiences. This book discusses meta-communication for reflective online conversations to provide digital people with models for distance education. This book brings together meta-communication, distance education, and models as well as reflective online conversations at the same time.The book is consisted of 321 pages covering 17 chapters. Topics covered in this book are divided into four sections: Meta-communicative knowledge building and online communications, dynamic models of meta-communication and reflective conversations, designing online messages for reflections, and meta-communicative assessments and reflective communication skills. The book's broader audience is anyone who is involved in e-learning.

  7. MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heuristics.

    Science.gov (United States)

    Helaers, Raphaël; Milinkovitch, Michel C

    2010-07-15

    The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high

  8. Russia-specific relative risks and their effects on the estimated alcohol-attributable burden of disease.

    Science.gov (United States)

    Shield, Kevin D; Rehm, Jürgen

    2015-05-10

    Alcohol consumption is a major risk factor for the burden of disease globally. This burden is estimated using Relative Risk (RR) functions for alcohol from meta-analyses that use data from all countries; however, for Russia and surrounding countries, country-specific risk data may need to be used. The objective of this paper is to compare the estimated burden of alcohol consumption calculated using Russia-specific alcohol RRs with the estimated burden of alcohol consumption calculated using alcohol RRs from meta-analyses. Data for 2012 on drinking indicators were calculated based on the Global Information System on Alcohol and Health. Data for 2012 on mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life Years (DALYs) lost by cause were obtained by country from the World Health Organization. Alcohol Population-Attributable Fractions (PAFs) were calculated based on a risk modelling methodology from Russia. These PAFs were compared to PAFs calculated using methods applied for all other countries. The 95% Uncertainty Intervals (UIs) for the alcohol PAFs were calculated using a Monte Carlo-like method. Using Russia-specific alcohol RR functions, in Russia in 2012 alcohol caused an estimated 231,900 deaths (95% UI: 185,600 to 278,200) (70,800 deaths among women and 161,100 deaths among men) and 13,295,000 DALYs lost (95% UI: 11,242,000 to 15,348,000) (3,670,000 DALYs lost among women and 9,625,000 DALYs lost among men) among people 0 to 64 years of age. This compares to an estimated 165,600 deaths (95% UI: 97,200 to 228,100) (29,700 deaths among women and 135,900 deaths among men) and 10,623,000 DALYs lost (95% UI: 7,265,000 to 13,754,000) (1,783,000 DALYs lost among women and 8,840,000 DALYs lost among men) among people 0 to 64 years of age caused by alcohol when non-Russia-specific alcohol RRs were used. Results indicate that if the Russia-specific RRs are used when estimating the health burden attributable to alcohol consumption in

  9. Adequacy of relative and absolute risk models for lifetime risk estimate of radiation-induced cancer

    International Nuclear Information System (INIS)

    McBride, M.; Coldman, A.J.

    1988-03-01

    This report examines the applicability of the relative (multiplicative) and absolute (additive) models in predicting lifetime risk of radiation-induced cancer. A review of the epidemiologic literature, and a discussion of the mathematical models of carcinogenesis and their relationship to these models of lifetime risk, are included. Based on the available data, the relative risk model for the estimation of lifetime risk is preferred for non-sex-specific epithelial tumours. However, because of lack of knowledge concerning other determinants of radiation risk and of background incidence rates, considerable uncertainty in modelling lifetime risk still exists. Therefore, it is essential that follow-up of exposed cohorts be continued so that population-based estimates of lifetime risk are available

  10. Meta-analytic structural equation modelling

    CERN Document Server

    Jak, Suzanne

    2015-01-01

    This book explains how to employ MASEM, the combination of meta-analysis (MA) and structural equation modelling (SEM). It shows how by using MASEM, a single model can be tested to explain the relationships between a set of variables in several studies. This book gives an introduction to MASEM, with a focus on the state of the art approach: the two stage approach of Cheung and Cheung & Chan. Both, the fixed and the random approach to MASEM are illustrated with two applications to real data. All steps that have to be taken to perform the analyses are discussed extensively. All data and syntax files are available online, so that readers can imitate all analyses. By using SEM for meta-analysis, this book shows how to benefit from all available information from all available studies, even if few or none of the studies report about all relationships that feature in the full model of interest.

  11. Meta-DiSc: a software for meta-analysis of test accuracy data.

    Science.gov (United States)

    Zamora, Javier; Abraira, Victor; Muriel, Alfonso; Khan, Khalid; Coomarasamy, Arri

    2006-07-12

    Systematic reviews and meta-analyses of test accuracy studies are increasingly being recognised as central in guiding clinical practice. However, there is currently no dedicated and comprehensive software for meta-analysis of diagnostic data. In this article, we present Meta-DiSc, a Windows-based, user-friendly, freely available (for academic use) software that we have developed, piloted, and validated to perform diagnostic meta-analysis. Meta-DiSc a) allows exploration of heterogeneity, with a variety of statistics including chi-square, I-squared and Spearman correlation tests, b) implements meta-regression techniques to explore the relationships between study characteristics and accuracy estimates, c) performs statistical pooling of sensitivities, specificities, likelihood ratios and diagnostic odds ratios using fixed and random effects models, both overall and in subgroups and d) produces high quality figures, including forest plots and summary receiver operating characteristic curves that can be exported for use in manuscripts for publication. All computational algorithms have been validated through comparison with different statistical tools and published meta-analyses. Meta-DiSc has a Graphical User Interface with roll-down menus, dialog boxes, and online help facilities. Meta-DiSc is a comprehensive and dedicated test accuracy meta-analysis software. It has already been used and cited in several meta-analyses published in high-ranking journals. The software is publicly available at http://www.hrc.es/investigacion/metadisc_en.htm.

  12. Association between Work-Related Stress and Risk for Type 2 Diabetes: A Systematic Review and Meta-Analysis of Prospective Cohort Studies.

    Science.gov (United States)

    Sui, Hua; Sun, Nijing; Zhan, Libin; Lu, Xiaoguang; Chen, Tuo; Mao, Xinyong

    2016-01-01

    The prevalence of type 2 diabetes is increasing rapidly around the world. Work-related stress is thought to be a major risk factor for type 2 diabetes; however, this association has not been widely studied, and the findings that have been reported are inconsistent. Therefore, we conducted a meta-analysis of prospective cohort studies to explore the association between work-related stress and risk for type 2 diabetes. A systematic literature search and manual search limited to articles published in English were performed to select the prospective cohort studies evaluated the association between work-related stress and risk for type 2 diabetes up to September 2014 from four electronic databases including PubMed, EMBASE, the Cochrane Library and Web of Science. A random-effects model was used to estimate the overall risk. No significant association was found between work-related stress and risk for type 2 diabetes based on meta-analysis of seven prospective cohort studies involving 214,086 participants and 5,511 cases (job demands: relative risk 0.94 [95% confidence interval 0.72-1.23]; decision latitude: relative risk 1.16 [0.85-1.58]; job strain: relative risk 1.12 [.0.95-1.32]). However, an association between work-related stress and risk for type 2 diabetes was observed in women (job strain: relative risk 1.22 [1.01-1.46]) (P = 0.04). A sensitivity analysis conducted by excluding one study in each turn yielded similar results. No publication bias was detected with a funnel plot despite the limited number of studies included in the analysis. The results of this meta-analysis did not confirm a direct association between work-related stress and risk for type 2 diabetes. In subgroup analyses we found job strain was a risk factor for type 2 diabetes in women.

  13. Effects of beverage alcohol price and tax levels on drinking: a meta-analysis of 1003 estimates from 112 studies.

    Science.gov (United States)

    Wagenaar, Alexander C; Salois, Matthew J; Komro, Kelli A

    2009-02-01

    We conducted a systematic review of studies examining relationships between measures of beverage alcohol tax or price levels and alcohol sales or self-reported drinking. A total of 112 studies of alcohol tax or price effects were found, containing 1003 estimates of the tax/price-consumption relationship. Studies included analyses of alternative outcome measures, varying subgroups of the population, several statistical models, and using different units of analysis. Multiple estimates were coded from each study, along with numerous study characteristics. Using reported estimates, standard errors, t-ratios, sample sizes and other statistics, we calculated the partial correlation for the relationship between alcohol price or tax and sales or drinking measures for each major model or subgroup reported within each study. Random-effects models were used to combine studies for inverse variance weighted overall estimates of the magnitude and significance of the relationship between alcohol tax/price and drinking. Simple means of reported elasticities are -0.46 for beer, -0.69 for wine and -0.80 for spirits. Meta-analytical results document the highly significant relationships (P price measures and indices of sales or consumption of alcohol (aggregate-level r = -0.17 for beer, -0.30 for wine, -0.29 for spirits and -0.44 for total alcohol). Price/tax also affects heavy drinking significantly (mean reported elasticity = -0.28, individual-level r = -0.01, P prices and taxes are related inversely to drinking. Effects are large compared to other prevention policies and programs. Public policies that raise prices of alcohol are an effective means to reduce drinking.

  14. Dietary Assessment in the MetaCardis Study: Development and Relative Validity of an Online Food Frequency Questionnaire.

    Science.gov (United States)

    Verger, Eric O; Armstrong, Patrice; Nielsen, Trine; Chakaroun, Rima; Aron-Wisnewsky, Judith; Gøbel, Rikke Juul; Schütz, Tatjana; Delaere, Fabien; Gausseres, Nicolas; Clément, Karine; Holmes, Bridget A

    2017-06-01

    The European study MetaCardis aims to investigate the role of the gut microbiota in health and cardiometabolic diseases in France, Germany, and Denmark. To evaluate long-term diet-disease relationships, a food frequency questionnaire (FFQ) was found to be the most relevant dietary assessment method for the MetaCardis study. The objectives of this study were to describe the development of three semiquantitative online FFQs used in the MetaCardis study-one FFQ per country-and to assess the relative validity of the French MetaCardis FFQ. The layout and format of the MetaCardis FFQ was based on the European Prospective Investigation of Cancer (EPIC)-Norfolk FFQ and the content was based on relevant European FFQs. Portion size and nutrient composition were derived from national food consumption surveys and food composition databases. To assess the validity of the French MetaCardis FFQ, a cross-sectional study design was utilized. The validation study included 324 adults recruited between September 2013 and June 2015 from different hospitals in Paris, France. Food intakes were measured with both the French MetaCardis FFQ and 3 consecutive self-administered web-based 24-hour dietary recalls (DRs). Several measures of validity of the French MetaCardis FFQ were evaluated: estimations of food groups, energy, and nutrient intakes from the DRs and the FFQ, Spearman and Pearson correlations, cross-classification, and Bland-Altman analyses. The French MetaCardis FFQ tended to report higher food, energy, and nutrient intakes compared with the DRs. Mean correlation coefficient was 0.429 for food, 0.460 for energy, 0.544 for macronutrients, 0.640 for alcohol, and 0.503 for micronutrient intakes. Almost half of participants (44.4%) were correctly classified within tertiles of consumption, whereas 12.9% were misclassified in the opposite tertile. Performance of the FFQ was relatively similar after stratification by sex. The French MetaCardis FFQ was found to have an acceptable level

  15. Diesel engine exhaust and lung cancer risks - evaluation of the meta-analysis by Vermeulen et al. 2014.

    Science.gov (United States)

    Morfeld, Peter; Spallek, Michael

    2015-01-01

    Vermeulen et al. 2014 published a meta-regression analysis of three relevant epidemiological US studies (Steenland et al. 1998, Garshick et al. 2012, Silverman et al. 2012) that estimated the association between occupational diesel engine exhaust (DEE) exposure and lung cancer mortality. The DEE exposure was measured as cumulative exposure to estimated respirable elemental carbon in μg/m(3)-years. Vermeulen et al. 2014 found a statistically significant dose-response association and described elevated lung cancer risks even at very low exposures. We performed an extended re-analysis using different modelling approaches (fixed and random effects regression analyses, Greenland/Longnecker method) and explored the impact of varying input data (modified coefficients of Garshick et al. 2012, results from Crump et al. 2015 replacing Silverman et al. 2012, modified analysis of Moehner et al. 2013). We reproduced the individual and main meta-analytical results of Vermeulen et al. 2014. However, our analysis demonstrated a heterogeneity of the baseline relative risk levels between the three studies. This heterogeneity was reduced after the coefficients of Garshick et al. 2012 were modified while the dose coefficient dropped by an order of magnitude for this study and was far from being significant (P = 0.6). A (non-significant) threshold estimate for the cumulative DEE exposure was found at 150 μg/m(3)-years when extending the meta-analyses of the three studies by hockey-stick regression modelling (including the modified coefficients for Garshick et al. 2012). The data used by Vermeulen and colleagues led to the highest relative risk estimate across all sensitivity analyses performed. The lowest relative risk estimate was found after exclusion of the explorative study by Steenland et al. 1998 in a meta-regression analysis of Garshick et al. 2012 (modified), Silverman et al. 2012 (modified according to Crump et al. 2015) and Möhner et al. 2013. The meta-coefficient was

  16. Estimation of rate constants of PCB dechlorination reactions using an anaerobic dehalogenation model.

    Science.gov (United States)

    Karakas, Filiz; Imamoglu, Ipek

    2017-02-15

    This study aims to estimate anaerobic dechlorination rate constants (k m ) of reactions of individual PCB congeners using data from four laboratory microcosms set up using sediment from Baltimore Harbor. Pathway k m values are estimated by modifying a previously developed model as Anaerobic Dehalogenation Model (ADM) which can be applied to any halogenated hydrophobic organic (HOC). Improvements such as handling multiple dechlorination activities (DAs) and co-elution of congeners, incorporating constraints, using new goodness of fit evaluation led to an increase in accuracy, speed and flexibility of ADM. DAs published in the literature in terms of chlorine substitutions as well as specific microorganisms and their combinations are used for identification of pathways. The best fit explaining the congener pattern changes was found for pathways of Phylotype DEH10, which has the ability to remove doubly flanked chlorines in meta and para positions, para flanked chlorines in meta position. The range of estimated k m values is between 0.0001-0.133d -1 , the median of which is found to be comparable to the few available published biologically confirmed rate constants. Compound specific modelling studies such as that performed by ADM can enable monitoring and prediction of concentration changes as well as toxicity during bioremediation. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Interval estimation of the overall treatment effect in a meta-analysis of a few small studies with zero events

    NARCIS (Netherlands)

    Pateras, Konstantinos; Nikolakopoulos, Stavros; Mavridis, Dimitris; Roes, Kit C.B.

    2018-01-01

    When a meta-analysis consists of a few small trials that report zero events, accounting for heterogeneity in the (interval) estimation of the overall effect is challenging. Typically, we predefine meta-analytical methods to be employed. In practice, data poses restrictions that lead to deviations

  18. bspmma: An R Package for Bayesian Semiparametric Models for Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Deborah Burr

    2012-07-01

    Full Text Available We introduce an R package, bspmma, which implements a Dirichlet-based random effects model specific to meta-analysis. In meta-analysis, when combining effect estimates from several heterogeneous studies, it is common to use a random-effects model. The usual frequentist or Bayesian models specify a normal distribution for the true effects. However, in many situations, the effect distribution is not normal, e.g., it can have thick tails, be skewed, or be multi-modal. A Bayesian nonparametric model based on mixtures of Dirichlet process priors has been proposed in the literature, for the purpose of accommodating the non-normality. We review this model and then describe a competitor, a semiparametric version which has the feature that it allows for a well-defined centrality parameter convenient for determining whether the overall effect is significant. This second Bayesian model is based on a different version of the Dirichlet process prior, and we call it the "conditional Dirichlet model". The package contains functions to carry out analyses based on either the ordinary or the conditional Dirichlet model, functions for calculating certain Bayes factors that provide a check on the appropriateness of the conditional Dirichlet model, and functions that enable an empirical Bayes selection of the precision parameter of the Dirichlet process. We illustrate the use of the package on two examples, and give an interpretation of the results in these two different scenarios.

  19. Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

    Science.gov (United States)

    Ise, Takeshi; Litton, Creighton M.; Giardina, Christian P.; Ito, Akihiko

    2010-12-01

    Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long-lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning to leaves, stems, and roots varies consistently with GPP and that the ratio of net primary production (NPP) to GPP is conservative across environmental gradients. To examine influences of carbon partitioning schemes employed by global ecosystem models, we used this meta-analysis-based model and a satellite-based (MODIS) terrestrial GPP data set to estimate global woody NPP and equilibrium biomass, and then compared it to two process-based ecosystem models (Biome-BGC and VISIT) using the same GPP data set. We hypothesized that different carbon partitioning schemes would result in large differences in global estimates of woody NPP and equilibrium biomass. Woody NPP estimated by Biome-BGC and VISIT was 25% and 29% higher than the meta-analysis-based model for boreal forests, with smaller differences in temperate and tropics. Global equilibrium woody biomass, calculated from model-specific NPP estimates and a single set of tissue turnover rates, was 48 and 226 Pg C higher for Biome-BGC and VISIT compared to the meta-analysis-based model, reflecting differences in carbon partitioning to structural versus metabolically active tissues. In summary, we found that different carbon partitioning schemes resulted in large variations in estimates of global woody carbon flux and storage, indicating that stand-level controls on carbon partitioning are not yet accurately represented in ecosystem models.

  20. Women's meta-perceptions of attractiveness and their relations to body image.

    Science.gov (United States)

    Dijkstra, Pieternel; Barelds, Dick P H

    2011-01-01

    The present study examined meta-perceptions of attractiveness among women. More specifically, ratings were collected about how women thought their partner, family and friends, and strangers would view their physical attractiveness. In an online survey, 1287 Dutch women (aged 19-80 years) answered questions concerning meta-perceptions of attractiveness, demographic data, body mass index (BMI), body image (Body Areas Satisfaction Scale, self-rated general physical attractiveness, and actual-ideal weight discrepancy), and self-esteem. Results showed that women's meta-perceptions of attractiveness reflected the level of closeness of the relationship with the other person, with the most positive meta-perceptions reported for the partner, followed by those for family and friends, and the least positive meta-perceptions for strangers. Meta-perceptions were strongly related to body image, self-esteem and BMI. Self-ratings of attractiveness appeared to be lower than all meta-perceptions of attractiveness, suggesting that women are aware of their own negative self-bias and/or other people's positive bias. Copyright © 2010 Elsevier Ltd. All rights reserved.

  1. Multivariate meta-analysis: Potential and promise

    Science.gov (United States)

    Jackson, Dan; Riley, Richard; White, Ian R

    2011-01-01

    The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

  2. MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heuristics

    Directory of Open Access Journals (Sweden)

    Milinkovitch Michel C

    2010-07-01

    Full Text Available Abstract Background The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Results Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood, including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. Conclusions The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these

  3. Meta-analysis of Gaussian individual patient data: Two-stage or not two-stage?

    Science.gov (United States)

    Morris, Tim P; Fisher, David J; Kenward, Michael G; Carpenter, James R

    2018-04-30

    Quantitative evidence synthesis through meta-analysis is central to evidence-based medicine. For well-documented reasons, the meta-analysis of individual patient data is held in higher regard than aggregate data. With access to individual patient data, the analysis is not restricted to a "two-stage" approach (combining estimates and standard errors) but can estimate parameters of interest by fitting a single model to all of the data, a so-called "one-stage" analysis. There has been debate about the merits of one- and two-stage analysis. Arguments for one-stage analysis have typically noted that a wider range of models can be fitted and overall estimates may be more precise. The two-stage side has emphasised that the models that can be fitted in two stages are sufficient to answer the relevant questions, with less scope for mistakes because there are fewer modelling choices to be made in the two-stage approach. For Gaussian data, we consider the statistical arguments for flexibility and precision in small-sample settings. Regarding flexibility, several of the models that can be fitted only in one stage may not be of serious interest to most meta-analysis practitioners. Regarding precision, we consider fixed- and random-effects meta-analysis and see that, for a model making certain assumptions, the number of stages used to fit this model is irrelevant; the precision will be approximately equal. Meta-analysts should choose modelling assumptions carefully. Sometimes relevant models can only be fitted in one stage. Otherwise, meta-analysts are free to use whichever procedure is most convenient to fit the identified model. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

  4. Cross-property relations and permeability estimation in model porous media

    International Nuclear Information System (INIS)

    Schwartz, L.M.; Martys, N.; Bentz, D.P.; Garboczi, E.J.; Torquato, S.

    1993-01-01

    Results from a numerical study examining cross-property relations linking fluid permeability to diffusive and electrical properties are presented. Numerical solutions of the Stokes equations in three-dimensional consolidated granular packings are employed to provide a basis of comparison between different permeability estimates. Estimates based on the Λ parameter (a length derived from electrical conduction) and on d c (a length derived from immiscible displacement) are found to be considerably more reliable than estimates based on rigorous permeability bounds related to pore space diffusion. We propose two hybrid relations based on diffusion which provide more accurate estimates than either of the rigorous permeability bounds

  5. A systematic review and meta-analysis of the proportion of dogs surrendered for dog-related and owner-related reasons.

    Science.gov (United States)

    Lambert, Kim; Coe, Jason; Niel, Lee; Dewey, Cate; Sargeant, Jan M

    2015-01-01

    Companion-animal relinquishment is a worldwide phenomenon that leaves companion animals homeless. Knowing why humans make the decision to end their relationship with a companion-animal can help in our understanding of this complex societal issue and can help to develop preventive strategies. A systematic review and meta-analysis was conducted to summarize reasons why dogs are surrendered, and determine if certain study characteristics were associated with the reported proportions of reasons for surrender. Articles investigating one or more reasons for dog surrender were selected from the references of a published scoping review. Two reviewers assessed the titles and abstracts of these articles, identifying 39 relevant articles. From these, 21 articles were further excluded because of ineligible study design, insufficient data available for calculating a proportion, or no data available for dogs. Data were extracted from 18 articles and meta-analysis was conducted on articles investigating reasons for dog surrender to a shelter (n=9) or dog surrender for euthanasia (n=5). Three studies were excluded from meta-analysis because they were duplicate populations. Other reasons for excluding studies from meta-analysis were, (1) the study only investigated reasons for dog re-relinquishment (n=2) and (2) the study sample size was dog surrender to a shelter and dog surrender for euthanasia. Results of meta-analysis found owner health/illness as a reason for dog surrender to a shelter had an overall estimate of 4.6% (95% CI: 4.1%, 5.2%). For all other identified reasons for surrender there was significant variation in methodology among studies preventing further meta-analysis. Univariable meta-regression was conducted to explore sources of variation among these studies. Country was identified as a significant source of variation (pdog surrender for euthanasia. The overall estimate for studies from Australia was 10% (95% CI: 8.0%, 12.0%; I(2)=15.5%), compared to 16% (95% CI

  6. Estimating chronic hepatitis C prognosis using transient elastography-based liver stiffness: A systematic review and meta-analysis.

    Science.gov (United States)

    Erman, A; Sathya, A; Nam, A; Bielecki, J M; Feld, J J; Thein, H-H; Wong, W W L; Grootendorst, P; Krahn, M D

    2018-05-01

    Chronic hepatitis C (CHC) is a leading cause of hepatic fibrosis and cirrhosis. The level of fibrosis is traditionally established by histology, and prognosis is estimated using fibrosis progression rates (FPRs; annual probability of progressing across histological stages). However, newer noninvasive alternatives are quickly replacing biopsy. One alternative, transient elastography (TE), quantifies fibrosis by measuring liver stiffness (LSM). Given these developments, the purpose of this study was (i) to estimate prognosis in treatment-naïve CHC patients using TE-based liver stiffness progression rates (LSPR) as an alternative to FPRs and (ii) to compare consistency between LSPRs and FPRs. A systematic literature search was performed using multiple databases (January 1990 to February 2016). LSPRs were calculated using either a direct method (given the difference in serial LSMs and time elapsed) or an indirect method given a single LSM and the estimated duration of infection and pooled using random-effects meta-analyses. For validation purposes, FPRs were also estimated. Heterogeneity was explored by random-effects meta-regression. Twenty-seven studies reporting on 39 groups of patients (N = 5874) were identified with 35 groups allowing for indirect and 8 for direct estimation of LSPR. The majority (~58%) of patients were HIV/HCV-coinfected. The estimated time-to-cirrhosis based on TE vs biopsy was 39 and 38 years, respectively. In univariate meta-regressions, male sex and HIV were positively and age at assessment, negatively associated with LSPRs. Noninvasive prognosis of HCV is consistent with FPRs in predicting time-to-cirrhosis, but more longitudinal studies of liver stiffness are needed to obtain refined estimates. © 2017 John Wiley & Sons Ltd.

  7. The Influence of Study-Level Inference Models and Study Set Size on Coordinate-Based fMRI Meta-Analyses

    Directory of Open Access Journals (Sweden)

    Han Bossier

    2018-01-01

    Full Text Available Given the increasing amount of neuroimaging studies, there is a growing need to summarize published results. Coordinate-based meta-analyses use the locations of statistically significant local maxima with possibly the associated effect sizes to aggregate studies. In this paper, we investigate the influence of key characteristics of a coordinate-based meta-analysis on (1 the balance between false and true positives and (2 the activation reliability of the outcome from a coordinate-based meta-analysis. More particularly, we consider the influence of the chosen group level model at the study level [fixed effects, ordinary least squares (OLS, or mixed effects models], the type of coordinate-based meta-analysis [Activation Likelihood Estimation (ALE that only uses peak locations, fixed effects, and random effects meta-analysis that take into account both peak location and height] and the amount of studies included in the analysis (from 10 to 35. To do this, we apply a resampling scheme on a large dataset (N = 1,400 to create a test condition and compare this with an independent evaluation condition. The test condition corresponds to subsampling participants into studies and combine these using meta-analyses. The evaluation condition corresponds to a high-powered group analysis. We observe the best performance when using mixed effects models in individual studies combined with a random effects meta-analysis. Moreover the performance increases with the number of studies included in the meta-analysis. When peak height is not taken into consideration, we show that the popular ALE procedure is a good alternative in terms of the balance between type I and II errors. However, it requires more studies compared to other procedures in terms of activation reliability. Finally, we discuss the differences, interpretations, and limitations of our results.

  8. Meta-GWAS Accuracy and Power (MetaGAP Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies.

    Directory of Open Access Journals (Sweden)

    Ronald de Vlaming

    2017-01-01

    Full Text Available Large-scale genome-wide association results are typically obtained from a fixed-effects meta-analysis of GWAS summary statistics from multiple studies spanning different regions and/or time periods. This approach averages the estimated effects of genetic variants across studies. In case genetic effects are heterogeneous across studies, the statistical power of a GWAS and the predictive accuracy of polygenic scores are attenuated, contributing to the so-called 'missing heritability'. Here, we describe the online Meta-GWAS Accuracy and Power (MetaGAP calculator (available at www.devlaming.eu which quantifies this attenuation based on a novel multi-study framework. By means of simulation studies, we show that under a wide range of genetic architectures, the statistical power and predictive accuracy provided by this calculator are accurate. We compare the predictions from the MetaGAP calculator with actual results obtained in the GWAS literature. Specifically, we use genomic-relatedness-matrix restricted maximum likelihood to estimate the SNP heritability and cross-study genetic correlation of height, BMI, years of education, and self-rated health in three large samples. These estimates are used as input parameters for the MetaGAP calculator. Results from the calculator suggest that cross-study heterogeneity has led to attenuation of statistical power and predictive accuracy in recent large-scale GWAS efforts on these traits (e.g., for years of education, we estimate a relative loss of 51-62% in the number of genome-wide significant loci and a relative loss in polygenic score R2 of 36-38%. Hence, cross-study heterogeneity contributes to the missing heritability.

  9. Workplace harassment from the victim's perspective: a theoretical model and meta-analysis.

    Science.gov (United States)

    Bowling, Nathan A; Beehr, Terry A

    2006-09-01

    Although workplace harassment affects the lives of many employees, until recently it has been relatively ignored in the organizational psychology literature. First, the authors introduced an attribution- and reciprocity-based model that explains the link between harassment and its potential causes and consequences. The authors then conducted a meta-analysis to examine the potential antecedents and consequences of workplace harassment. As shown by the meta-analysis, both environmental and individual difference factors potentially contributed to harassment and harassment was negatively related to the well-being of both individual employees and their employing organizations. Furthermore, harassment contributed to the variance in many outcomes, even after controlling for 2 of the most commonly studied occupational stressors, role ambiguity and role conflict. (c) 2006 APA, all rights reserved

  10. Road safety effects of roundabouts: A meta-analysis.

    Science.gov (United States)

    Elvik, Rune

    2017-02-01

    This paper presents a meta-analysis of the road safety effects of converting junctions to roundabouts. 44 studies containing a total of 154 estimates of effect were included. Based on a meta-regression analysis, converting junctions to roundabouts is associated with a reduction of fatal accidents of about 65% and a reduction of injury accidents of about 40%. The mean effect on property-damage-only accidents is ambiguous. Summary estimates of effect are robust for fatal and injury accidents, but vary depending on the model of meta-analysis and the treatment of outlying data points for property-damage-only accidents. A trim-and-fill analysis suggests a weak tendency for publication bias, with modest influence on summary estimates of effect. It is concluded that roundabouts are very effective in reducing traffic fatalities. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Early Start DENVER Model: A Meta - analysis

    Directory of Open Access Journals (Sweden)

    Jane P. Canoy

    2015-11-01

    Full Text Available Each child with Autism Spectrum Disorder has different symptoms, skills and types of impairment or disorder with other children. This is why the word “spectrum” is included in this disorder. Eapen, Crncec, and Walter, 2013 claimed that there was an emerging evidence that early interventions gives the greatest capacity of child’s development during their first years of life as “brain plasticity” are high during this period. With this, the only intervention program model for children as young as 18 months that has been validated in a randomized clinical trial is “Early Start Denver Model” (ESDM. This study aimed to determine the effectiveness of the outcome of “Early Start Denver Model” (ESDM towards young children with Autism Spectrum Disorders. This study made use of meta-analysis method. In this study, the researcher utilized studies related to “Early Start Denver Model (ESDM” which is published in a refereed journal which are all available online. There were five studies included which totals 149 children exposed to ESDM. To examine the “pooled effects” of ESDM in a variety of outcomes, a meta-analytic procedure was performed after the extraction of data of the concrete outcomes. Comprehensive Meta Analysis Version 3.3.070 was used to analyze the data.  The effectiveness of the outcome of “Early Start Denver Model” towards young children with Autism Spectrum Disorders (ASD highly depends on the intensity of intervention and the younger child age. This study would provide the basis in effectively implementing an early intervention to children with autism such as the “Early Start Denver Model” (ESDM that would show great outcome effects to those children that has “Autism Spectrum Disorder”.

  12. Body mass index and risk of BPH: a meta-analysis.

    Science.gov (United States)

    Wang, S; Mao, Q; Lin, Y; Wu, J; Wang, X; Zheng, X; Xie, L

    2012-09-01

    Epidemiological studies have reported conflicting results relating obesity to BPH. A meta-analysis of cohort and case-control studies was conducted to pool the risk estimates of the association between obesity and BPH. Eligible studies were retrieved by both computer searches and review of references. We analyzed abstracted data with random effects models to obtain the summary risk estimates. Dose-response meta-analysis was performed for studies reporting categorical risk estimates for a series of exposure levels. A total of 19 studies met the inclusion criteria of the meta-analysis. Positive association with body mass index (BMI) was observed in BPH and lower urinary tract symptoms (LUTS) combined group (odds ratio=1.27, 95% confidence intervals 1.05-1.53). In subgroup analysis, BMI exhibited a positive dose-response relationship with BPH/LUTS in population-based case-control studies and a marginal positive association was observed between risk of BPH and increased BMI. However, no association between BPH/LUTS and BMI was observed in other subgroups stratified by study design, geographical region or primary outcome. The overall current literatures suggested that BMI was associated with increased risk of BPH. Further efforts should be made to confirm these findings and clarify the underlying biological mechanisms.

  13. Quantifying the dose-response relationship between circulating folate concentrations and colorectal cancer in cohort studies: a meta-analysis based on a flexible meta-regression model.

    Science.gov (United States)

    Chuang, Shu-Chun; Rota, Matteo; Gunter, Marc J; Zeleniuch-Jacquotte, Anne; Eussen, Simone J P M; Vollset, Stein Emil; Ueland, Per Magne; Norat, Teresa; Ziegler, Regina G; Vineis, Paolo

    2013-10-01

    Most epidemiologic studies on folate intake suggest that folate may be protective against colorectal cancer, but the results on circulating (plasma or serum) folate are mostly inconclusive. We conducted a meta-analysis of case-control studies nested within prospective studies on circulating folate and colorectal cancer risk by using flexible meta-regression models to test the linear and nonlinear dose-response relationships. A total of 8 publications (10 cohorts, representing 3,477 cases and 7,039 controls) were included in the meta-analysis. The linear and nonlinear models corresponded to relative risks of 0.96 (95% confidence interval (CI): 0.91, 1.02) and 0.99 (95% CI: 0.96, 1.02), respectively, per 10 nmol/L of circulating folate in contrast to the reference value. The pooled relative risks when comparing the highest with the lowest category were 0.80 (95% CI: 0.61, 0.99) for radioimmunoassay and 1.03 (95% CI: 0.83, 1.22) for microbiological assay. Overall, our analyses suggest a null association between circulating folate and colorectal cancer risk. The stronger association for the radioimmunoassay-based studies could reflect differences in cohorts and study designs rather than assay performance. Further investigations need to integrate more accurate measurements and flexible modeling to explore the effects of folate in the presence of genetic, lifestyle, dietary, and hormone-related factors.

  14. Effectiveness of meta-models for multi-objective optimization of centrifugal impeller

    Energy Technology Data Exchange (ETDEWEB)

    Bellary, Sayed Ahmed Imran; Samad, Abdus [Indian Institute of Technology Madras, Chennai (India); Husain, Afzal [Sultan Qaboos University, Al-Khoudh (Oman)

    2014-12-15

    The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.

  15. Effectiveness of meta-models for multi-objective optimization of centrifugal impeller

    International Nuclear Information System (INIS)

    Bellary, Sayed Ahmed Imran; Samad, Abdus; Husain, Afzal

    2014-01-01

    The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.

  16. Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

    2018-03-01

    Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

  17. Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

    2017-01-01

    Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

  18. Altered sensorimotor activation patterns in idiopathic dystonia-an activation likelihood estimation meta-analysis of functional brain imaging studies

    DEFF Research Database (Denmark)

    Løkkegaard, Annemette; Herz, Damian M; Haagensen, Brian Numelin

    2016-01-01

    Dystonia is characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements or postures. Functional neuroimaging studies have yielded abnormal task-related sensorimotor activation in dystonia, but the results appear to be rather variable across studies....... Further, study size was usually small including different types of dystonia. Here we performed an activation likelihood estimation (ALE) meta-analysis of functional neuroimaging studies in patients with primary dystonia to test for convergence of dystonia-related alterations in task-related activity...... postcentral gyrus, right superior temporal gyrus and dorsal midbrain. Apart from the midbrain cluster, all between-group differences in task-related activity were retrieved in a sub-analysis including only the 14 studies on patients with focal dystonia. For focal dystonia, an additional cluster of increased...

  19. Age and work-related motives : Results of a meta-analysis

    NARCIS (Netherlands)

    Kooij, Dorien T. A. M.; De Lange, Annet H.; Jansen, Paul G. W.; Kanfer, Ruth; Dikkers, Josje S. E.

    An updated literature review was conducted and a meta-analysis was performed to investigate the relationship between age and work-related motives. Building on theorizing in life span psychology, we hypothesized the existence of age-related differences in work-related motives. Specifically, we

  20. Age and work-related motives: Results of a meta-analysis

    NARCIS (Netherlands)

    Kooij, D.T.A.M.; Lange, A.H. de; Jansen, P.G.W.; Kanfer, R.; Dikkers, J.S.E.

    2011-01-01

    An updated literature review was conducted and a meta-analysis was performed to investigate the relationship between age and work-related motives. Building on theorizing in life span psychology, we hypothesized the existence of age-related differences in work-related motives. Specifically, we

  1. Voxelwise meta-ananlysis of gray matter anomalies in progressive supranuclear palsy and Parkinson’s disease using anatomic likelihood estimation

    Directory of Open Access Journals (Sweden)

    Huifang eShang

    2014-02-01

    Full Text Available Numerous voxel-based morphometry (VBM studies on gray matter (GM of patients with progressive supranuclear palsy (PSP and Parkinson’s disease (PD have been conducted separately. Identifying the different neuroanatomical changes in GM resulting from PSP and PD through meta-analysis will aid the differential diagnosis of PSP and PD. In this study, a systematic review of VBM studies of patients with PSP and PD relative to healthy controls (HC in the Embase and PubMed databases from January 1995 to April 2013 was conducted. The anatomical distribution of the coordinates of GM differences was meta-analyzed using anatomical likelihood estimation. Separate maps of GM changes were constructed and subtraction meta-analysis was performed to explore the differences in GM abnormalities between PSP and PD. Nine PSP studies and 24 PD studies were included. GM reductions were present in the bilateral thalamus, basal ganglia, midbrain, insular cortex and inferior frontal gyrus, and left precentral gyrus and anterior cingulate gyrus in PSP. Atrophy of GM was concentrated in the bilateral middle and inferior frontal gyrus, precuneus, left precentral gyrus, middle temporal gyrus, right superior parietal lobule, and right cuneus in PD. Subtraction meta-analysis indicated that GM volume was lesser in the bilateral midbrain, thalamus, and insula in PSP compared with that in PD. Our meta-analysis indicated that PSP and PD shared a similar distribution of neuroanatomical changes in the frontal lobe, including inferior frontal gyrus and precentral gyrus, and that atrophy of the midbrain, thalamus, and insula are neuroanatomical markers for differentiating PSP from PD.

  2. Accounting for Heterogeneity in Relative Treatment Effects for Use in Cost-Effectiveness Models and Value-of-Information Analyses.

    Science.gov (United States)

    Welton, Nicky J; Soares, Marta O; Palmer, Stephen; Ades, Anthony E; Harrison, David; Shankar-Hari, Manu; Rowan, Kathy M

    2015-07-01

    Cost-effectiveness analysis (CEA) models are routinely used to inform health care policy. Key model inputs include relative effectiveness of competing treatments, typically informed by meta-analysis. Heterogeneity is ubiquitous in meta-analysis, and random effects models are usually used when there is variability in effects across studies. In the absence of observed treatment effect modifiers, various summaries from the random effects distribution (random effects mean, predictive distribution, random effects distribution, or study-specific estimate [shrunken or independent of other studies]) can be used depending on the relationship between the setting for the decision (population characteristics, treatment definitions, and other contextual factors) and the included studies. If covariates have been measured that could potentially explain the heterogeneity, then these can be included in a meta-regression model. We describe how covariates can be included in a network meta-analysis model and how the output from such an analysis can be used in a CEA model. We outline a model selection procedure to help choose between competing models and stress the importance of clinical input. We illustrate the approach with a health technology assessment of intravenous immunoglobulin for the management of adult patients with severe sepsis in an intensive care setting, which exemplifies how risk of bias information can be incorporated into CEA models. We show that the results of the CEA and value-of-information analyses are sensitive to the model and highlight the importance of sensitivity analyses when conducting CEA in the presence of heterogeneity. The methods presented extend naturally to heterogeneity in other model inputs, such as baseline risk. © The Author(s) 2015.

  3. Model-Assisted Control of Flow Front in Resin Transfer Molding Based on Real-Time Estimation of Permeability/Porosity Ratio

    Directory of Open Access Journals (Sweden)

    Bai-Jian Wei

    2016-09-01

    Full Text Available Resin transfer molding (RTM is a popular manufacturing technique that produces fiber reinforced polymer (FRP composites. In this paper, a model-assisted flow front control system is developed based on real-time estimation of permeability/porosity ratio using the information acquired by a visualization system. In the proposed control system, a radial basis function (RBF network meta-model is utilized to predict the position of the future flow front by inputting the injection pressure, the current position of flow front, and the estimated ratio. By conducting optimization based on the meta-model, the value of injection pressure to be implemented at each step is obtained. Moreover, a cascade control structure is established to further improve the control performance. Experiments show that the developed system successfully enhances the performance of flow front control in RTM. Especially, the cascade structure makes the control system robust to model mismatch.

  4. Forecasting urban water demand: A meta-regression analysis.

    Science.gov (United States)

    Sebri, Maamar

    2016-12-01

    Water managers and planners require accurate water demand forecasts over the short-, medium- and long-term for many purposes. These range from assessing water supply needs over spatial and temporal patterns to optimizing future investments and planning future allocations across competing sectors. This study surveys the empirical literature on the urban water demand forecasting using the meta-analytical approach. Specifically, using more than 600 estimates, a meta-regression analysis is conducted to identify explanations of cross-studies variation in accuracy of urban water demand forecasting. Our study finds that accuracy depends significantly on study characteristics, including demand periodicity, modeling method, forecasting horizon, model specification and sample size. The meta-regression results remain robust to different estimators employed as well as to a series of sensitivity checks performed. The importance of these findings lies in the conclusions and implications drawn out for regulators and policymakers and for academics alike. Copyright © 2016. Published by Elsevier Ltd.

  5. Property preservation and quality measures in meta-models

    NARCIS (Netherlands)

    Siem, A.Y.D.

    2008-01-01

    This thesis consists of three parts. Each part considers different sorts of meta-models. In the first part so-called Sandwich models are considered. In the second part Kriging models are considered. Finally, in the third part, (trigonometric) Polynomials and Rational models are studied.

  6. In search of a corrected prescription drug elasticity estimate: a meta-regression approach.

    Science.gov (United States)

    Gemmill, Marin C; Costa-Font, Joan; McGuire, Alistair

    2007-06-01

    An understanding of the relationship between cost sharing and drug consumption depends on consistent and unbiased price elasticity estimates. However, there is wide heterogeneity among studies, which constrains the applicability of elasticity estimates for empirical purposes and policy simulation. This paper attempts to provide a corrected measure of the drug price elasticity by employing meta-regression analysis (MRA). The results indicate that the elasticity estimates are significantly different from zero, and the corrected elasticity is -0.209 when the results are made robust to heteroskedasticity and clustering of observations. Elasticity values are higher when the study was published in an economic journal, when the study employed a greater number of observations, and when the study used aggregate data. Elasticity estimates are lower when the institutional setting was a tax-based health insurance system.

  7. Ego Depletion and the Strength Model of Self-Control: A Meta-Analysis

    Science.gov (United States)

    Hagger, Martin S.; Wood, Chantelle; Stiff, Chris; Chatzisarantis, Nikos L. D.

    2010-01-01

    According to the strength model, self-control is a finite resource that determines capacity for effortful control over dominant responses and, once expended, leads to impaired self-control task performance, known as "ego depletion". A meta-analysis of 83 studies tested the effect of ego depletion on task performance and related outcomes,…

  8. The "Emotional Side" of Entrepreneurship: A Meta-Analysis of the Relation between Positive and Negative Affect and Entrepreneurial Performance.

    Science.gov (United States)

    Fodor, Oana C; Pintea, Sebastian

    2017-01-01

    The experience of work in an entrepreneurial context is saturated with emotional experiences. While the literature on the relation between affect and entrepreneurial performance (EP) is growing, there was no quantitative integration of the results so far. This study addresses this gap and meta-analytically integrates the results from 17 studies ( N = 3810) in order to estimate the effect size for the relation between positive (PA) and negative affect (NA), on the one hand, and EP, on the other hand. The meta-analysis includes studies in English language, published until August 2016. The results indicate a significant positive relation between PA and EP, r = 0.18. The overall NA - EP relation was not significant, r = -0.12. Only state NA has a significant negative relation with EP ( r = -0.16). The moderating role of several conceptual (i.e., emotion duration, integrality etc.), sample (i.e., gender, age, education) and methodological characteristics of the studies (i.e., type of measurements etc.) are explored and implications for future research are discussed.

  9. Meta-connectomics: human brain network and connectivity meta-analyses.

    Science.gov (United States)

    Crossley, N A; Fox, P T; Bullmore, E T

    2016-04-01

    Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

  10. The link between employee attitudes and employee effectiveness: Data matrix of meta-analytic estimates based on 1161 unique correlations

    Directory of Open Access Journals (Sweden)

    Michael M. Mackay

    2016-09-01

    Full Text Available This article offers a correlation matrix of meta-analytic estimates between various employee job attitudes (i.e., Employee engagement, job satisfaction, job involvement, and organizational commitment and indicators of employee effectiveness (i.e., Focal performance, contextual performance, turnover intention, and absenteeism. The meta-analytic correlations in the matrix are based on over 1100 individual studies representing over 340,000 employees. Data was collected worldwide via employee self-report surveys. Structural path analyses based on the matrix, and the interpretation of the data, can be found in “Investigating the incremental validity of employee engagement in the prediction of employee effectiveness: a meta-analytic path analysis” (Mackay et al., 2016 [1]. Keywords: Meta-analysis, Job attitudes, Job performance, Employee, Engagement, Employee effectiveness

  11. The Magnitude of Mortality from Ischemic Heart Disease Attributed to Occupational Factors in Korea - Attributable Fraction Estimation Using Meta-analysis.

    Science.gov (United States)

    Ha, Jaehyeok; Kim, Soo-Geun; Paek, Domyung; Park, Jungsun

    2011-03-01

    Ischemic heart disease (IHD) is a major cause of death in Korea and known to result from several occupational factors. This study attempted to estimate the current magnitude of IHD mortality due to occupational factors in Korea. After selecting occupational risk factors by literature investigation, we calculated attributable fractions (AFs) from relative risks and exposure data for each factor. Relative risks were estimated using meta-analysis based on published research. Exposure data were collected from the 2006 Survey of Korean Working Conditions. Finally, we estimated 2006 occupation-related IHD mortality. FOR THE FACTORS CONSIDERED, WE ESTIMATED THE FOLLOWING RELATIVE RISKS: noise 1.06, environmental tobacco smoke 1.19 (men) and 1.22 (women), shift work 1.12, and low job control 1.15 (men) and 1.08 (women). Combined AFs of those factors in the IHD were estimated at 9.29% (0.3-18.51%) in men and 5.78% (-7.05-19.15%) in women. Based on these fractions, Korea's 2006 death toll from occupational IHD between the age of 15 and 69 was calculated at 353 in men (total 3,804) and 72 in women (total 1,246). We estimated occupational IHD mortality of Korea with updated data and more relevant evidence. Despite the efforts to obtain reliable estimates, there were many assumptions and limitations that must be overcome. Future research based on more precise design and reliable evidence is required for more accurate estimates.

  12. Work-related critical incidents in hospital-based health care providers and the risk of post-traumatic stress symptoms, anxiety, and depression: a meta-analysis.

    Science.gov (United States)

    de Boer, Jacoba; Lok, Anja; Van't Verlaat, Ellen; Duivenvoorden, Hugo J; Bakker, Arnold B; Smit, Bert J

    2011-07-01

    This meta-analysis reviewed existing data on the impact of work-related critical incidents in hospital-based health care professionals. Work-related critical incidents may induce post-traumatic stress symptoms or even post-traumatic stress disorder (PTSD), anxiety, and depression and may negatively affect health care practitioners' behaviors toward patients. Nurses and doctors often cope by working part time or switching jobs. Hospital administrators and health care practitioners themselves may underestimate the effects of work-related critical incidents. Relevant online databases were searched for original research published from inception to 2009 and manual searches of the Journal of Traumatic Stress, reference lists, and the European Traumatic Stress Research Database were conducted. Two researchers independently decided on inclusion and study quality. Effect sizes were estimated using standardized mean differences with 95% confidence intervals. Consistency was evaluated, using the I(2)-statistic. Meta-analysis was performed using the random effects model. Eleven studies, which included 3866 participants, evaluated the relationship between work-related critical incidents and post-traumatic stress symptoms. Six of these studies, which included 1695 participants, also reported on the relationship between work-related critical incidents and symptoms of anxiety and depression. Heterogeneity among studies was high and could not be accounted for by study quality, character of the incident, or timing of data collection. Pooled effect sizes for the impact of work-related critical incidents on post-traumatic stress symptoms, anxiety, and depression were small to medium. Remarkably, the effect was more pronounced in the longer than in the shorter term. In conclusion, this meta-analysis supports the hypothesis that work-related critical incidents are positively related to post-traumatic stress symptoms, anxiety, and depression in hospital-based health care professionals

  13. A knowledge representation meta-model for rule-based modelling of signalling networks

    Directory of Open Access Journals (Sweden)

    Adrien Basso-Blandin

    2016-03-01

    Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

  14. Child-Centered Play Therapy in the Schools: Review and Meta-Analysis

    Science.gov (United States)

    Ray, Dee C.; Armstrong, Stephen A.; Balkin, Richard S.; Jayne, Kimberly M.

    2015-01-01

    The authors conducted a meta-analysis and systematic review that examined 23 studies evaluating the effectiveness of child centered play therapy (CCPT) conducted in elementary schools. Meta-analysis results were explored using a random effects model for mean difference and mean gain effect size estimates. Results revealed statistically significant…

  15. AMFIBIA: A Meta-Model for the Integration of Business Process Modelling Aspects

    DEFF Research Database (Denmark)

    Axenath, Björn; Kindler, Ekkart; Rubin, Vladimir

    2007-01-01

    AMFIBIA is a meta-model that formalises the essential aspects and concepts of business processes. Though AMFIBIA is not the first approach to formalising the aspects and concepts of business processes, it is more ambitious in the following respects: Firstly, it is independent from particular...... modelling formalisms of business processes and it is designed in such a way that any formalism for modelling some aspect of a business process can be plugged into AMFIBIA. Therefore, AMFIBIA is formalism-independent. Secondly, it is not biased toward any aspect of business processes; the different aspects...... can be considered and modelled independently of each other. Moreover, AMFIBIA is not restricted to a fixed set of aspects; new aspects of business processes can be easily integrated. Thirdly, AMFIBIA does not only name and relate the concepts of business process modelling, as it is typically done...

  16. A meta-analysis on the price elasticity of energy demand

    International Nuclear Information System (INIS)

    Labandeira, Xavier; Labeaga, José M.; López-Otero, Xiral

    2017-01-01

    Price elasticities of energy demand have become increasingly relevant in estimating the socio-economic and environmental effects of energy policies or other events that influence the price of energy goods. Since the 1970s, a large number of academic papers have provided both short and long-term price elasticity estimates for different countries using several models, data and estimation techniques. Yet the literature offers a rather wide range of estimates for the price elasticities of demand for energy. This paper quantitatively summarizes the recent, but sizeable, empirical evidence to facilitate a sounder economic assessment of (in some cases policy-related) energy price changes. It uses meta-analysis to identify the main factors affecting short and long term elasticity results for energy, in general, as well as for specific products, i.e., electricity, natural gas, gasoline, diesel and heating oil. - Highlights: • An updated and wider meta-analysis on price elasticities of energy demand. • Energy goods are shown to be price inelastic both in the short and long-term. • Results are relevant for a proper design and implementation of energy policies. • Our results refer to energy, as a whole, and specific energy goods.

  17. Factoring vs linear modeling in rate estimation: a simulation study of relative accuracy.

    Science.gov (United States)

    Maldonado, G; Greenland, S

    1998-07-01

    A common strategy for modeling dose-response in epidemiology is to transform ordered exposures and covariates into sets of dichotomous indicator variables (that is, to factor the variables). Factoring tends to increase estimation variance, but it also tends to decrease bias and thus may increase or decrease total accuracy. We conducted a simulation study to examine the impact of factoring on the accuracy of rate estimation. Factored and unfactored Poisson regression models were fit to follow-up study datasets that were randomly generated from 37,500 population model forms that ranged from subadditive to supramultiplicative. In the situations we examined, factoring sometimes substantially improved accuracy relative to fitting the corresponding unfactored model, sometimes substantially decreased accuracy, and sometimes made little difference. The difference in accuracy between factored and unfactored models depended in a complicated fashion on the difference between the true and fitted model forms, the strength of exposure and covariate effects in the population, and the study size. It may be difficult in practice to predict when factoring is increasing or decreasing accuracy. We recommend, therefore, that the strategy of factoring variables be supplemented with other strategies for modeling dose-response.

  18. Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

    Science.gov (United States)

    Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P

    2014-06-26

    To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.

  19. A Meta-Analysis of the Relation between Creative Self-Efficacy and Different Creativity Measurements

    Science.gov (United States)

    Haase, Jennifer; Hoff, Eva V.; Hanel, Paul H. P.; Innes-Ker, Åse

    2018-01-01

    This meta-analysis investigated the relations between creative self-efficacy (CSE) and creativity measures and hypothesized that self-assessed questionnaires would have a different relation to self-efficacy beliefs compared to other creativity tests. The meta-analysis synthesized 60 effect sizes from 41 papers (overall N = 17226). Taken as a…

  20. Using meta-analytic path analysis to test theoretical predictions in health behavior: An illustration based on meta-analyses of the theory of planned behavior.

    Science.gov (United States)

    Hagger, Martin S; Chan, Derwin K C; Protogerou, Cleo; Chatzisarantis, Nikos L D

    2016-08-01

    Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs from social cognitive theories is important to test nomological validity, account for mediation effects, and evaluate unique effects of theory constructs independent of past behavior. We illustrate our points by conducting new analyses of two meta-analyses of a popular theory applied to health behaviors, the theory of planned behavior. We conducted meta-analytic path analyses of the theory in two behavioral contexts (alcohol and dietary behaviors) using data from the primary studies included in the original meta-analyses augmented to include intercorrelations among constructs and relations with past behavior missing from the original analysis. Findings supported the nomological validity of the theory and its hypotheses for both behaviors, confirmed important model processes through mediation analysis, demonstrated the attenuating effect of past behavior on theory relations, and provided estimates of the unique effects of theory constructs independent of past behavior. Our analysis illustrates the importance of conducting a simultaneous test of theory-stipulated effects in meta-analyses of social cognitive theories applied to health behavior. We recommend researchers adopt this analytic procedure when synthesizing evidence across primary tests of social cognitive theories in health. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Effectiveness of Social Media-based Interventions on Weight-related Behaviors and Body Weight Status: Review and Meta-analysis.

    Science.gov (United States)

    An, Ruopeng; Ji, Mengmeng; Zhang, Sheng

    2017-11-01

    We reviewed scientific literature regarding the effectiveness of social media-based interventions about weight-related behaviors and body weight status. A keyword search were performed in May 2017 in the Clinical-Trials.gov, Cochrane Library, PsycINFO, PubMed, and Web of Science databases. We conducted a meta-analysis to estimate the pooled effect size of social media-based interventions on weight-related outcome measures. We identified 22 interventions from the keyword and reference search, including 12 randomized controlled trials, 6 pre-post studies and 3 cohort studies conducted in 9 countries during 2010-2016. The majority (N = 17) used Facebook, followed by Twitter (N = 4) and Instagram (N = 1). Intervention durations averaged 17.8 weeks with a mean sample size of 69. The meta-analysis showed that social media-based interventions were associated with a statistically significant, but clinically modest reduction of body weight by 1.01 kg, body mass index by 0.92 kg/m2, and waist circumstance by 2.65 cm, and an increase of daily number of steps taken by 1530. In the meta-regression there was no doseresponse effect with respect to intervention duration. The boom of social media provides an unprecedented opportunity to implement health promotion programs. Future interventions should make efforts to improve intervention scalability and effectiveness.

  2. Relative risk estimation of Chikungunya disease in Malaysia: An analysis based on Poisson-gamma model

    Science.gov (United States)

    Samat, N. A.; Ma'arof, S. H. Mohd Imam

    2015-05-01

    Disease mapping is a method to display the geographical distribution of disease occurrence, which generally involves the usage and interpretation of a map to show the incidence of certain diseases. Relative risk (RR) estimation is one of the most important issues in disease mapping. This paper begins by providing a brief overview of Chikungunya disease. This is followed by a review of the classical model used in disease mapping, based on the standardized morbidity ratio (SMR), which we then apply to our Chikungunya data. We then fit an extension of the classical model, which we refer to as a Poisson-Gamma model, when prior distributions for the relative risks are assumed known. Both results are displayed and compared using maps and we reveal a smoother map with fewer extremes values of estimated relative risk. The extensions of this paper will consider other methods that are relevant to overcome the drawbacks of the existing methods, in order to inform and direct government strategy for monitoring and controlling Chikungunya disease.

  3. Event-related fMRI studies of false memory: An Activation Likelihood Estimation meta-analysis.

    Science.gov (United States)

    Kurkela, Kyle A; Dennis, Nancy A

    2016-01-29

    Over the last two decades, a wealth of research in the domain of episodic memory has focused on understanding the neural correlates mediating false memories, or memories for events that never happened. While several recent qualitative reviews have attempted to synthesize this literature, methodological differences amongst the empirical studies and a focus on only a sub-set of the findings has limited broader conclusions regarding the neural mechanisms underlying false memories. The current study performed a voxel-wise quantitative meta-analysis using activation likelihood estimation to investigate commonalities within the functional magnetic resonance imaging (fMRI) literature studying false memory. The results were broken down by memory phase (encoding, retrieval), as well as sub-analyses looking at differences in baseline (hit, correct rejection), memoranda (verbal, semantic), and experimental paradigm (e.g., semantic relatedness and perceptual relatedness) within retrieval. Concordance maps identified significant overlap across studies for each analysis. Several regions were identified in the general false retrieval analysis as well as multiple sub-analyses, indicating their ubiquitous, yet critical role in false retrieval (medial superior frontal gyrus, left precentral gyrus, left inferior parietal cortex). Additionally, several regions showed baseline- and paradigm-specific effects (hit/perceptual relatedness: inferior and middle occipital gyrus; CRs: bilateral inferior parietal cortex, precuneus, left caudate). With respect to encoding, analyses showed common activity in the left middle temporal gyrus and anterior cingulate cortex. No analysis identified a common cluster of activation in the medial temporal lobe. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Chronic exposure to chlorophenol related compounds in the pesticide production workplace and lung cancer: a meta-analysis.

    Science.gov (United States)

    Zendehdel, Rezvan; Tayefeh-Rahimian, Raana; Kabir, Ali

    2014-01-01

    Chlorophenols (CPs) and related phenoxyacetic acids (PAs) are pesticide groups contaminated with highly toxic 2, 3, 7, 8-tetrachlorodibenzo-p-dioxin (TCDD) during production. PAs and CPs exposure is associated with risk of cancer, but the situation regarding lung cancer has not been clearly defined. We proposed a meta-analysis of published researches to evaluate relationship between chronic exposure to PAs and CPs in pesticide production workplaces and the risk of lung cancer. After searching PubMed, Scopus, Scholar Google, Web of Sciences until August 2013, the association between chronic PAs and CPs exposure in production workplace and lung cancer was studied in 15 cohort studies. The standardized mortality rate (SMR) and 95% confidence intervals (CI) were collected from the papers. We used random or fixed-effects models, Egger test, funnel plot and meta regression in our analysis. Five papers with six reports were included in the final analysis. The standardized mortality rate for lung cancer from the random model was 1.18 (95% CI: 1.03-1.35, p=0.014) with moderate heterogeneity. Publication bias was not found for included studies in meta-analysis (p=0.9). Our findings has strengthen the evidence of lung cancer from chronic exposure to chlorophenol related compounds (PAs, CPs).

  5. Sizing Up the Milky Way: A Bayesian Mixture Model Meta-analysis of Photometric Scale Length Measurements

    Science.gov (United States)

    Licquia, Timothy C.; Newman, Jeffrey A.

    2016-11-01

    The exponential scale length (L d ) of the Milky Way’s (MW’s) disk is a critical parameter for describing the global physical size of our Galaxy, important both for interpreting other Galactic measurements and helping us to understand how our Galaxy fits into extragalactic contexts. Unfortunately, current estimates span a wide range of values and are often statistically incompatible with one another. Here, we perform a Bayesian meta-analysis to determine an improved, aggregate estimate for L d , utilizing a mixture-model approach to account for the possibility that any one measurement has not properly accounted for all statistical or systematic errors. Within this machinery, we explore a variety of ways of modeling the nature of problematic measurements, and then employ a Bayesian model averaging technique to derive net posterior distributions that incorporate any model-selection uncertainty. Our meta-analysis combines 29 different (15 visible and 14 infrared) photometric measurements of L d available in the literature; these involve a broad assortment of observational data sets, MW models and assumptions, and methodologies, all tabulated herein. Analyzing the visible and infrared measurements separately yields estimates for L d of {2.71}-0.20+0.22 kpc and {2.51}-0.13+0.15 kpc, respectively, whereas considering them all combined yields 2.64 ± 0.13 kpc. The ratio between the visible and infrared scale lengths determined here is very similar to that measured in external spiral galaxies. We use these results to update the model of the Galactic disk from our previous work, constraining its stellar mass to be {4.8}-1.1+1.5× {10}10 M ⊙, and the MW’s total stellar mass to be {5.7}-1.1+1.5× {10}10 M ⊙.

  6. Meta-STEPP: subpopulation treatment effect pattern plot for individual patient data meta-analysis.

    Science.gov (United States)

    Wang, Xin Victoria; Cole, Bernard; Bonetti, Marco; Gelber, Richard D

    2016-09-20

    We have developed a method, called Meta-STEPP (subpopulation treatment effect pattern plot for meta-analysis), to explore treatment effect heterogeneity across covariate values in the meta-analysis setting for time-to-event data when the covariate of interest is continuous. Meta-STEPP forms overlapping subpopulations from individual patient data containing similar numbers of events with increasing covariate values, estimates subpopulation treatment effects using standard fixed-effects meta-analysis methodology, displays the estimated subpopulation treatment effect as a function of the covariate values, and provides a statistical test to detect possibly complex treatment-covariate interactions. Simulation studies show that this test has adequate type-I error rate recovery as well as power when reasonable window sizes are chosen. When applied to eight breast cancer trials, Meta-STEPP suggests that chemotherapy is less effective for tumors with high estrogen receptor expression compared with those with low expression. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  7. Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago.

    Science.gov (United States)

    Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E; Pellissier, Loïc

    2018-03-01

    Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns.

  8. Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago

    Science.gov (United States)

    Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E.

    2018-01-01

    Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns. PMID:29657753

  9. The “Emotional Side” of Entrepreneurship: A Meta-Analysis of the Relation between Positive and Negative Affect and Entrepreneurial Performance

    Science.gov (United States)

    Fodor, Oana C.; Pintea, Sebastian

    2017-01-01

    The experience of work in an entrepreneurial context is saturated with emotional experiences. While the literature on the relation between affect and entrepreneurial performance (EP) is growing, there was no quantitative integration of the results so far. This study addresses this gap and meta-analytically integrates the results from 17 studies (N = 3810) in order to estimate the effect size for the relation between positive (PA) and negative affect (NA), on the one hand, and EP, on the other hand. The meta-analysis includes studies in English language, published until August 2016. The results indicate a significant positive relation between PA and EP, r = 0.18. The overall NA – EP relation was not significant, r = -0.12. Only state NA has a significant negative relation with EP (r = -0.16). The moderating role of several conceptual (i.e., emotion duration, integrality etc.), sample (i.e., gender, age, education) and methodological characteristics of the studies (i.e., type of measurements etc.) are explored and implications for future research are discussed. PMID:28348534

  10. Meta-analysis, Simpson's paradox, and the number needed to treat

    Directory of Open Access Journals (Sweden)

    Deeks Jonathan J

    2002-01-01

    Full Text Available Abstract Background There is debate concerning methods for calculating numbers needed to treat (NNT from results of systematic reviews. Methods We investigate the susceptibility to bias for alternative methods for calculating NNTs through illustrative examples and mathematical theory. Results Two competing methods have been recommended: one method involves calculating the NNT from meta-analytical estimates, the other by treating the data as if it all arose from a single trial. The 'treat-as-one-trial' method was found to be susceptible to bias when there were imbalances between groups within one or more trials in the meta-analysis (Simpson's paradox. Calculation of NNTs from meta-analytical estimates is not prone to the same bias. The method of calculating the NNT from a meta-analysis depends on the treatment effect used. When relative measures of treatment effect are used the estimates of NNTs can be tailored to the level of baseline risk. Conclusions The treat-as-one-trial method of calculating numbers needed to treat should not be used as it is prone to bias. Analysts should always report the method they use to compute estimates to enable readers to judge whether it is appropriate.

  11. Robust variance estimation with dependent effect sizes: practical considerations including a software tutorial in Stata and spss.

    Science.gov (United States)

    Tanner-Smith, Emily E; Tipton, Elizabeth

    2014-03-01

    Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and spss (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding the practical application and implementation of those macros. This paper provides a brief tutorial on the implementation of the Stata and spss macros and discusses practical issues meta-analysts should consider when estimating meta-regression models with robust variance estimates. Two example databases are used in the tutorial to illustrate the use of meta-analysis with robust variance estimates. Copyright © 2013 John Wiley & Sons, Ltd.

  12. Software Cost-Estimation Model

    Science.gov (United States)

    Tausworthe, R. C.

    1985-01-01

    Software Cost Estimation Model SOFTCOST provides automated resource and schedule model for software development. Combines several cost models found in open literature into one comprehensive set of algorithms. Compensates for nearly fifty implementation factors relative to size of task, inherited baseline, organizational and system environment and difficulty of task.

  13. Using a laboratory-based growth model to estimate mass- and temperature-dependent growth parameters across populations of juvenile Chinook Salmon

    Science.gov (United States)

    Perry, Russell W.; Plumb, John M.; Huntington, Charles

    2015-01-01

    To estimate the parameters that govern mass- and temperature-dependent growth, we conducted a meta-analysis of existing growth data from juvenile Chinook Salmon Oncorhynchus tshawytscha that were fed an ad libitum ration of a pelleted diet. Although the growth of juvenile Chinook Salmon has been well studied, research has focused on a single population, a narrow range of fish sizes, or a narrow range of temperatures. Therefore, we incorporated the Ratkowsky model for temperature-dependent growth into an allometric growth model; this model was then fitted to growth data from 11 data sources representing nine populations of juvenile Chinook Salmon. The model fit the growth data well, explaining 98% of the variation in final mass. The estimated allometric mass exponent (b) was 0.338 (SE = 0.025), similar to estimates reported for other salmonids. This estimate of b will be particularly useful for estimating mass-standardized growth rates of juvenile Chinook Salmon. In addition, the lower thermal limit, optimal temperature, and upper thermal limit for growth were estimated to be 1.8°C (SE = 0.63°C), 19.0°C (SE = 0.27°C), and 24.9°C (SE = 0.02°C), respectively. By taking a meta-analytical approach, we were able to provide a growth model that is applicable across populations of juvenile Chinook Salmon receiving an ad libitum ration of a pelleted diet.

  14. Neonatal resuscitation and immediate newborn assessment and stimulation for the prevention of neonatal deaths: a systematic review, meta-analysis and Delphi estimation of mortality effect

    Science.gov (United States)

    2011-01-01

    Background Of 136 million babies born annually, around 10 million require assistance to breathe. Each year 814,000 neonatal deaths result from intrapartum-related events in term babies (previously “birth asphyxia”) and 1.03 million from complications of prematurity. No systematic assessment of mortality reduction from tactile stimulation or resuscitation has been published. Objective To estimate the mortality effect of immediate newborn assessment and stimulation, and basic resuscitation on neonatal deaths due to term intrapartum-related events or preterm birth, for facility and home births. Methods We conducted systematic reviews for studies reporting relevant mortality or morbidity outcomes. Evidence was assessed using GRADE criteria adapted to provide a systematic approach to mortality effect estimates for the Lives Saved Tool (LiST). Meta-analysis was performed if appropriate. For interventions with low quality evidence but strong recommendation for implementation, a Delphi panel was convened to estimate effect size. Results We identified 24 studies of neonatal resuscitation reporting mortality outcomes (20 observational, 2 quasi-experimental, 2 cluster randomized controlled trials), but none of immediate newborn assessment and stimulation alone. A meta-analysis of three facility-based studies examined the effect of resuscitation training on intrapartum-related neonatal deaths (RR= 0.70, 95%CI 0.59-0.84); this estimate was used for the effect of facility-based basic neonatal resuscitation (additional to stimulation). The evidence for preterm mortality effect was low quality and thus expert opinion was sought. In community-based studies, resuscitation training was part of packages with multiple concurrent interventions, and/or studies did not distinguish term intrapartum-related from preterm deaths, hence no meta-analysis was conducted. Our Delphi panel of 18 experts estimated that immediate newborn assessment and stimulation would reduce both intrapartum-related

  15. A meta-analysis of the technology acceptance model : investigating subjective norm and moderation effects

    NARCIS (Netherlands)

    Schepers, J.J.L.; Wetzels, M.G.M.

    2007-01-01

    We conducted a quantitative meta-analysis of previous research on the technology acceptance model (TAM) in an attempt to make well-grounded statements on the role of subjective norm. Furthermore, we compared TAM results by taking into account moderating effects of one individual-related factor (type

  16. Estimated prevalence of halitosis: a systematic review and meta-regression analysis.

    Science.gov (United States)

    Silva, Manuela F; Leite, Fábio R M; Ferreira, Larissa B; Pola, Natália M; Scannapieco, Frank A; Demarco, Flávio F; Nascimento, Gustavo G

    2018-01-01

    This study aims to conduct a systematic review to determine the prevalence of halitosis in adolescents and adults. Electronic searches were performed using four different databases without restrictions: PubMed, Scopus, Web of Science, and SciELO. Population-based observational studies that provided data about the prevalence of halitosis in adolescents and adults were included. Additionally, meta-analyses, meta-regression, and sensitivity analyses were conducted to synthesize the evidence. A total of 584 articles were initially found and considered for title and abstract evaluation. Thirteen articles met inclusion criteria. The combined prevalence of halitosis was found to be 31.8% (95% CI 24.6-39.0%). Methodological aspects such as the year of publication and the socioeconomic status of the country where the study was conducted seemed to influence the prevalence of halitosis. Our results demonstrated that the estimated prevalence of halitosis was 31.8%, with high heterogeneity between studies. The results suggest a worldwide trend towards a rise in halitosis prevalence. Given the high prevalence of halitosis and its complex etiology, dental professionals should be aware of their roles in halitosis prevention and treatment.

  17. Simulation-based power calculations for planning a two-stage individual participant data meta-analysis.

    Science.gov (United States)

    Ensor, Joie; Burke, Danielle L; Snell, Kym I E; Hemming, Karla; Riley, Richard D

    2018-05-18

    Researchers and funders should consider the statistical power of planned Individual Participant Data (IPD) meta-analysis projects, as they are often time-consuming and costly. We propose simulation-based power calculations utilising a two-stage framework, and illustrate the approach for a planned IPD meta-analysis of randomised trials with continuous outcomes where the aim is to identify treatment-covariate interactions. The simulation approach has four steps: (i) specify an underlying (data generating) statistical model for trials in the IPD meta-analysis; (ii) use readily available information (e.g. from publications) and prior knowledge (e.g. number of studies promising IPD) to specify model parameter values (e.g. control group mean, intervention effect, treatment-covariate interaction); (iii) simulate an IPD meta-analysis dataset of a particular size from the model, and apply a two-stage IPD meta-analysis to obtain the summary estimate of interest (e.g. interaction effect) and its associated p-value; (iv) repeat the previous step (e.g. thousands of times), then estimate the power to detect a genuine effect by the proportion of summary estimates with a significant p-value. In a planned IPD meta-analysis of lifestyle interventions to reduce weight gain in pregnancy, 14 trials (1183 patients) promised their IPD to examine a treatment-BMI interaction (i.e. whether baseline BMI modifies intervention effect on weight gain). Using our simulation-based approach, a two-stage IPD meta-analysis has meta-analysis was appropriate. Pre-specified adjustment for prognostic factors would increase power further. Incorrect dichotomisation of BMI would reduce power by over 20%, similar to immediately throwing away IPD from ten trials. Simulation-based power calculations could inform the planning and funding of IPD projects, and should be used routinely.

  18. Meta-analysis of field-saturated hydraulic conductivity recovery following wildland fire: Applications for hydrologic model parameterization and resilience assessment

    Science.gov (United States)

    Ebel, Brian A.; Martin, Deborah

    2017-01-01

    Hydrologic recovery after wildfire is critical for restoring the ecosystem services of protecting of human lives and infrastructure from hazards and delivering water supply of sufficient quality and quantity. Recovery of soil-hydraulic properties, such as field-saturated hydraulic conductivity (Kfs), is a key factor for assessing the duration of watershed-scale flash flood and debris flow risks after wildfire. Despite the crucial role of Kfs in parameterizing numerical hydrologic models to predict the magnitude of postwildfire run-off and erosion, existing quantitative relations to predict Kfsrecovery with time since wildfire are lacking. Here, we conduct meta-analyses of 5 datasets from the literature that measure or estimate Kfs with time since wildfire for longer than 3-year duration. The meta-analyses focus on fitting 2 quantitative relations (linear and non-linear logistic) to explain trends in Kfs temporal recovery. The 2 relations adequately described temporal recovery except for 1 site where macropore flow dominated infiltration and Kfs recovery. This work also suggests that Kfs can have low hydrologic resistance (large postfire changes), and moderate to high hydrologic stability (recovery time relative to disturbance recurrence interval) and resilience (recovery of hydrologic function and provision of ecosystem services). Future Kfs relations could more explicitly incorporate processes such as soil-water repellency, ground cover and soil structure regeneration, macropore recovery, and vegetation regrowth.

  19. A meta-analysis of biomarkers related to oxidative stress and nitric oxide pathway in migraine.

    Science.gov (United States)

    Neri, Monica; Frustaci, Alessandra; Milic, Mirta; Valdiglesias, Vanessa; Fini, Massimo; Bonassi, Stefano; Barbanti, Piero

    2015-09-01

    Oxidative and nitrosative stress are considered key events in the still unclear pathophysiology of migraine. Studies comparing the level of biomarkers related to nitric oxide (NO) pathway/oxidative stress in the blood/urine of migraineurs vs. unaffected controls were extracted from the PubMed database. Summary estimates of mean ratios (MR) were carried out whenever a minimum of three papers were available. Nineteen studies were included in the meta-analyses, accounting for more than 1000 patients and controls, and compared with existing literature. Most studies measuring superoxide dismutase (SOD) showed lower activity in cases, although the meta-analysis in erythrocytes gave null results. On the contrary, plasma levels of thiobarbituric acid reactive substances (TBARS), an aspecific biomarker of oxidative damage, showed a meta-MR of 2.20 (95% CI: 1.65-2.93). As for NOs, no significant results were found in plasma, serum and urine. However, higher levels were shown during attacks, in patients with aura, and an effect of diet was found. The analysis of glutathione precursor homocysteine and asymmetric dimethylarginine (ADMA), an NO synthase inhibitor, gave inconclusive results. The role of the oxidative pathway in migraine is still uncertain. Interesting evidence emerged for TBARS and SOD, and concerning the possible role of diet in the control of NOx levels. © International Headache Society 2015.

  20. A Meta-Analytic Test of Redundancy and Relative Importance of the Dark Triad and Five-Factor Model of Personality.

    Science.gov (United States)

    O'Boyle, Ernest H; Forsyth, Donelson R; Banks, George C; Story, Paul A; White, Charles D

    2015-12-01

    We examined the relationships between Machiavellianism, narcissism, and psychopathy-the three traits of the Dark Triad (DT)-and the Five-Factor Model (FFM) of personality. The review identified 310 independent samples drawn from 215 sources and yielded information pertaining to global trait relationships and facet-level relationships. We used meta-analysis to examine (a) the bivariate relations between the DT and the five global traits and 30 facets of the FFM, (b) the relative importance of each of the FFM global traits in predicting DT, and (c) the relationship between the DT and FFM facets identified in translational models of narcissism and psychopathy. These analyses identified consistent and theoretically meaningful associations between the DT traits and the facets of the FFM. The five traits of the FFM, in a relative importance analysis, accounted for much of the variance in Machiavellianism, narcissism, and psychopathy, respectively, and facet-level analyses identified specific facets of each FFM trait that were consistently associated with narcissism (e.g., angry/hostility, modesty) and psychopathy (e.g., straightforwardness, deliberation). The FFM explained nearly all of the variance in psychopathy (R(2) c  = .88) and a substantial portion of the variance in narcissism (R(2) c  = .42). © 2014 Wiley Periodicals, Inc.

  1. Effectiveness and cost-effectiveness of antidepressants in primary care: a multiple treatment comparison meta-analysis and cost-effectiveness model.

    Directory of Open Access Journals (Sweden)

    Joakim Ramsberg

    Full Text Available OBJECTIVE: To determine effectiveness and cost-effectiveness over a one-year time horizon of pharmacological first line treatment in primary care for patients with moderate to severe depression. DESIGN: A multiple treatment comparison meta-analysis was employed to determine the relative efficacy in terms of remission of 10 antidepressants (citalopram, duloxetine escitalopram, fluoxetine, fluvoxamine mirtazapine, paroxetine, reboxetine, sertraline and venlafaxine. The estimated remission rates were then applied in a decision-analytic model in order to estimate costs and quality of life with different treatments at one year. DATA SOURCES: Meta-analyses of remission rates from randomised controlled trials, and cost and quality-of-life data from published sources. RESULTS: The most favourable pharmacological treatment in terms of remission was escitalopram with an 8- to 12-week probability of remission of 0.47. Despite a high acquisition cost, this clinical effectiveness translated into escitalopram being both more effective and having a lower total cost than all other comparators from a societal perspective. From a healthcare perspective, the cost per QALY of escitalopram was €3732 compared with venlafaxine. CONCLUSION: Of the investigated antidepressants, escitalopram has the highest probability of remission and is the most effective and cost-effective pharmacological treatment in a primary care setting, when evaluated over a one year time-horizon. Small differences in remission rates may be important when assessing costs and cost-effectiveness of antidepressants.

  2. A model-based correction for outcome reporting bias in meta-analysis.

    Science.gov (United States)

    Copas, John; Dwan, Kerry; Kirkham, Jamie; Williamson, Paula

    2014-04-01

    It is often suspected (or known) that outcomes published in medical trials are selectively reported. A systematic review for a particular outcome of interest can only include studies where that outcome was reported and so may omit, for example, a study that has considered several outcome measures but only reports those giving significant results. Using the methodology of the Outcome Reporting Bias (ORB) in Trials study of (Kirkham and others, 2010. The impact of outcome reporting bias in randomised controlled trials on a cohort of systematic reviews. British Medical Journal 340, c365), we suggest a likelihood-based model for estimating the effect of ORB on confidence intervals and p-values in meta-analysis. Correcting for bias has the effect of moving estimated treatment effects toward the null and hence more cautious assessments of significance. The bias can be very substantial, sometimes sufficient to completely overturn previous claims of significance. We re-analyze two contrasting examples, and derive a simple fixed effects approximation that can be used to give an initial estimate of the effect of ORB in practice.

  3. e-Government Maturity Model Based on Systematic Review and Meta-Ethnography Approach

    Directory of Open Access Journals (Sweden)

    Darmawan Napitupulu

    2016-11-01

    Full Text Available Maturity model based on e-Government portal has been developed by a number of researchers both individually and institutionally, but still scattered in various journals and conference articles and can be said to have a different focus with each other, both in terms of stages and features. The aim of this research is conducting a study to integrate a number of maturity models existing today in order to build generic maturity model based on e-Government portal. The method used in this study is Systematic Review with meta-ethnography qualitative approach. Meta-ethnography, which is part of Systematic Review method, is a technique to perform data integration to obtain theories and concepts with a new level of understanding that is deeper and thorough. The result obtained is a maturity model based on e-Government portal that consists of 7 (seven stages, namely web presence, interaction, transaction, vertical integration, horizontal integration, full integration, and open participation. These seven stages are synthesized from the 111 key concepts related to 25 studies of maturity model based e-Government portal. The maturity model resulted is more comprehensive and generic because it is an integration of models (best practices that exists today.

  4. Meta-analysis of individual registry results enhances international registry collaboration.

    Science.gov (United States)

    Paxton, Elizabeth W; Mohaddes, Maziar; Laaksonen, Inari; Lorimer, Michelle; Graves, Stephen E; Malchau, Henrik; Namba, Robert S; Kärrholm, John; Rolfson, Ola; Cafri, Guy

    2018-03-28

    Background and purpose - Although common in medical research, meta-analysis has not been widely adopted in registry collaborations. A meta-analytic approach in which each registry conducts a standardized analysis on its own data followed by a meta-analysis to calculate a weighted average of the estimates allows collaboration without sharing patient-level data. The value of meta-analysis as an alternative to individual patient data analysis is illustrated in this study by comparing the risk of revision of porous tantalum cups versus other uncemented cups in primary total hip arthroplasties from Sweden, Australia, and a US registry (2003-2015). Patients and methods - For both individual patient data analysis and meta-analysis approaches a Cox proportional hazard model was fit for time to revision, comparing porous tantalum (n = 23,201) with other uncemented cups (n = 128,321). Covariates included age, sex, diagnosis, head size, and stem fixation. In the meta-analysis approach, treatment effect size (i.e., Cox model hazard ratio) was calculated within each registry and a weighted average for the individual registries' estimates was calculated. Results - Patient-level data analysis and meta-analytic approaches yielded the same results with the porous tantalum cups having a higher risk of revision than other uncemented cups (HR (95% CI) 1.6 (1.4-1.7) and HR (95% CI) 1.5 (1.4-1.7), respectively). Adding the US cohort to the meta-analysis led to greater generalizability, increased precision of the treatment effect, and similar findings (HR (95% CI) 1.6 (1.4-1.7)) with increased risk of porous tantalum cups. Interpretation - The meta-analytic technique is a viable option to address privacy, security, and data ownership concerns allowing more expansive registry collaboration, greater generalizability, and increased precision of treatment effects.

  5. Comparison of variance estimators for metaanalysis of instrumental variable estimates

    NARCIS (Netherlands)

    Schmidt, A. F.; Hingorani, A. D.; Jefferis, B. J.; White, J.; Groenwold, R. H H; Dudbridge, F.; Ben-Shlomo, Y.; Chaturvedi, N.; Engmann, J.; Hughes, A.; Humphries, S.; Hypponen, E.; Kivimaki, M.; Kuh, D.; Kumari, M.; Menon, U.; Morris, R.; Power, C.; Price, J.; Wannamethee, G.; Whincup, P.

    2016-01-01

    Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two

  6. Determinants of investment behaviour. Methods and applications of meta-analysis

    International Nuclear Information System (INIS)

    Koetse, M.J.

    2006-01-01

    Meta-analysis is gradually gaining ground in economics as a research method to objectively and quantitatively summarise a body of existing empirical evidence. This dissertation studies the performance of well-known meta-analytic models and presents two meta-analysis applications. Despite its many attractive features, meta-analysis faces several methodical difficulties, especially when applied in economic research. We investigate two specific methodical problems that any meta-analysis in economics will have to deal with, viz., systematic effect-size variation due to primary-study misspecifications, and random effect-size heterogeneity. Using Monte-Carlo analysis we investigate the effects of these methodical problems on the results of a meta-analysis, and study the small-sample properties of several well-known and often applied meta-estimators. The focus of the meta-analysis applications is on two topics that are relevant for understanding investment behaviour, viz., the impact of uncertainty on investment spending, and the potential for substitution of capital for energy in production processes. In the first application we aim to shed light on the direction of the relationship between investment and uncertainty, and to uncover which factors are empirically relevant for explaining the wide variety in study outcomes. In the second application our goal is to analyse the direction and magnitude of capital-energy substitution potential, and to analyse the empirical relevance of suggested sources of variation in elasticity estimates

  7. Determinants of investment behaviour. Methods and applications of meta-analysis

    Energy Technology Data Exchange (ETDEWEB)

    Koetse, M.J.

    2006-03-14

    Meta-analysis is gradually gaining ground in economics as a research method to objectively and quantitatively summarise a body of existing empirical evidence. This dissertation studies the performance of well-known meta-analytic models and presents two meta-analysis applications. Despite its many attractive features, meta-analysis faces several methodical difficulties, especially when applied in economic research. We investigate two specific methodical problems that any meta-analysis in economics will have to deal with, viz., systematic effect-size variation due to primary-study misspecifications, and random effect-size heterogeneity. Using Monte-Carlo analysis we investigate the effects of these methodical problems on the results of a meta-analysis, and study the small-sample properties of several well-known and often applied meta-estimators. The focus of the meta-analysis applications is on two topics that are relevant for understanding investment behaviour, viz., the impact of uncertainty on investment spending, and the potential for substitution of capital for energy in production processes. In the first application we aim to shed light on the direction of the relationship between investment and uncertainty, and to uncover which factors are empirically relevant for explaining the wide variety in study outcomes. In the second application our goal is to analyse the direction and magnitude of capital-energy substitution potential, and to analyse the empirical relevance of suggested sources of variation in elasticity estimates.

  8. Improved resolution in the position of drought-related QTLs in a single mapping population of rice by meta-analysis

    Directory of Open Access Journals (Sweden)

    Courtois Brigitte

    2009-06-01

    Azucena map of September 2007 to genetic and physical position on the map-base sequence of rice. This files shows the position of markers used in the Bala × Azucena map in (Kosambi cM, the position on the International Rice Genome Sequencing Project map where alignment is possible, the gene model to which the marker belongs where applicable, the position of the marker on the Nipponbare sequence if available and, if not available the position on the Nipponbare sequence of the PACor BAC clone which that marker hybridizes if that is available. The column for alternative names are abbreviated names of some markers used by the authors in previous publications. Click here for file Conclusion The meta-analysis is valuable in providing improved ability to dissect the complex genetic structure of traits, and distinguish between pleiotropy and close linkage. It also provides relatively small target regions for the identification of positional candidate genes.

  9. Neural Correlates of Psychotherapy in Anxiety and Depression: A Meta-Analysis

    Science.gov (United States)

    Messina, Irene; Sambin, Marco; Palmieri, Arianna; Viviani, Roberto

    2013-01-01

    Several studies have used neuroimaging methods to identify neural change in brain networks associated to emotion regulation after psychotherapy of depression and anxiety. In the present work we adopted a meta-analytic technique specific to neuroimaging data to evaluate the consistence of empirical findings and assess models of therapy that have been proposed in the literature. Meta-analyses were conducted with the Activation Likelihood Estimation technique, which evaluates the overlap between foci of activation across studies. The analysis included 16 studies found in Pubmed (200 foci of activation and 193 patients). Separate meta-analyses were conducted on studies of 1) depression, post-traumatic stress disorder and panic disorder investigated with rest state metabolism (6 studies, 70 patients); 2) depression, post-traumatic stress disorder and panic disorder investigated with task-related activation studies (5 studies, 65 patients); 3) the previous studies considered jointly; and 4) phobias investigated with studies on exposure-related activation (5 studies, 57 patients). Studies on anxiety and depression gave partially consistent results for changes in the dorsomedial prefrontal cortex and in the posterior cingulated gyrus/precuneus. Several areas of change in the temporal lobes were also observed. Studies on the therapy of phobia were consistent with a reduction of activity in medial temporal areas. The cluster of change in the prefrontal cortex may refer to increased recruitment of control processes, as hypothesized by influential models of emotion regulation changes due to psychotherapy. However, not all areas associated with controlled emotion regulation were detected in the meta-analysis, while involvement of midline structures suggested changes in self-related information processing. Changes in phobia were consistent with reduced reactivity to phobic stimuli. PMID:24040309

  10. Neural correlates of psychotherapy in anxiety and depression: a meta-analysis.

    Directory of Open Access Journals (Sweden)

    Irene Messina

    Full Text Available Several studies have used neuroimaging methods to identify neural change in brain networks associated to emotion regulation after psychotherapy of depression and anxiety. In the present work we adopted a meta-analytic technique specific to neuroimaging data to evaluate the consistence of empirical findings and assess models of therapy that have been proposed in the literature. Meta-analyses were conducted with the Activation Likelihood Estimation technique, which evaluates the overlap between foci of activation across studies. The analysis included 16 studies found in Pubmed (200 foci of activation and 193 patients. Separate meta-analyses were conducted on studies of 1 depression, post-traumatic stress disorder and panic disorder investigated with rest state metabolism (6 studies, 70 patients; 2 depression, post-traumatic stress disorder and panic disorder investigated with task-related activation studies (5 studies, 65 patients; 3 the previous studies considered jointly; and 4 phobias investigated with studies on exposure-related activation (5 studies, 57 patients. Studies on anxiety and depression gave partially consistent results for changes in the dorsomedial prefrontal cortex and in the posterior cingulated gyrus/precuneus. Several areas of change in the temporal lobes were also observed. Studies on the therapy of phobia were consistent with a reduction of activity in medial temporal areas. The cluster of change in the prefrontal cortex may refer to increased recruitment of control processes, as hypothesized by influential models of emotion regulation changes due to psychotherapy. However, not all areas associated with controlled emotion regulation were detected in the meta-analysis, while involvement of midline structures suggested changes in self-related information processing. Changes in phobia were consistent with reduced reactivity to phobic stimuli.

  11. The relation between self-conscious emotions and delinquency : A meta-analysis

    NARCIS (Netherlands)

    Spruit, A.; Schalkwijk, F.; van Vugt, E.; Stams, G.J.

    Self-conscious emotions are expected to be related to delinquency, as they guide moral decision making. In the current study, two separate multilevel meta-analyses were performed to examine the overall relation between guilt, shame and delinquency. In addition, possible moderating factors were

  12. Prevalence of Enuresis and its Related Factors among Children in Iran: A Systematic Review and Meta-analysis

    Directory of Open Access Journals (Sweden)

    Atekeh Hadinezhad Makrani

    2015-11-01

    Full Text Available Introduction: Enuresis is the second most common disorder among children after allergic disorders. According to the results of previous studies, different estimates of enuresis prevalence and its related factors have been reported. Combining the results of these studies is valuable. This study aims to estimate the prevalence of enuresis and its related factors among Iranian children.Materials and Methods:Relevant articles published during 2000 to 15 May 2015 were identified by a comprehensive search within national and international databanks. Having applied inclusion/exclusion criteria and quality assessment, eligible papers were selected. In addition, references of the articles were reviewed to enhance the search strategy. Standard error of the prevalence in each study was calculated using binomial distribution. Random effects model was used to combine the results. All data analyses were performed using STATA SE V.11 software. Results: We entered 15 eligible articles into the systematic review/meta-analysis recruited 20832 Iranian children. Prevalence (95% CI of enuresis among all children, boys and girls were estimated as of 11.01% (9.2-12.8, 13.9%(11.2-16.7 and 8.4%(6.3-10.6 respectively. Enuresis was more common among children with positive familial history, those with deep sleep, high water consumption, sniffing, low educated and low income parents, mouth breathing, urinary tract infection and children with history of corporal punishment. Conclusion: Our study showed that a considerable proportion of Iranian children are suffering from enuresis and male gender is a predictive factor for this disorder.

  13. Grain yield increase in cereal variety mixtures: A meta-analysis of field trials

    DEFF Research Database (Denmark)

    Kiær, Lars Pødenphant; Skovgaard, Ib; Østergård, Hanne

    2009-01-01

    on grain yield. To investigate the prevalence and preconditions for positive mixing effects, reported grain yields of variety mixtures and pure variety stands were obtained from previously published variety trials, converted into relative mixing effects and combined using meta-analysis. Furthermore...... as meeting the criteria for inclusion in the meta-analysis; on the other hand, nearly 200 studies were discarded. The accepted studies reported results on both winter and spring types of each crop species. Relative mixing effects ranged from 30% to 100% with an overall meta-estimate of at least 2.7% (p

  14. The Review Systematic and Meta Analysis of Prevalence and Causes of Nosocomial Infection in Iran

    Directory of Open Access Journals (Sweden)

    Pezhman Bagheri

    2014-12-01

    Full Text Available Background and Aim: The variation of reported nosocomial infection is very high respectively. It seems review systematic and Meta analysis of related documents gives precise estimate of this subject for correct politisize. So tha aim of this study the review systematic and meta analysis of prevalence and causes of nosocomial infection in iran. Materials and Methods: For this study all articles published in Iranian journals and international journals, Final Report of Research Projects, related papers presented at congresses and thesis were reviewed with using standard and sensitive keywords. Then, all articles published between 1997-2010 years that had eligibility Inclusion criteria after quality control, using random model, intered to process of meta-analysis. Results: The finding show that the best estimate of total prevalence of nosocomial infection in Iran is 30.43% and the most common infections of nosocomial infection are respiratory infection 39.4%%, urinary infection 23.88%, bacteremia 21.98% and the most common factors of nosocomial infection are Pseudomonas aeroginosa 26.78%, klebsiella 31.42%, Staphylococcus 23.6% and E.coli 30.93%. The research also found a substantial heterogeneity that using meta regression method the main cause of produce of this heterogeneity, participants people, sample size, average age of the samples, time of study and gender were introduced. Conclusions: The simple review of studied documents in this survey show that prevalence rate of different nosocomial infection in Iran is high relatively. Hence make appropriate and evidence-based educational and control programs to reduce nosocomial infections prevalence rate in Iran should be considered by policy makers.

  15. Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study.

    Directory of Open Access Journals (Sweden)

    Binod Neupane

    Full Text Available In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when

  16. The Neural Bases of Difficult Speech Comprehension and Speech Production: Two Activation Likelihood Estimation (ALE) Meta-Analyses

    Science.gov (United States)

    Adank, Patti

    2012-01-01

    The role of speech production mechanisms in difficult speech comprehension is the subject of on-going debate in speech science. Two Activation Likelihood Estimation (ALE) analyses were conducted on neuroimaging studies investigating difficult speech comprehension or speech production. Meta-analysis 1 included 10 studies contrasting comprehension…

  17. Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration

    Directory of Open Access Journals (Sweden)

    Kelemen Arpad

    2008-08-01

    Full Text Available Abstract Background This paper addresses key biological problems and statistical issues in the analysis of large gene expression data sets that describe systemic temporal response cascades to therapeutic doses in multiple tissues such as liver, skeletal muscle, and kidney from the same animals. Affymetrix time course gene expression data U34A are obtained from three different tissues including kidney, liver and muscle. Our goal is not only to find the concordance of gene in different tissues, identify the common differentially expressed genes over time and also examine the reproducibility of the findings by integrating the results through meta analysis from multiple tissues in order to gain a significant increase in the power of detecting differentially expressed genes over time and to find the differential differences of three tissues responding to the drug. Results and conclusion Bayesian categorical model for estimating the proportion of the 'call' are used for pre-screening genes. Hierarchical Bayesian Mixture Model is further developed for the identifications of differentially expressed genes across time and dynamic clusters. Deviance information criterion is applied to determine the number of components for model comparisons and selections. Bayesian mixture model produces the gene-specific posterior probability of differential/non-differential expression and the 95% credible interval, which is the basis for our further Bayesian meta-inference. Meta-analysis is performed in order to identify commonly expressed genes from multiple tissues that may serve as ideal targets for novel treatment strategies and to integrate the results across separate studies. We have found the common expressed genes in the three tissues. However, the up/down/no regulations of these common genes are different at different time points. Moreover, the most differentially expressed genes were found in the liver, then in kidney, and then in muscle.

  18. Exposure to traffic-related air pollution and risk of development of childhood asthma: A systematic review and meta-analysis.

    Science.gov (United States)

    Khreis, Haneen; Kelly, Charlotte; Tate, James; Parslow, Roger; Lucas, Karen; Nieuwenhuijsen, Mark

    2017-03-01

    The question of whether children's exposure to traffic-related air pollution (TRAP) contributes to their development of asthma is unresolved. We conducted a systematic review and performed meta-analyses to analyze the association between TRAP and asthma development in childhood. We systematically reviewed epidemiological studies published until 8 September 2016 and available in the Embase, Ovid MEDLINE (R), and Transport databases. We included studies that examined the association between children's exposure to TRAP metrics and their risk of 'asthma' incidence or lifetime prevalence, from birth to age 18years old. We extracted key characteristics of each included study using a predefined data items template and these were tabulated. We used the Critical Appraisal Skills Programme checklists to assess the validity of each included study. Where four or more independent risk estimates were available for a continuous pollutant exposure, we conducted overall and age-specific meta-analyses, and four sensitivity analyses for each summary meta-analytic exposure-outcome association. Forty-one studies met our eligibility criteria. There was notable variability in asthma definitions, TRAP exposure assessment methods and confounder adjustment. The overall random-effects risk estimates (95% CI) were 1.08 (1.03, 1.14) per 0.5×10 -5 m -1 black carbon (BC), 1.05 (1.02, 1.07) per 4μg/m 3 nitrogen dioxide (NO 2 ), 1.48 (0.89, 2.45) per 30μg/m 3 nitrogen oxides (NO x ), 1.03 (1.01, 1.05) per 1μg/m 3 Particulate Matter asthma development. Our findings support the hypothesis that childhood exposure to TRAP contributes to their development of asthma. Future meta-analyses would benefit from greater standardization of study methods including exposure assessment harmonization, outcome harmonization, confounders' harmonization and the inclusion of all important confounders in individual studies. PROSPERO 2014: CRD42014015448. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. A Bayesian Meta-Analysis of the Effect of Alcohol Use on HCV-Treatment Outcomes with a Comparison of Resampling Methods to Assess Uncertainty in Parameter Estimates.

    Energy Technology Data Exchange (ETDEWEB)

    Cauthen, Katherine Regina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lambert, Gregory Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Finley, Patrick D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ross, David [US Dept. of Veterans Affairs, Washington, DC (United States); Chartier, Maggie [US Dept. of Veterans Affairs, Washington, DC (United States); Davey, Victoria J. [US Dept. of Veterans Affairs, Washington, DC (United States)

    2015-10-01

    There is mounting evidence that alcohol use is significantly linked to lower HCV treatment response rates in interferon-based therapies, though some of the evidence is conflicting. Furthermore, although health care providers recommend reducing or abstaining from alcohol use prior to treatment, many patients do not succeed in doing so. The goal of this meta-analysis was to systematically review and summarize the Englishlanguage literature up through January 30, 2015 regarding the relationship between alcohol use and HCV treatment outcomes, among patients who were not required to abstain from alcohol use in order to receive treatment. Seven pertinent articles studying 1,751 HCV-infected patients were identified. Log-ORs of HCV treatment response for heavy alcohol use and light alcohol use were calculated and compared. We employed a hierarchical Bayesian meta-analytic model to accommodate the small sample size. The summary estimate for the log-OR of HCV treatment response was -0.775 with a 95% credible interval of (-1.397, -0.236). The results of the Bayesian meta-analysis are slightly more conservative compared to those obtained from a boot-strapped, random effects model. We found evidence of heterogeneity (Q = 14.489, p = 0.025), accounting for 60.28% of the variation among log-ORs. Meta-regression to capture the sources of this heterogeneity did not identify any of the covariates investigated as significant. This meta-analysis confirms that heavy alcohol use is associated with decreased HCV treatment response compared to lighter levels of alcohol use. Further research is required to characterize the mechanism by which alcohol use affects HCV treatment response.

  20. Effect of clinical response to active drugs and placebo on antipsychotics and mood stabilizers relative efficacy for bipolar depression and mania: A meta-regression analysis.

    Science.gov (United States)

    Bartoli, Francesco; Clerici, Massimo; Di Brita, Carmen; Riboldi, Ilaria; Crocamo, Cristina; Carrà, Giuseppe

    2018-04-01

    Randomised placebo-controlled trials investigating treatments for bipolar disorder have been hampered by wide variations of active drugs and placebo clinical response rates. It is important to estimate whether the active drug or placebo response has a greater influence in determining the relative efficacy of drugs for psychosis (antipsychotics) and relapse prevention (mood stabilisers) for bipolar depression and mania. We identified 53 randomised, placebo-controlled trials assessing antipsychotic or mood stabiliser monotherapy ('active drugs') for bipolar depression or mania. We carried out random-effects meta-regressions, estimating the influence of active drugs and placebo response rates on treatment relative efficacy. Meta-regressions showed that treatment relative efficacy for bipolar mania was influenced by the magnitude of clinical response to active drugs ( p=0.002), but not to placebo ( p=0.60). On the other hand, treatment relative efficacy for bipolar depression was influenced by response to placebo ( p=0.047), but not to active drugs ( p=0.98). Despite several limitations, our unexpected findings showed that antipsychotics / mood stabilisers relative efficacy for bipolar depression seems unrelated to active drugs response rates, depending only on clinical response to placebo. Future research should explore strategies to reduce placebo-related issues in randomised, placebo-controlled trials for bipolar depression.

  1. Estimation of genetic parameters related to eggshell strength using random regression models.

    Science.gov (United States)

    Guo, J; Ma, M; Qu, L; Shen, M; Dou, T; Wang, K

    2015-01-01

    This study examined the changes in eggshell strength and the genetic parameters related to this trait throughout a hen's laying life using random regression. The data were collected from a crossbred population between 2011 and 2014, where the eggshell strength was determined repeatedly for 2260 hens. Using random regression models (RRMs), several Legendre polynomials were employed to estimate the fixed, direct genetic and permanent environment effects. The residual effects were treated as independently distributed with heterogeneous variance for each test week. The direct genetic variance was included with second-order Legendre polynomials and the permanent environment with third-order Legendre polynomials. The heritability of eggshell strength ranged from 0.26 to 0.43, the repeatability ranged between 0.47 and 0.69, and the estimated genetic correlations between test weeks was high at > 0.67. The first eigenvalue of the genetic covariance matrix accounted for about 97% of the sum of all the eigenvalues. The flexibility and statistical power of RRM suggest that this model could be an effective method to improve eggshell quality and to reduce losses due to cracked eggs in a breeding plan.

  2. Poor prognostic value of the modified Mallampati score: a meta-analysis involving 177 088 patients

    DEFF Research Database (Denmark)

    Lundstrøm, L H; Vester-Andersen, M; Møller, Ann

    2011-01-01

    searches. The pooled estimates from the meta-analyses were calculated based on a random-effects model and a summary receiver operating curve. Meta-regression analyses were performed to explore sources of possible heterogeneity between the studies. The summary receiver operating curve demonstrated an area...

  3. Estimating the attributable fraction for melanoma: a meta-analysis of pigmentary characteristics and freckling.

    Science.gov (United States)

    Olsen, Catherine M; Carroll, Heidi J; Whiteman, David C

    2010-11-15

    Epidemiologic research has demonstrated convincingly that certain pigmentary characteristics are associated with increased relative risks of melanoma; however there has been no comprehensive review to rank these characteristics in order of their importance on a population level. We conducted a systematic review of the literature and meta-analysis to quantify the contribution of pigmentary characteristics to melanoma, estimated by the population-attributable fraction (PAF). Eligible studies were those that permitted quantitative assessment of the association between histologically confirmed melanoma and hair colour, eye colour, skin phototype and presence of freckling; we identified 66 such studies using citation databases, followed by manual review of retrieved references. We calculated summary relative risks using weighted averages of the log RR, taking into account random effects, and used these to estimate the PAF. The pooled RRs for pigmentary characteristics were: 2.64 for red/red-blond, 2.0 for blond and 1.46 for light brown hair colour (vs. dark); 1.57 for blue/blue-grey and 1.51 for green/grey/hazel eye colour (vs. dark); 2.27, 1.99 and 1.35 for skin phototypes I, II and III respectively (vs. IV); and 1.99 for presence of freckling. The highest PAFs were observed for skin phototypes 1/II (0.27), presence of freckling (0.23), and blond hair colour (0.23). For eye colour, the PAF for blue/blue-grey eye colour was higher than for green/grey/hazel eye colour (0.18 vs. 0.13). The PAF of melanoma associated with red hair colour was 0.10. These estimates of melanoma burden attributable to pigmentary characteristics provide a basis for designing prevention strategies for melanoma.

  4. Are Parents' Gender Schemas Related to Their Children's Gender-Related Cognitions? A Meta-Analysis.

    Science.gov (United States)

    Tenenbaum, Harriet R.; Leaper, Campbell

    2002-01-01

    Used meta-analysis to examine relationship of parents' gender schemas and their offspring's gender-related cognitions, with samples ranging in age from infancy through early adulthood. Found a small but meaningful effect size (r=.16) indicating a positive correlation between parent gender schema and offspring measures. Effect sizes were influenced…

  5. Dynamical SUSY breaking in meta-stable vacua

    International Nuclear Information System (INIS)

    Intriligator, Kenneth; Seiberg, Nathan; Shih, David

    2006-01-01

    Dynamical supersymmetry breaking in a long-lived meta-stable vacuum is a phenomenologically viable possibility. This relatively unexplored avenue leads to many new models of dynamical supersymmetry breaking. Here, we present a surprisingly simple class of models with meta-stable dynamical supersymmetry breaking: N = 1 supersymmetric QCD, with massive flavors. Though these theories are strongly coupled, we definitively demonstrate the existence of meta-stable vacua by using the free-magnetic dual. Model building challenges, such as large flavor symmetries and the absence of an R-symmetry, are easily accommodated in these theories. Their simplicity also suggests that broken supersymmetry is generic in supersymmetric field theory and in the landscape of string vacua

  6. Multivariate Meta-Analysis Using Individual Participant Data

    Science.gov (United States)

    Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

    2015-01-01

    When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is…

  7. Blind estimation of a ship's relative wave heading

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; Iseki, Toshio

    2012-01-01

    This article proposes a method to estimate a ship’s relative heading against the waves. The procedure relies purely on ship- board measurements of global responses such as motion components, accelerations and the bending moment amidships. There is no particular (mathematical) model connected to t...... to the estimate, and therefore it is called a ’blind estimate’. The approach is in this introductory study tested by analysing simulated data. The analysis reveals that it is possible to estimate a ship’s relative heading on the basis of shipboard measurements only....

  8. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

    Science.gov (United States)

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

    Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

  9. Feature and Meta-Models in Clafer: Mixed, Specialized, and Coupled

    DEFF Research Database (Denmark)

    Bąk, Kacper; Czarnecki, Krzysztof; Wasowski, Andrzej

    2011-01-01

    constraints (such as mapping feature configurations to component configurations or model templates). Clafer also allows arranging models into multiple specialization and extension layers via constraints and inheritance. We identify four key mechanisms allowing a meta-modeling language to express feature...

  10. Model and Interoperability using Meta Data Annotations

    Science.gov (United States)

    David, O.

    2011-12-01

    Software frameworks and architectures are in need for meta data to efficiently support model integration. Modelers have to know the context of a model, often stepping into modeling semantics and auxiliary information usually not provided in a concise structure and universal format, consumable by a range of (modeling) tools. XML often seems the obvious solution for capturing meta data, but its wide adoption to facilitate model interoperability is limited by XML schema fragmentation, complexity, and verbosity outside of a data-automation process. Ontologies seem to overcome those shortcomings, however the practical significance of their use remains to be demonstrated. OMS version 3 took a different approach for meta data representation. The fundamental building block of a modular model in OMS is a software component representing a single physical process, calibration method, or data access approach. Here, programing language features known as Annotations or Attributes were adopted. Within other (non-modeling) frameworks it has been observed that annotations lead to cleaner and leaner application code. Framework-supported model integration, traditionally accomplished using Application Programming Interfaces (API) calls is now achieved using descriptive code annotations. Fully annotated components for various hydrological and Ag-system models now provide information directly for (i) model assembly and building, (ii) data flow analysis for implicit multi-threading or visualization, (iii) automated and comprehensive model documentation of component dependencies, physical data properties, (iv) automated model and component testing, calibration, and optimization, and (v) automated audit-traceability to account for all model resources leading to a particular simulation result. Such a non-invasive methodology leads to models and modeling components with only minimal dependencies on the modeling framework but a strong reference to its originating code. Since models and

  11. Effects of Yoga on Measures of Health-related Quality of Life from SF-36 and SF-12 Assessments: A Systematic Review and Meta-analysis

    Directory of Open Access Journals (Sweden)

    Gabriel Benavidez

    2017-12-01

    Full Text Available Objectives Yoga is commonly being adopted and prescribed with the intent to increase a participant’s health-related quality of life. In practice, the current gold-standard health-related quality of life measurement tool is the SF-36 and SF-12 assessments. Therefore, it is important for yoga scientists and practitioners to understand yoga’s effects on health-related quality of life when in fact a gold-standard assessment is implemented. The purpose of this study was to employ systematic review and meta-analytic techniques to examine the effect of yoga on measures of health-related quality of life measured using only the SF-36/12 assessments. Methods A current (January 2007 to December 2016 systematic review of the Pubmed database was conducted and included studies that used yoga as an intervention with outcomes measures of health-related quality of life measured by the SF-36/12. Ten different measures were extracted from studies including eight dimension scores (physical functioning, bodily pain, physical role function, general health, mental health, emotional role function, social function, and vitality and two summary scores (physical component and mental component. Ten different meta-analyses were performed using calculated standardized mean effect sizes and random effects models. Both moderator and sensitivity analyses were conducted. Results A total of 34 studies were included is the analyses with 185 independent effect sizes. Yoga intervention showed a significant positive effect on all ten measures of the SF-36/12. Effects ranged from 0.56 (0.39-0.73 to 0.28 (0.17-0.40. Yoga type (Hatha, Iyengar, Other moderated the effects of yoga intervention on the mental component (p=.021, with Hatha yielding the greatest effects (ES=1.63, 0.61-2.65. The sensitivity analysis showed little to no bias in mean effect size estimates. Conclusions The meta-analytic evidence clearly supports the small-to-medium positive effects of yoga on health-related

  12. Predicted effect size of lisdexamfetamine treatment of attention deficit/hyperactivity disorder (ADHD) in European adults: Estimates based on indirect analysis using a systematic review and meta-regression analysis.

    Science.gov (United States)

    Fridman, M; Hodgkins, P S; Kahle, J S; Erder, M H

    2015-06-01

    There are few approved therapies for adults with attention-deficit/hyperactivity disorder (ADHD) in Europe. Lisdexamfetamine (LDX) is an effective treatment for ADHD; however, no clinical trials examining the efficacy of LDX specifically in European adults have been conducted. Therefore, to estimate the efficacy of LDX in European adults we performed a meta-regression of existing clinical data. A systematic review identified US- and Europe-based randomized efficacy trials of LDX, atomoxetine (ATX), or osmotic-release oral system methylphenidate (OROS-MPH) in children/adolescents and adults. A meta-regression model was then fitted to the published/calculated effect sizes (Cohen's d) using medication, geographical location, and age group as predictors. The LDX effect size in European adults was extrapolated from the fitted model. Sensitivity analyses performed included using adult-only studies and adding studies with placebo designs other than a standard pill-placebo design. Twenty-two of 2832 identified articles met inclusion criteria. The model-estimated effect size of LDX for European adults was 1.070 (95% confidence interval: 0.738, 1.401), larger than the 0.8 threshold for large effect sizes. The overall model fit was adequate (80%) and stable in the sensitivity analyses. This model predicts that LDX may have a large treatment effect size in European adults with ADHD. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  13. Grey literature in meta-analyses.

    Science.gov (United States)

    Conn, Vicki S; Valentine, Jeffrey C; Cooper, Harris M; Rantz, Marilyn J

    2003-01-01

    In meta-analysis, researchers combine the results of individual studies to arrive at cumulative conclusions. Meta-analysts sometimes include "grey literature" in their evidential base, which includes unpublished studies and studies published outside widely available journals. Because grey literature is a source of data that might not employ peer review, critics have questioned the validity of its data and the results of meta-analyses that include it. To examine evidence regarding whether grey literature should be included in meta-analyses and strategies to manage grey literature in quantitative synthesis. This article reviews evidence on whether the results of studies published in peer-reviewed journals are representative of results from broader samplings of research on a topic as a rationale for inclusion of grey literature. Strategies to enhance access to grey literature are addressed. The most consistent and robust difference between published and grey literature is that published research is more likely to contain results that are statistically significant. Effect size estimates of published research are about one-third larger than those of unpublished studies. Unfunded and small sample studies are less likely to be published. Yet, importantly, methodological rigor does not differ between published and grey literature. Meta-analyses that exclude grey literature likely (a) over-represent studies with statistically significant findings, (b) inflate effect size estimates, and (c) provide less precise effect size estimates than meta-analyses including grey literature. Meta-analyses should include grey literature to fully reflect the existing evidential base and should assess the impact of methodological variations through moderator analysis.

  14. Self-Concept and Academic Achievement: A Meta-Analysis of Longitudinal Relations

    Science.gov (United States)

    Huang, Chiungjung

    2011-01-01

    The relation between self-concept and academic achievement was examined in 39 independent and longitudinal samples through the integration of meta-analysis and path analysis procedures. For relations with more than 3 independent samples, the mean observed correlations ranged from 0.20 to 0.27 between prior self-concept and subsequent academic…

  15. Evaluating the Quality of Evidence from a Network Meta-Analysis

    Science.gov (United States)

    Salanti, Georgia; Del Giovane, Cinzia; Chaimani, Anna; Caldwell, Deborah M.; Higgins, Julian P. T.

    2014-01-01

    Systematic reviews that collate data about the relative effects of multiple interventions via network meta-analysis are highly informative for decision-making purposes. A network meta-analysis provides two types of findings for a specific outcome: the relative treatment effect for all pairwise comparisons, and a ranking of the treatments. It is important to consider the confidence with which these two types of results can enable clinicians, policy makers and patients to make informed decisions. We propose an approach to determining confidence in the output of a network meta-analysis. Our proposed approach is based on methodology developed by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group for pairwise meta-analyses. The suggested framework for evaluating a network meta-analysis acknowledges (i) the key role of indirect comparisons (ii) the contributions of each piece of direct evidence to the network meta-analysis estimates of effect size; (iii) the importance of the transitivity assumption to the validity of network meta-analysis; and (iv) the possibility of disagreement between direct evidence and indirect evidence. We apply our proposed strategy to a systematic review comparing topical antibiotics without steroids for chronically discharging ears with underlying eardrum perforations. The proposed framework can be used to determine confidence in the results from a network meta-analysis. Judgements about evidence from a network meta-analysis can be different from those made about evidence from pairwise meta-analyses. PMID:24992266

  16. Problematic gaming behaviour and health-related outcomes: A systematic review and meta-analysis.

    Science.gov (United States)

    Männikkö, Niko; Ruotsalainen, Heidi; Miettunen, Jouko; Pontes, Halley M; Kääriäinen, Maria

    2017-11-01

    This systematic review and meta-analysis aimed to investigate the interplay between problematic gaming behaviour and health-related outcomes at different developmental stages. A total of 50 empirical studies met the specified inclusion criteria, and a meta-analysis using correlation coefficients was used for the studies that reported adverse health implications regarding the impact of problematic gaming behaviour on depression, anxiety, obsessive-compulsive disorder and somatisation. Overall, the results suggested that problematic gaming behaviour is significantly associated with a wide range of detrimental health-related outcomes. Finally, the limitations of this review alongside its implications were discussed and considered for future research.

  17. Correlation between the model accuracy and model-based SOC estimation

    International Nuclear Information System (INIS)

    Wang, Qianqian; Wang, Jiao; Zhao, Pengju; Kang, Jianqiang; Yan, Few; Du, Changqing

    2017-01-01

    State-of-charge (SOC) estimation is a core technology for battery management systems. Considerable progress has been achieved in the study of SOC estimation algorithms, especially the algorithm on the basis of Kalman filter to meet the increasing demand of model-based battery management systems. The Kalman filter weakens the influence of white noise and initial error during SOC estimation but cannot eliminate the existing error of the battery model itself. As such, the accuracy of SOC estimation is directly related to the accuracy of the battery model. Thus far, the quantitative relationship between model accuracy and model-based SOC estimation remains unknown. This study summarizes three equivalent circuit lithium-ion battery models, namely, Thevenin, PNGV, and DP models. The model parameters are identified through hybrid pulse power characterization test. The three models are evaluated, and SOC estimation conducted by EKF-Ah method under three operating conditions are quantitatively studied. The regression and correlation of the standard deviation and normalized RMSE are studied and compared between the model error and the SOC estimation error. These parameters exhibit a strong linear relationship. Results indicate that the model accuracy affects the SOC estimation accuracy mainly in two ways: dispersion of the frequency distribution of the error and the overall level of the error. On the basis of the relationship between model error and SOC estimation error, our study provides a strategy for selecting a suitable cell model to meet the requirements of SOC precision using Kalman filter.

  18. Determining job satisfaction of nurses working in hospitals of Iran: A systematic review and meta-analysis.

    Science.gov (United States)

    Amiresmaili, Mohammadreza; Moosazadeh, Mahmood

    2013-09-01

    Employees feeling and attitude to their job has a significant role on their performance. Present study sought to investigate documents related to nurses job satisfaction, using systematic review and meta-analysis to estimate nurses job satisfaction in Iran. Papers on nurses job satisfaction were identified by searching different data bases using appropriate key words. Seventeen studies were extracted using inclusuion criteria. Data were analyzed using Meta-analysis command in STATA 11. Considerable hetrogenecity is apparent in results of nurses job satisfaction studies. Although, according to random effect model, nurses total job satisfaction was estimated at 46.3 (CI: 32.1-60.4), this was estimated at 51.9 (CI = 51.1-52.8) using fixed effect model. Additionally, a reverse relationship was observed between nurses overall job satisfaction and their age. Nurses' job satisfaction in Iran is at a good level compared with other countries. The more satisfied the nurses are with their working conditions, the less is their intention to leave their job. Dissatisfaction is associated with higher resignment and turnover, paying deep attention to efficient factors on nurses dissatisfaction and trying to overcome them is important to improve nurses' working conditions.

  19. A case study of discordant overlapping meta-analyses: vitamin d supplements and fracture.

    Directory of Open Access Journals (Sweden)

    Mark J Bolland

    Full Text Available BACKGROUND: Overlapping meta-analyses on the same topic are now very common, and discordant results often occur. To explore why discordant results arise, we examined a common topic for overlapping meta-analyses- vitamin D supplements and fracture. METHODS AND FINDINGS: We identified 24 meta-analyses of vitamin D (with or without calcium and fracture in a PubMed search in October 2013, and analysed a sample of 7 meta-analyses in the highest ranking general medicine journals. We used the AMSTAR tool to assess the quality of the meta-analyses, and compared their methodologies, analytic techniques and results. Applying the AMSTAR tool suggested the meta-analyses were generally of high quality. Despite this, there were important differences in trial selection, data extraction, and analytical methods that were only apparent after detailed assessment. 25 trials were included in at least one meta-analysis. Four meta-analyses included all eligible trials according to the stated inclusion and exclusion criteria, but the other 3 meta-analyses "missed" between 3 and 8 trials, and 2 meta-analyses included apparently ineligible trials. The relative risks used for individual trials differed between meta-analyses for total fracture in 10 of 15 trials, and for hip fracture in 6 of 12 trials, because of different outcome definitions and analytic approaches. The majority of differences (11/16 led to more favourable estimates of vitamin D efficacy compared to estimates derived from unadjusted intention-to-treat analyses using all randomised participants. The conclusions of the meta-analyses were discordant, ranging from strong statements that vitamin D prevents fractures to equally strong statements that vitamin D without calcium does not prevent fractures. CONCLUSIONS: Substantial differences in trial selection, outcome definition and analytic methods between overlapping meta-analyses led to discordant estimates of the efficacy of vitamin D for fracture prevention

  20. The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective.

    Science.gov (United States)

    Kruschke, John K; Liddell, Torrin M

    2018-02-01

    In the practice of data analysis, there is a conceptual distinction between hypothesis testing, on the one hand, and estimation with quantified uncertainty on the other. Among frequentists in psychology, a shift of emphasis from hypothesis testing to estimation has been dubbed "the New Statistics" (Cumming 2014). A second conceptual distinction is between frequentist methods and Bayesian methods. Our main goal in this article is to explain how Bayesian methods achieve the goals of the New Statistics better than frequentist methods. The article reviews frequentist and Bayesian approaches to hypothesis testing and to estimation with confidence or credible intervals. The article also describes Bayesian approaches to meta-analysis, randomized controlled trials, and power analysis.

  1. Modeling units of study from a pedagogical perspective: the pedagogical meta-model behind EML

    NARCIS (Netherlands)

    Koper, Rob

    2003-01-01

    This text is a short summary of the work on pedagogical analysis carried out when EML (Educational Modelling Language) was being developed. Because we address pedagogical meta-models the consequence is that I must justify the underlying pedagogical models it describes. I have included a (far from

  2. Marital status integration and suicide: A meta-analysis and meta-regression.

    Science.gov (United States)

    Kyung-Sook, Woo; SangSoo, Shin; Sangjin, Shin; Young-Jeon, Shin

    2018-01-01

    Marital status is an index of the phenomenon of social integration within social structures and has long been identified as an important predictor suicide. However, previous meta-analyses have focused only on a particular marital status, or not sufficiently explored moderators. A meta-analysis of observational studies was conducted to explore the relationships between marital status and suicide and to understand the important moderating factors in this association. Electronic databases were searched to identify studies conducted between January 1, 2000 and June 30, 2016. We performed a meta-analysis, subgroup analysis, and meta-regression of 170 suicide risk estimates from 36 publications. Using random effects model with adjustment for covariates, the study found that the suicide risk for non-married versus married was OR = 1.92 (95% CI: 1.75-2.12). The suicide risk was higher for non-married individuals aged analysis by gender, non-married men exhibited a greater risk of suicide than their married counterparts in all sub-analyses, but women aged 65 years or older showed no significant association between marital status and suicide. The suicide risk in divorced individuals was higher than for non-married individuals in both men and women. The meta-regression showed that gender, age, and sample size affected between-study variation. The results of the study indicated that non-married individuals have an aggregate higher suicide risk than married ones. In addition, gender and age were confirmed as important moderating factors in the relationship between marital status and suicide. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Meta-modeling soil organic carbon sequestration potential and its application at regional scale.

    Science.gov (United States)

    Luo, Zhongkui; Wang, Enli; Bryan, Brett A; King, Darran; Zhao, Gang; Pan, Xubin; Bende-Michl, Ulrike

    2013-03-01

    Upscaling the results from process-based soil-plant models to assess regional soil organic carbon (SOC) change and sequestration potential is a great challenge due to the lack of detailed spatial information, particularly soil properties. Meta-modeling can be used to simplify and summarize process-based models and significantly reduce the demand for input data and thus could be easily applied on regional scales. We used the pre-validated Agricultural Production Systems sIMulator (APSIM) to simulate the impact of climate, soil, and management on SOC at 613 reference sites across Australia's cereal-growing regions under a continuous wheat system. We then developed a simple meta-model to link the APSIM-modeled SOC change to primary drivers, i.e., the amount of recalcitrant SOC, plant available water capacity of soil, soil pH, and solar radiation, temperature, and rainfall in the growing season. Based on high-resolution soil texture data and 8165 climate data points across the study area, we used the meta-model to assess SOC sequestration potential and the uncertainty associated with the variability of soil characteristics. The meta-model explained 74% of the variation of final SOC content as simulated by APSIM. Applying the meta-model to Australia's cereal-growing regions reveals regional patterns in SOC, with higher SOC stock in cool, wet regions. Overall, the potential SOC stock ranged from 21.14 to 152.71 Mg/ha with a mean of 52.18 Mg/ha. Variation of soil properties induced uncertainty ranging from 12% to 117% with higher uncertainty in warm, wet regions. In general, soils in Australia's cereal-growing regions under continuous wheat production were simulated as a sink of atmospheric carbon dioxide with a mean sequestration potential of 8.17 Mg/ha.

  4. The structure of common emotion regulation strategies: A meta-analytic examination.

    Science.gov (United States)

    Naragon-Gainey, Kristin; McMahon, Tierney P; Chacko, Thomas P

    2017-04-01

    Emotion regulation has been examined extensively with regard to important outcomes, including psychological and physical health. However, the literature includes many different emotion regulation strategies but little examination of how they relate to one another, making it difficult to interpret and synthesize findings. The goal of this meta-analysis was to examine the underlying structure of common emotion regulation strategies (i.e., acceptance, behavioral avoidance, distraction, experiential avoidance, expressive suppression, mindfulness, problem solving, reappraisal, rumination, worry), and to evaluate this structure in light of theoretical models of emotion regulation. We also examined how distress tolerance-an important emotion regulation ability -relates to strategy use. We conducted meta-analyses estimating the correlations between emotion regulation strategies (based on 331 samples and 670 effect sizes), as well as between distress tolerance and strategies. The resulting meta-analytic correlation matrix was submitted to confirmatory and exploratory factor analyses. None of the confirmatory models, based on prior theory, was an acceptable fit to the data. Exploratory factor analysis suggested that 3 underlying factors best characterized these data. Two factors-labeled Disengagement and Aversive Cognitive Perseveration-emerged as strongly correlated but distinct factors, with the latter consisting of putatively maladaptive strategies. The third factor, Adaptive Engagement, was a less unified factor and weakly related to the other 2 factors. Distress tolerance was most closely associated with low levels of repetitive negative thought and experiential avoidance, and high levels of acceptance and mindfulness. We discuss the theoretical implications of these findings and applications to emotion regulation assessment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  5. A meta model-based methodology for an energy savings uncertainty assessment of building retrofitting

    Directory of Open Access Journals (Sweden)

    Caucheteux Antoine

    2016-01-01

    Full Text Available To reduce greenhouse gas emissions, energy retrofitting of building stock presents significant potential for energy savings. In the design stage, energy savings are usually assessed through Building Energy Simulation (BES. The main difficulty is to first assess the energy efficiency of the existing buildings, in other words, to calibrate the model. As calibration is an under determined problem, there is many solutions for building representation in simulation tools. In this paper, a method is proposed to assess not only energy savings but also their uncertainty. Meta models, using experimental designs, are used to identify many acceptable calibrations: sets of parameters that provide the most accurate representation of the building are retained to calculate energy savings. The method was applied on an existing office building modeled with the TRNsys BES. The meta model, using 13 parameters, is built with no more than 105 simulations. The evaluation of the meta model on thousands of new simulations gives a normalized mean bias error between the meta model and BES of <4%. Energy savings are assessed based on six energy savings concepts, which indicate savings of 2–45% with a standard deviation ranging between 1.3% and 2.5%.

  6. Consumption of Dairy Products in Relation to Changes in Anthropometric Variables in Adult Populations: A Systematic Review and Meta-Analysis of Cohort Studies.

    Directory of Open Access Journals (Sweden)

    Lukas Schwingshackl

    Full Text Available The current state of knowledge regarding the association of dairy products and weight gain, overweight, and obesity is based on studies reporting contradicting and inconclusive results. The aim of the present study was thus to clarify the link between dairy consumption in relation to changes in anthropometric measures/adiposity by a meta-analytical approach.For the meta-analysis PubMed, EMBASE, Web of Sciences, and google scholar were searched by two independent authors up to May 2016 with no restriction to language or calendar date. Prospective cohort studies reporting about intake of dairy consumption (including milk, yogurt, cheese, butter and changes in body weight or waist circumference, risk of overweight, obesity, or weight gain were eligible. Pooled effects were calculated using a random effects model, and also a fixed effect model for sensitivity analysis. Due to the heterogeneity of statistical analytical approaches of the studies the analysis were done separately for beta-coefficients of changes in body weight and/or waist circumference per serving of dairy, for differences in weight gain/gain in waist circumference when comparing extreme categories of dairy consumption, and for odds ratios in regard to weight gain, overweight/obesity, or abdominal obesity.24 studies (27 reports met the inclusion criteria for the systematic review, and 22 studies provided sufficient data for inclusion in the meta-analysis. The meta-analysis of the five studies on changes in body weight per serving of dairy no significant results could be found for whole fat dairy and low fat dairy. However, there was inverse association between changes in body weight for each serving's increase of yogurt (beta: -40.99 gram/year, 95% CI, -48.09 to -33.88, whereas each serving's increase of cheese was positively associated (beta: -10.97 gram/year, 95% CI, 2.86 to 19.07. Furthermore, the highest dairy intake category was associated with a reduced risk of abdominal

  7. Can trial sequential monitoring boundaries reduce spurious inferences from meta-analyses?

    DEFF Research Database (Denmark)

    Thorlund, Kristian; Devereaux, P J; Wetterslev, Jørn

    2008-01-01

    BACKGROUND: Results from apparently conclusive meta-analyses may be false. A limited number of events from a few small trials and the associated random error may be under-recognized sources of spurious findings. The information size (IS, i.e. number of participants) required for a reliable......-analyses after each included trial and evaluated their results using a conventional statistical criterion (alpha = 0.05) and two-sided Lan-DeMets monitoring boundaries. We examined the proportion of false positive results and important inaccuracies in estimates of treatment effects that resulted from the two...... approaches. RESULTS: Using the random-effects model and final data, 12 of the meta-analyses yielded P > alpha = 0.05, and 21 yielded P alpha = 0.05. The monitoring boundaries eliminated all false positives. Important inaccuracies in estimates were observed in 6 out of 21 meta-analyses using the conventional...

  8. A meta-analysis of the price elasticity of gasoline demand. A SUR approach

    Energy Technology Data Exchange (ETDEWEB)

    Brons, Martijn; Rietveld, Piet [Department of Spatial Economics, Vrije Universiteit, De Boelelaan 1105, 1081 HV Amsterdam (Netherlands); Tinbergen Institute Amsterdam (TIA), Roetersstraat 31, 1018 WB Amsterdam (Netherlands); Nijkamp, Peter [Department of Spatial Economics, Vrije Universiteit, De Boelelaan 1105, 1081 HV Amsterdam (Netherlands); Tinbergen Institute Amsterdam (TIA), Roetersstraat 31, 1018 WB Amsterdam (Netherlands); The Netherlands Organisation of Scientific Research (NWO), postbus 93138 - 2509 AC Den Haag (Netherlands); Pels, Eric [Department of Spatial Economics, Vrije Universiteit, De Boelelaan 1105, 1081 HV Amsterdam (Netherlands)

    2008-09-15

    Automobile gasoline demand can be expressed as a multiplicative function of fuel efficiency, mileage per car and car ownership. This implies a linear relationship between the price elasticity of total fuel demand and the price elasticities of fuel efficiency, mileage per car and car ownership. In this meta-analytical study we aim to investigate and explain the variation in empirical estimates of the price elasticity of gasoline demand. A methodological novelty is that we use the linear relationship between the elasticities to develop a meta-analytical estimation approach based on a Seemingly Unrelated Regression (SUR) model with Cross Equation Restrictions. This approach enables us to combine observations of different elasticities and thus increase our sample size. Furthermore, it allows for a more detailed interpretation of our meta-regression results. The empirical results of the study demonstrate that the SUR approach leads to more precise results (i.e., lower standard errors) than a standard meta-analytical approach. We find that, with mean short run and long run price elasticities of - 0.34 and - 0.84, respectively, the demand for gasoline is not very price sensitive. Both in the short and the long run, the impact of a change in the gasoline price on demand is mainly driven by responses in fuel efficiency and mileage per car and to a slightly lesser degree by changes in car ownership. Furthermore, we find that study characteristics relating to the geographic area studied, the year of the study, the type of data used, the time horizon and the functional specification of the demand equation have a significant impact on the estimated value of the price elasticity of gasoline demand. (author)

  9. A meta-analysis of the price elasticity of gasoline demand. A SUR approach

    International Nuclear Information System (INIS)

    Brons, Martijn; Rietveld, Piet; Nijkamp, Peter; Pels, Eric

    2008-01-01

    Automobile gasoline demand can be expressed as a multiplicative function of fuel efficiency, mileage per car and car ownership. This implies a linear relationship between the price elasticity of total fuel demand and the price elasticities of fuel efficiency, mileage per car and car ownership. In this meta-analytical study we aim to investigate and explain the variation in empirical estimates of the price elasticity of gasoline demand. A methodological novelty is that we use the linear relationship between the elasticities to develop a meta-analytical estimation approach based on a Seemingly Unrelated Regression (SUR) model with Cross Equation Restrictions. This approach enables us to combine observations of different elasticities and thus increase our sample size. Furthermore, it allows for a more detailed interpretation of our meta-regression results. The empirical results of the study demonstrate that the SUR approach leads to more precise results (i.e., lower standard errors) than a standard meta-analytical approach. We find that, with mean short run and long run price elasticities of - 0.34 and - 0.84, respectively, the demand for gasoline is not very price sensitive. Both in the short and the long run, the impact of a change in the gasoline price on demand is mainly driven by responses in fuel efficiency and mileage per car and to a slightly lesser degree by changes in car ownership. Furthermore, we find that study characteristics relating to the geographic area studied, the year of the study, the type of data used, the time horizon and the functional specification of the demand equation have a significant impact on the estimated value of the price elasticity of gasoline demand. (author)

  10. Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: meta-epidemiological study

    DEFF Research Database (Denmark)

    Wood, L.; Egger, M.; Gluud, L.L.

    2008-01-01

    OBJECTIVE: To examine whether the association of inadequate or unclear allocation concealment and lack of blinding with biased estimates of intervention effects varies with the nature of the intervention or outcome. DESIGN: Combined analysis of data from three meta-epidemiological studies based o...

  11. Estimated effect of alcohol pricing policies on health and health economic outcomes in England: an epidemiological model.

    Science.gov (United States)

    Purshouse, Robin C; Meier, Petra S; Brennan, Alan; Taylor, Karl B; Rafia, Rachid

    2010-04-17

    Although pricing policies for alcohol are known to be effective, little is known about how specific interventions affect health-care costs and health-related quality-of-life outcomes for different types of drinkers. We assessed effects of alcohol pricing and promotion policy options in various population subgroups. We built an epidemiological mathematical model to appraise 18 pricing policies, with English data from the Expenditure and Food Survey and the General Household Survey for average and peak alcohol consumption. We used results from econometric analyses (256 own-price and cross-price elasticity estimates) to estimate effects of policies on alcohol consumption. We applied risk functions from systemic reviews and meta-analyses, or derived from attributable fractions, to model the effect of consumption changes on mortality and disease prevalence for 47 illnesses. General price increases were effective for reduction of consumption, health-care costs, and health-related quality of life losses in all population subgroups. Minimum pricing policies can maintain this level of effectiveness for harmful drinkers while reducing effects on consumer spending for moderate drinkers. Total bans of supermarket and off-license discounting are effective but banning only large discounts has little effect. Young adult drinkers aged 18-24 years are especially affected by policies that raise prices in pubs and bars. Minimum pricing policies and discounting restrictions might warrant further consideration because both strategies are estimated to reduce alcohol consumption, and related health harms and costs, with drinker spending increases targeting those who incur most harm. Policy Research Programme, UK Department of Health. Copyright 2010 Elsevier Ltd. All rights reserved.

  12. Empirical Comparison of Publication Bias Tests in Meta-Analysis.

    Science.gov (United States)

    Lin, Lifeng; Chu, Haitao; Murad, Mohammad Hassan; Hong, Chuan; Qu, Zhiyong; Cole, Stephen R; Chen, Yong

    2018-04-16

    Decision makers rely on meta-analytic estimates to trade off benefits and harms. Publication bias impairs the validity and generalizability of such estimates. The performance of various statistical tests for publication bias has been largely compared using simulation studies and has not been systematically evaluated in empirical data. This study compares seven commonly used publication bias tests (i.e., Begg's rank test, trim-and-fill, Egger's, Tang's, Macaskill's, Deeks', and Peters' regression tests) based on 28,655 meta-analyses available in the Cochrane Library. Egger's regression test detected publication bias more frequently than other tests (15.7% in meta-analyses of binary outcomes and 13.5% in meta-analyses of non-binary outcomes). The proportion of statistically significant publication bias tests was greater for larger meta-analyses, especially for Begg's rank test and the trim-and-fill method. The agreement among Tang's, Macaskill's, Deeks', and Peters' regression tests for binary outcomes was moderately strong (most κ's were around 0.6). Tang's and Deeks' tests had fairly similar performance (κ > 0.9). The agreement among Begg's rank test, the trim-and-fill method, and Egger's regression test was weak or moderate (κ < 0.5). Given the relatively low agreement between many publication bias tests, meta-analysts should not rely on a single test and may apply multiple tests with various assumptions. Non-statistical approaches to evaluating publication bias (e.g., searching clinical trials registries, records of drug approving agencies, and scientific conference proceedings) remain essential.

  13. Meta-modeling of occupancy variables and analysis of their impact on energy outcomes of office buildings

    International Nuclear Information System (INIS)

    Wang, Qinpeng; Augenbroe, Godfried; Kim, Ji-Hyun; Gu, Li

    2016-01-01

    Highlights: • A meta-analysis framework for a stochastic characterization of occupancy variables. • Sensitivity ranking of occupancy variability against all other sources of uncertainty. • Sensitivity of occupant presence for building energy consumption is low. • Accurate mean knowledge is sufficient for predicting building energy consumption. • Prediction of peak demand behavior requires stochastic occupancy modeling. - Abstract: Occupants interact with buildings in various ways via their presence (passive effects) and control actions (active effects). Therefore, understanding the influence of occupants is essential if we are to evaluate the performance of a building. In this paper, we model the mean profiles and variability of occupancy variables (presence and actions) separately. We will use a multi-variate Gaussian distribution to generate mean profiles of occupancy variables, while the variability will be represented by a multi-dimensional time series model, within a framework for a meta-analysis that synthesizes occupancy data gathered from a pool of buildings. We then discuss variants of occupancy models with respect to various outcomes of interest such as HVAC energy consumption and peak demand behavior via a sensitivity analysis. Results show that our approach is able to generate stochastic occupancy profiles, requiring minimum additional input from the energy modeler other than standard diversity profiles. Along with the meta-analysis, we enable the generalization of previous research results and statistical inferences to choose occupancy variables for future buildings. The sensitivity analysis shows that for aggregated building energy consumption, occupant presence has a smaller impact compared to lighting and appliance usage. Specifically, being accumulatively 55% wrong with regard to presence, only translates to 2% error in aggregated cooling energy in July and 3.6% error in heating energy in January. Such a finding redirects focus to the

  14. Occupational Noise Exposure and the Risk for Work-Related Injury: A Systematic Review and Meta-analysis.

    Science.gov (United States)

    Dzhambov, Angel; Dimitrova, Donka

    2017-11-10

    Occupational noise exposure has been linked to work-related injuries. Strategies to control occupational hazards often rely on dose-response relationships needed to inform policy, but quantitative synthesis of the relevant literature has not been done so far. This study aimed to systematically review the epidemiological literature and to perform meta-analysis of the risk for work-related injury due to occupational noise exposure. PRISMA and MOOSE guidelines were followed. PubMed, ScienceDirect, and Google Scholar were searched up until 15 December 2016 in English, Russian, and Spanish. Reference lists, grey literature, and expert archives were searched as well. The risk of bias was assessed for each study and incorporated into the meta-analysis weights using the quality effects model. Overall, 21 studies were included at the qualitative review stage: 9 cross-sectional, 6 case-control, 4 cohort, 1 case-crossover, and 1 ecological. Noise exposure was assessed objectively in 13 studies. Information on occupational injuries was elicited from medical records/registry in 13 studies. Meta-analyses showed RR = 1.22 (95% CI: 1.15, 1.29) (n = 59028) per 5 dB increase in noise exposure (Cochran's Q = 27.26, P 90-95 dB) compared with the least exposed group (Cochran's Q = 180.46, P work-related injury risk. However, the quality of evidence is 'very low'; therefore, the magnitude of this association should be interpreted with caution. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

  15. Regional variation in the prevalence of E. coli O157 in cattle: a meta-analysis and meta-regression.

    Science.gov (United States)

    Islam, Md Zohorul; Musekiwa, Alfred; Islam, Kamrul; Ahmed, Shahana; Chowdhury, Sharmin; Ahad, Abdul; Biswas, Paritosh Kumar

    2014-01-01

    Escherichia coli O157 (EcO157) infection has been recognized as an important global public health concern. But information on the prevalence of EcO157 in cattle at the global and at the wider geographical levels is limited, if not absent. This is the first meta-analysis to investigate the point prevalence of EcO157 in cattle at the global level and to explore the factors contributing to variation in prevalence estimates. Seven electronic databases- CAB Abstracts, PubMed, Biosis Citation Index, Medline, Web of Knowledge, Scirus and Scopus were searched for relevant publications from 1980 to 2012. A random effect meta-analysis model was used to produce the pooled estimates. The potential sources of between study heterogeneity were identified using meta-regression. A total of 140 studies consisting 220,427 cattle were included in the meta-analysis. The prevalence estimate of EcO157 in cattle at the global level was 5.68% (95% CI, 5.16-6.20). The random effects pooled prevalence estimates in Africa, Northern America, Oceania, Europe, Asia and Latin America-Caribbean were 31.20% (95% CI, 12.35-50.04), 7.35% (95% CI, 6.44-8.26), 6.85% (95% CI, 2.41-11.29), 5.15% (95% CI, 4.21-6.09), 4.69% (95% CI, 3.05-6.33) and 1.65% (95% CI, 0.77-2.53), respectively. Between studies heterogeneity was evidenced in most regions. World region (p<0.001), type of cattle (p<0.001) and to some extent, specimens (p = 0.074) as well as method of pre-enrichment (p = 0.110), were identified as factors for variation in the prevalence estimates of EcO157 in cattle. The prevalence of the organism seems to be higher in the African and Northern American regions. The important factors that might have influence in the estimates of EcO157 are type of cattle and kind of screening specimen. Their roles need to be determined and they should be properly handled in any survey to estimate the true prevalence of EcO157.

  16. Evaluation of Simulation Models that Estimate the Effect of Dietary Strategies on Nutritional Intake: A Systematic Review.

    Science.gov (United States)

    Grieger, Jessica A; Johnson, Brittany J; Wycherley, Thomas P; Golley, Rebecca K

    2017-05-01

    Background: Dietary simulation modeling can predict dietary strategies that may improve nutritional or health outcomes. Objectives: The study aims were to undertake a systematic review of simulation studies that model dietary strategies aiming to improve nutritional intake, body weight, and related chronic disease, and to assess the methodologic and reporting quality of these models. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guided the search strategy with studies located through electronic searches [Cochrane Library, Ovid (MEDLINE and Embase), EBSCOhost (CINAHL), and Scopus]. Study findings were described and dietary modeling methodology and reporting quality were critiqued by using a set of quality criteria adapted for dietary modeling from general modeling guidelines. Results: Forty-five studies were included and categorized as modeling moderation, substitution, reformulation, or promotion dietary strategies. Moderation and reformulation strategies targeted individual nutrients or foods to theoretically improve one particular nutrient or health outcome, estimating small to modest improvements. Substituting unhealthy foods with healthier choices was estimated to be effective across a range of nutrients, including an estimated reduction in intake of saturated fatty acids, sodium, and added sugar. Promotion of fruits and vegetables predicted marginal changes in intake. Overall, the quality of the studies was moderate to high, with certain features of the quality criteria consistently reported. Conclusions: Based on the results of reviewed simulation dietary modeling studies, targeting a variety of foods rather than individual foods or nutrients theoretically appears most effective in estimating improvements in nutritional intake, particularly reducing intake of nutrients commonly consumed in excess. A combination of strategies could theoretically be used to deliver the best improvement in outcomes. Study quality was moderate to

  17. Introducing Meta-models for a More Efficient Hazard Mitigation Strategy with Rockfall Protection Barriers

    Science.gov (United States)

    Toe, David; Mentani, Alessio; Govoni, Laura; Bourrier, Franck; Gottardi, Guido; Lambert, Stéphane

    2018-04-01

    The paper presents a new approach to assess the effecctiveness of rockfall protection barriers, accounting for the wide variety of impact conditions observed on natural sites. This approach makes use of meta-models, considering a widely used rockfall barrier type and was developed from on FE simulation results. Six input parameters relevant to the block impact conditions have been considered. Two meta-models were developed concerning the barrier capability either of stopping the block or in reducing its kinetic energy. The outcome of the parameters range on the meta-model accuracy has been also investigated. The results of the study reveal that the meta-models are effective in reproducing with accuracy the response of the barrier to any impact conditions, providing a formidable tool to support the design of these structures. Furthermore, allowing to accommodate the effects of the impact conditions on the prediction of the block-barrier interaction, the approach can be successfully used in combination with rockfall trajectory simulation tools to improve rockfall quantitative hazard assessment and optimise rockfall mitigation strategies.

  18. Estimation of silver in Ag-meta kaolinite by neutron activation

    International Nuclear Information System (INIS)

    Daniels, E.A.; Rao, S.M.

    1981-01-01

    The present work is based on the neutron activation of Ag-meta kaolinite for the determination of its silver content from the β-activity of the compound using standard tables which showed the percentage of silver in mixtures of silver nitrate and meta kaolinite of known composition against β-activity of the mixture activated under identical conditions. (author)

  19. Taking Seriously Ingroup Self-Evaluation, Meta-Prejudice, and Prejudice in Analyzing Interreligious Relations.

    Science.gov (United States)

    Putra, Idhamsyah Eka

    2016-07-18

    The present study aims to understand the conditions where prejudice can be predicted by ingroup and outgroup meta-prejudice. The data collecting was disseminated toward Muslim and Christian participants (N = 362) living in Maumere, Flores Island, Indonesia. In Flores, Christianity is the largest religion and Islam is the second. Across two samples, the effects of ingroup and outgroup meta-prejudice on prejudice were found to be moderated by ingroup self-evaluation. It shows that at high level (but not low) of positive ingroup self-evaluation, ingroup and outgroup meta-prejudice were found to predict prejudice. The results suggest that it is important to consider how group members evaluate their own group and how group members think what others are thinking, in the study pertaining to intergroup relations.

  20. Maximum likelihood estimation and EM algorithm of Copas-like selection model for publication bias correction.

    Science.gov (United States)

    Ning, Jing; Chen, Yong; Piao, Jin

    2017-07-01

    Publication bias occurs when the published research results are systematically unrepresentative of the population of studies that have been conducted, and is a potential threat to meaningful meta-analysis. The Copas selection model provides a flexible framework for correcting estimates and offers considerable insight into the publication bias. However, maximizing the observed likelihood under the Copas selection model is challenging because the observed data contain very little information on the latent variable. In this article, we study a Copas-like selection model and propose an expectation-maximization (EM) algorithm for estimation based on the full likelihood. Empirical simulation studies show that the EM algorithm and its associated inferential procedure performs well and avoids the non-convergence problem when maximizing the observed likelihood. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. The association between maternal smoking and placenta abruption: a meta-analysis.

    Science.gov (United States)

    Shobeiri, Fatemeh; Masoumi, Seyedeh Zahra; Jenabi, Ensiyeh

    2017-08-01

    Several epidemiological studies have determined that maternal smoking can increase the risk of placenta abruption. To date, only a meta-analysis has been performed for assessing the relationship between smoking and placenta abruption. This meta-analysis was conducted to estimate the association between smoking and the risk of placenta abruption. A literature search was conducted in major databases such as PubMed, Web of Science, and Scopus from the earliest possible year to April 2016. The heterogeneity across studies was explored by Q-test and I 2 statistic. The publication bias was assessed using Begg's and Egger's tests. The results were reported using odds ratio (OR) estimate with its 95% confidence intervals (CI) using a random effects model. The literature search yielded 1167 publications until April 2016 with 4 309 610 participants. Based on OR estimates obtained from case-control and cohort studies, there was a significant association between smoking and placenta abruption (1.80; 95% CI: 1.75, 1.85). Based on the results of cohort studies, smoking and placenta abruption had a significant association (relative risk ratio: 1.65; 95% CI: 1.51, 1.80). Based on reports in epidemiological studies, we showed that smoking is a risk factor for placenta abruption.

  2. Estimation of environment-related properties of chemicals for design of sustainable processes: development of group-contribution+ (GC+) property models and uncertainty analysis.

    Science.gov (United States)

    Hukkerikar, Amol Shivajirao; Kalakul, Sawitree; Sarup, Bent; Young, Douglas M; Sin, Gürkan; Gani, Rafiqul

    2012-11-26

    The aim of this work is to develop group-contribution(+) (GC(+)) method (combined group-contribution (GC) method and atom connectivity index (CI) method) based property models to provide reliable estimations of environment-related properties of organic chemicals together with uncertainties of estimated property values. For this purpose, a systematic methodology for property modeling and uncertainty analysis is used. The methodology includes a parameter estimation step to determine parameters of property models and an uncertainty analysis step to establish statistical information about the quality of parameter estimation, such as the parameter covariance, the standard errors in predicted properties, and the confidence intervals. For parameter estimation, large data sets of experimentally measured property values of a wide range of chemicals (hydrocarbons, oxygenated chemicals, nitrogenated chemicals, poly functional chemicals, etc.) taken from the database of the US Environmental Protection Agency (EPA) and from the database of USEtox is used. For property modeling and uncertainty analysis, the Marrero and Gani GC method and atom connectivity index method have been considered. In total, 22 environment-related properties, which include the fathead minnow 96-h LC(50), Daphnia magna 48-h LC(50), oral rat LD(50), aqueous solubility, bioconcentration factor, permissible exposure limit (OSHA-TWA), photochemical oxidation potential, global warming potential, ozone depletion potential, acidification potential, emission to urban air (carcinogenic and noncarcinogenic), emission to continental rural air (carcinogenic and noncarcinogenic), emission to continental fresh water (carcinogenic and noncarcinogenic), emission to continental seawater (carcinogenic and noncarcinogenic), emission to continental natural soil (carcinogenic and noncarcinogenic), and emission to continental agricultural soil (carcinogenic and noncarcinogenic) have been modeled and analyzed. The application

  3. Estimating the relative utility of screening mammography.

    Science.gov (United States)

    Abbey, Craig K; Eckstein, Miguel P; Boone, John M

    2013-05-01

    The concept of diagnostic utility is a fundamental component of signal detection theory, going back to some of its earliest works. Attaching utility values to the various possible outcomes of a diagnostic test should, in principle, lead to meaningful approaches to evaluating and comparing such systems. However, in many areas of medical imaging, utility is not used because it is presumed to be unknown. In this work, we estimate relative utility (the utility benefit of a detection relative to that of a correct rejection) for screening mammography using its known relation to the slope of a receiver operating characteristic (ROC) curve at the optimal operating point. The approach assumes that the clinical operating point is optimal for the goal of maximizing expected utility and therefore the slope at this point implies a value of relative utility for the diagnostic task, for known disease prevalence. We examine utility estimation in the context of screening mammography using the Digital Mammographic Imaging Screening Trials (DMIST) data. We show how various conditions can influence the estimated relative utility, including characteristics of the rating scale, verification time, probability model, and scope of the ROC curve fit. Relative utility estimates range from 66 to 227. We argue for one particular set of conditions that results in a relative utility estimate of 162 (±14%). This is broadly consistent with values in screening mammography determined previously by other means. At the disease prevalence found in the DMIST study (0.59% at 365-day verification), optimal ROC slopes are near unity, suggesting that utility-based assessments of screening mammography will be similar to those found using Youden's index.

  4. Risk of herpes zoster and family history: A Meta-analysis of case–control studies

    Directory of Open Access Journals (Sweden)

    Yi Chun Lai

    2016-01-01

    Full Text Available Background: Herpes zoster (HZ results from the reactivation of latent varicella zoster virus (VZV residing in dorsal root and cranial nerve ganglia. Advanced age and dysfunctional cell-mediated immune responses are well-established risk factors for VZV reactivation. There have been recent interests in whether there is an increased risk of the disease associated with a positive family history. Aims and Objectives: We aimed to conduct a meta-analysis to evaluate the association between HZ infection and family history. In addition, we investigated the dose-response relationship between HZ infection and the number of relatives with a history of HZ. Materials and Methods: Observational studies were searched from MEDLINE, EMBASE, and Cochrane Central Register from inception to April 15, 2015. The Meta-analysis of Observational Studies in Epidemiology guidelines were followed in conducting this study. To estimate the pooled odds ratio, random-effects model of DerSimonian and Laird was used. Heterogeneity between studies was assessed using the I2 statistic. A dose-response meta-analysis with studies that reported appropriate data were done using the generalized least squares for trend method. Results: Five studies, yielding a total of 4169 subjects, were identified for meta-analysis. Cases with HZ were 3.03 (95% confidence interval [CI]: 1.86–4.94, P < 0.001 and 3.27 (95% CI: 1.75–6.10, P < 0.001 times more likely to report the first-degree relatives and total relatives with a history of HZ, respectively. A significant positive dose-response relationship between the risk of HZ infection and the number of relatives with a history of HZ was also demonstrated (P < 0.001. Conclusions: This meta-analysis demonstrated that family history is a significant risk factor for HZ infection. This risk has a dose-response relationship with the number of relatives with a history of HZ.

  5. Parameter Estimation for Thurstone Choice Models

    Energy Technology Data Exchange (ETDEWEB)

    Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-04-24

    We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.

  6. Multivariate meta-analysis: a robust approach based on the theory of U-statistic.

    Science.gov (United States)

    Ma, Yan; Mazumdar, Madhu

    2011-10-30

    Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.

  7. Meta-Analysis of Effect Sizes Reported at Multiple Time Points Using General Linear Mixed Model

    Science.gov (United States)

    Musekiwa, Alfred; Manda, Samuel O. M.; Mwambi, Henry G.; Chen, Ding-Geng

    2016-01-01

    Meta-analysis of longitudinal studies combines effect sizes measured at pre-determined time points. The most common approach involves performing separate univariate meta-analyses at individual time points. This simplistic approach ignores dependence between longitudinal effect sizes, which might result in less precise parameter estimates. In this paper, we show how to conduct a meta-analysis of longitudinal effect sizes where we contrast different covariance structures for dependence between effect sizes, both within and between studies. We propose new combinations of covariance structures for the dependence between effect size and utilize a practical example involving meta-analysis of 17 trials comparing postoperative treatments for a type of cancer, where survival is measured at 6, 12, 18 and 24 months post randomization. Although the results from this particular data set show the benefit of accounting for within-study serial correlation between effect sizes, simulations are required to confirm these results. PMID:27798661

  8. Health care: necessity or luxury good? A meta-regression analysis

    OpenAIRE

    Iordache, Ioana Raluca

    2014-01-01

    When estimating the influence income per capita exerts on health care expenditure, the research in the field offers mixed results. Studies employ different data, estimation techniques and models, which brings about the question whether these differences in research design play any part in explaining the heterogeneity of reported outcomes. By employing meta-regression analysis, the present paper analyzes 220 estimates of health spending income elasticity collected from 54 studies and finds tha...

  9. Prevalence of retinopathy of prematurity in Iran: asystematic review and Meta-analysis

    Directory of Open Access Journals (Sweden)

    Saman Maroufizadeh

    2017-08-01

    Full Text Available AIM: To estimate overall prevalence of retinopathy of prematurity (ROP in Iran using a systematic review and Meta-analysis. METHODS: A systematic review and Meta-analysis was performed of all published studies pertaining to prevalence of ROP using international and national electronic databases (ISI Web of Sciences, PubMed, Scopus, Google Scholar, SID, MagIran, and IranMedex from their inception until May 2016 with standard keywords. Begg and Egger tests were used to examine the publication bias and Cochran test and I2 statistics were used to evaluate the statistical heterogeneity. Pooled estimate of the prevalence of ROP were calculated using random effects Meta-analysis. RESULTS: The publication bias assumption was rejected by Egger tests with P-value equal to 0.024. The results of Cochran test and I2 statistics revealed substantial heterogeneity (Q=1099.02, df=25, I2=97.7%, P=0.001. The overall prevalence of ROP using the random effect model in Iran was 26.1% (95% CI: 20.3%-31.8%. CONCLUSION: The prevalence of ROP is relatively high in Iran. Low birth weight and gestational age are significant risk factors for the disease. Improved care, including oxygen delivery and monitoring, for preterm babies in all facility settings would reduce the number of babies affected with ROP.

  10. Meta-analysis on the efficacy of foot-and-mouth disease emergency vaccination

    DEFF Research Database (Denmark)

    Hisham Beshara Halasa, Tariq; Boklund, Anette; Cox, S.

    2012-01-01

    The objectives of this study were to provide a summary quantification of the efficacy of FMD emergency vaccination based on a systematic review and a meta-analysis of available literature, and to further discuss the suitability of this review and meta-analysis to summarize and further interpret...... of clinical signs including FMD lesions and fever, while the virological protection parameter was estimated based on the outcome of laboratory tests that were used to diagnose FMD infection. A meta-analysis relative risk was calculated per protection parameter. Results of the meta-analyses were examined using...... vaccine. Fortunately, no significant bias that would alter the conclusions was encountered in the analysis. Meta-analysis showed to be a useful tool to summarize literature results from a systematic review of the efficacy of foot and mouth disease emergency vaccination....

  11. Exposure to organochlorine pollutants and type 2 diabetes: a systematic review and meta-analysis.

    Directory of Open Access Journals (Sweden)

    Mengling Tang

    Full Text Available OBJECTIVE: Though exposure to organochlorine pollutants (OCPs is considered a risk factor for type 2 diabetes (T2DM, epidemiological evidence for the association remains controversial. A systematic review and meta-analysis was applied to quantitatively evaluate the association between exposure to OCPs and incidence of T2DM and pool the inconsistent evidence. DESIGN AND METHODS: Publications in English were searched in MEDLINE and WEB OF SCIENCE databases and related reference lists up to August 2013. Quantitative estimates and information regarding study characteristics were extracted from 23 original studies. Quality assessments of external validity, bias, exposure measurement and confounding were performed, and subgroup analyses were conducted to examine the heterogeneity sources. RESULTS: We retrieved 23 eligible articles to conduct this meta-analysis. OR (odds ratio or RR (risk ratio estimates in each subgroup were discussed, and the strong associations were observed in PCB-153 (OR, 1.52; 95% CI, 1.19-1.94, PCBs (OR, 2.14; 95% CI, 1.53-2.99, and p,p'-DDE (OR, 1.33; 95% CI, 1.15-1.54 based on a random-effects model. CONCLUSIONS: This meta-analysis provides quantitative evidence supporting the conclusion that exposure to organochlorine pollutants is associated with an increased risk of incidence of T2DM.

  12. Advances in the GRADE approach to rate the certainty in estimates from a network meta-analysis.

    Science.gov (United States)

    Brignardello-Petersen, Romina; Bonner, Ashley; Alexander, Paul E; Siemieniuk, Reed A; Furukawa, Toshi A; Rochwerg, Bram; Hazlewood, Glen S; Alhazzani, Waleed; Mustafa, Reem A; Murad, M Hassan; Puhan, Milo A; Schünemann, Holger J; Guyatt, Gordon H

    2018-01-01

    This article describes conceptual advances of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group guidance to evaluate the certainty of evidence (confidence in evidence, quality of evidence) from network meta-analysis (NMA). Application of the original GRADE guidance, published in 2014, in a number of NMAs has resulted in advances that strengthen its conceptual basis and make the process more efficient. This guidance will be useful for systematic review authors who aim to assess the certainty of all pairwise comparisons from an NMA and who are familiar with the basic concepts of NMA and the traditional GRADE approach for pairwise meta-analysis. Two principles of the original GRADE NMA guidance are that we need to rate the certainty of the evidence for each pairwise comparison within a network separately and that in doing so we need to consider both the direct and indirect evidence. We present, discuss, and illustrate four conceptual advances: (1) consideration of imprecision is not necessary when rating the direct and indirect estimates to inform the rating of NMA estimates, (2) there is no need to rate the indirect evidence when the certainty of the direct evidence is high and the contribution of the direct evidence to the network estimate is at least as great as that of the indirect evidence, (3) we should not trust a statistical test of global incoherence of the network to assess incoherence at the pairwise comparison level, and (4) in the presence of incoherence between direct and indirect evidence, the certainty of the evidence of each estimate can help decide which estimate to believe. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Estimating internal exposure risks by the relative risk and the National Institute of Health risk models

    International Nuclear Information System (INIS)

    Mehta, S.K.; Sarangapani, R.

    1995-01-01

    This paper presents tabulations of risk (R) and person-years of life lost (PYLL) for acute exposures of individual organs at ages 20 and 40 yrs for the Indian and Japanese populations to illustrate the effect of age at exposure in the two models. Results are also presented for the organ wise nominal probability coefficients (NPC) and PYLL for individual organs for the age distributed Indian population by the two models. The results presented show that for all organs the estimates of PYLL and NPC for the Indian population are lower than those for the Japanese population by both models except for oesophagus, breast and ovary by the relative risk (RR) model, where the opposite trend is observed. The results also show that the Indian all-cancer values of NPC averaged over the two models is 2.9 x 10 -2 Sv -1 , significantly lower than the world average value of 5x10 -2 Sv -1 estimated by the ICRP. (author). 9 refs., 2 figs., 2 tabs

  14. Multivariate meta-analysis: modelling the heterogeneity mixing apples and oranges; dangerous or delicious?

    NARCIS (Netherlands)

    L.R. Arends (Lidia)

    2006-01-01

    textabstractMeta-analysis may be broadly defined as the quantitative review and synthesis of the results of related but independent studies. For the simple case where meta-analysis concerns only one outcome measure in each study, the statistical methods are well established now. However, in many

  15. Methodology for the Model-based Small Area Estimates of Cancer-Related Knowledge - Small Area Estimates

    Science.gov (United States)

    The HINTS is designed to produce reliable estimates at the national and regional levels. GIS maps using HINTS data have been used to provide a visual representation of possible geographic relationships in HINTS cancer-related variables.

  16. Speech perception in autism spectrum disorder: An activation likelihood estimation meta-analysis.

    Science.gov (United States)

    Tryfon, Ana; Foster, Nicholas E V; Sharda, Megha; Hyde, Krista L

    2018-02-15

    Autism spectrum disorder (ASD) is often characterized by atypical language profiles and auditory and speech processing. These can contribute to aberrant language and social communication skills in ASD. The study of the neural basis of speech perception in ASD can serve as a potential neurobiological marker of ASD early on, but mixed results across studies renders it difficult to find a reliable neural characterization of speech processing in ASD. To this aim, the present study examined the functional neural basis of speech perception in ASD versus typical development (TD) using an activation likelihood estimation (ALE) meta-analysis of 18 qualifying studies. The present study included separate analyses for TD and ASD, which allowed us to examine patterns of within-group brain activation as well as both common and distinct patterns of brain activation across the ASD and TD groups. Overall, ASD and TD showed mostly common brain activation of speech processing in bilateral superior temporal gyrus (STG) and left inferior frontal gyrus (IFG). However, the results revealed trends for some distinct activation in the TD group showing additional activation in higher-order brain areas including left superior frontal gyrus (SFG), left medial frontal gyrus (MFG), and right IFG. These results provide a more reliable neural characterization of speech processing in ASD relative to previous single neuroimaging studies and motivate future work to investigate how these brain signatures relate to behavioral measures of speech processing in ASD. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Association between interleukin 1 receptor antagonist gene 86-bp VNTR polymorphism and sepsis: a meta-analysis.

    Science.gov (United States)

    Fang, Fang; Pan, Jian; Li, Yiping; Xu, Lixiao; Su, Guanghao; Li, Gang; Wang, Jian

    2015-01-01

    Many studies have focused on the relationship between interleukin 1 receptor antagonist (IL1RN) gene 86-bp VNTR polymorphism and sepsis, but the results remain inconsistent. Thus, a meta-analysis was carried out to derive a more precise estimation of the association between IL1RN 86-bp VNTR polymorphism and risk of sepsis and sepsis-related mortality. Relevant publications were searched in several widely used databases and six eligible studies were included in the meta-analysis. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the strength of the association between IL1RN 86-bp VNTR polymorphism and risk of sepsis and sepsis-related mortality. Significant associations between IL1RN 86-bp VNTR polymorphism and sepsis risk were observed in both overall meta-analysis for L2 versus 22 (OR=0.75, 95% CI=0.59-0.94) and severe sepsis subgroup for LL+L2 versus 22 (OR=0.67, 95% CI=0.47-0.93). L stands for long alleles containing three to six repeats; 2 stands for short allele containing two repeats. However, no significant sepsis mortality variation was detected for all genetic models. According to the results of our meta-analysis, the IL1RN 86-bp VNTR polymorphism probably associates with sepsis risk but not with sepsis-related mortality. Copyright © 2014. Published by Elsevier Inc.

  18. Milestones of mathematical model for business process management related to cost estimate documentation in petroleum industry

    Science.gov (United States)

    Khamidullin, R. I.

    2018-05-01

    The paper is devoted to milestones of the optimal mathematical model for a business process related to cost estimate documentation compiled during construction and reconstruction of oil and gas facilities. It describes the study and analysis of fundamental issues in petroleum industry, which are caused by economic instability and deterioration of a business strategy. Business process management is presented as business process modeling aimed at the improvement of the studied business process, namely main criteria of optimization and recommendations for the improvement of the above-mentioned business model.

  19. LBLOCA sensitivity analysis using meta models

    International Nuclear Information System (INIS)

    Villamizar, M.; Sanchez-Saez, F.; Villanueva, J.F.; Carlos, S.; Sanchez, A.I.; Martorell, S.

    2014-01-01

    This paper presents an approach to perform the sensitivity analysis of the results of simulation of thermal hydraulic codes within a BEPU approach. Sensitivity analysis is based on the computation of Sobol' indices that makes use of a meta model, It presents also an application to a Large-Break Loss of Coolant Accident, LBLOCA, in the cold leg of a pressurized water reactor, PWR, addressing the results of the BEMUSE program and using the thermal-hydraulic code TRACE. (authors)

  20. NASA Software Cost Estimation Model: An Analogy Based Estimation Model

    Science.gov (United States)

    Hihn, Jairus; Juster, Leora; Menzies, Tim; Mathew, George; Johnson, James

    2015-01-01

    The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K-­ nearest neighbor prediction model performance on the same data set.

  1. Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

    Science.gov (United States)

    Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

    2016-01-15

    When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

  2. Sensitivity analysis for publication bias in meta-analysis of diagnostic studies for a continuous biomarker.

    Science.gov (United States)

    Hattori, Satoshi; Zhou, Xiao-Hua

    2018-02-10

    Publication bias is one of the most important issues in meta-analysis. For standard meta-analyses to examine intervention effects, the funnel plot and the trim-and-fill method are simple and widely used techniques for assessing and adjusting for the influence of publication bias, respectively. However, their use may be subjective and can then produce misleading insights. To make a more objective inference for publication bias, various sensitivity analysis methods have been proposed, including the Copas selection model. For meta-analysis of diagnostic studies evaluating a continuous biomarker, the summary receiver operating characteristic (sROC) curve is a very useful method in the presence of heterogeneous cutoff values. To our best knowledge, no methods are available for evaluation of influence of publication bias on estimation of the sROC curve. In this paper, we introduce a Copas-type selection model for meta-analysis of diagnostic studies and propose a sensitivity analysis method for publication bias. Our method enables us to assess the influence of publication bias on the estimation of the sROC curve and then judge whether the result of the meta-analysis is sufficiently confident or should be interpreted with much caution. We illustrate our proposed method with real data. Copyright © 2017 John Wiley & Sons, Ltd.

  3. Induced abortion rate in Iran: a meta-analysis.

    Science.gov (United States)

    Motaghi, Zahra; Poorolajal, Jalal; Keramat, Afsaneh; Shariati, Mohammad; Yunesian, Masud; Masoumi, Seyyedeh Zahra

    2013-10-01

    About 44 million induced abortions take place worldwide annually, of which 50% are unsafe. The results of studies investigated the induced abortion rate in Iran are inconsistent. The aim of this meta-analysis was to estimate the incidence rate of induced abortion in Iran. National and international electronic databases, as well as conference databases until July 2012 were searched. Reference lists of articles were screened and the studies' authors were contacted for additional unpublished studies. Cross-sectional studies addressing induced abortion in Iran were included in this meta-analysis. The primary outcome of interest was the induced abortion rate (the number of abortions per 1000 women aged 15-44 years in a year) or the ratio (the number of abortions per 100 live births in a year). The secondary outcome of interest was the prevalence of unintended pregnancies (the number of mistimed, unplanned, or unwanted pregnancies per total pregnancies). Data were analyzed using random effect models. Of 603 retrieved studies, using search strategy, 10 studies involving 102,394 participants were eventually included in the meta-analysis. The induced abortion rate and ratio were estimated as 8.9 per 1000 women aged 15-44 years (95% CI: 5.46, 12.33) and 5.34 per 100 live births (95% CI: 3.61, 7.07), respectively. The prevalence of unintended pregnancy was estimated as 27.94 per 100 pregnant women (95% CI: 23.46, 32.42). The results of this meta-analysis helped a better understanding of the incidence of induced abortion in Iran compared to the other developing countries in Asia. However, additional sources of data on abortion other than medical records and survey studies are needed to estimate the true rate of unsafe abortion in Iran.

  4. Childhood autism spectrum disorders and exposure to nitrogen dioxide, and particulate matter air pollution: A review and meta-analysis.

    Science.gov (United States)

    Flores-Pajot, Marie-Claire; Ofner, Marianna; Do, Minh T; Lavigne, Eric; Villeneuve, Paul J

    2016-11-01

    Genetic and environmental factors have been recognized to play an important role in autism. The possibility that exposure to outdoor air pollution increases the risk of autism spectrum disorder (ASD) has been an emerging area of research. Herein, we present a systematic review, and meta-analysis of published epidemiological studies that have investigated these associations. We undertook a comprehensive search strategy to identify studies that investigated outdoor air pollution and autism in children. Overall, seven cohorts and five case-control studies met our inclusion criteria for the meta-analysis. We summarized the associations between exposure to air pollution and ASD based on the following critical exposure windows: (i) first, second and third trimester of pregnancy, (ii) entire pregnancy, and (iii) postnatal period. Random effects meta-analysis modeling was undertaken to derive pooled risk estimates for these exposures across the studies. The meta-estimates for the change in ASD associated with a 10μg/m 3 increase in exposure in PM 2.5 and 10 ppb increase in NO 2 during pregnancy were 1.34 (95% CI:0.83, 2.17) and 1.05 (95% CI:0.99, 1.11), respectively. Stronger associations were observed for exposures received after birth, but these estimates were unstable as they were based on only two studies. O 3 exposure was weakly associated with ASD during the third trimester of pregnancy and during the entire pregnancy, however, these estimates were also based on only two studies. Our meta-analysis support the hypothesis that exposure to ambient air pollution is associated with an increased risk of autism. Our findings should be interpreted cautiously due to relatively small number of studies, and several studies were unable to control for other key risk factors. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Appraisal of emotions in media use: Towards a process model of meta-emotion and emotion regulation

    NARCIS (Netherlands)

    Bartsch, A.; Vorderer, P.A.; Mangold, R.; Viehoff, R.

    2008-01-01

    Over the past 20 years, research on meta-emotion and related concepts such as meta-mood and need for affect has become fruitful and prominent across a variety of disciplines, including media psychology. This paper reviews the literature on meta-emotion and considers problems regarding the definition

  6. Effect size calculation in meta-analyses of psychotherapy outcome research.

    Science.gov (United States)

    Hoyt, William T; Del Re, A C

    2018-05-01

    Meta-analysis of psychotherapy intervention research normally examines differences between treatment groups and some form of comparison group (e.g., wait list control; alternative treatment group). The effect of treatment is normally quantified as a standardized mean difference (SMD). We describe procedures for computing unbiased estimates of the population SMD from sample data (e.g., group Ms and SDs), and provide guidance about a number of complications that may arise related to effect size computation. These complications include (a) incomplete data in research reports; (b) use of baseline data in computing SMDs and estimating the population standard deviation (σ); (c) combining effect size data from studies using different research designs; and (d) appropriate techniques for analysis of data from studies providing multiple estimates of the effect of interest (i.e., dependent effect sizes). Clinical or Methodological Significance of this article: Meta-analysis is a set of techniques for producing valid summaries of existing research. The initial computational step for meta-analyses of research on intervention outcomes involves computing an effect size quantifying the change attributable to the intervention. We discuss common issues in the computation of effect sizes and provide recommended procedures to address them.

  7. Estimating small area health-related characteristics of populations: a methodological review

    Directory of Open Access Journals (Sweden)

    Azizur Rahman

    2017-05-01

    Full Text Available Estimation of health-related characteristics at a fine local geographic level is vital for effective health promotion programmes, provision of better health services and population-specific health planning and management. Lack of a micro-dataset readily available for attributes of individuals at small areas negatively impacts the ability of local and national agencies to manage serious health issues and related risks in the community. A solution to this challenge would be to develop a method that simulates reliable small-area statistics. This paper provides a significant appraisal of the methodologies for estimating health-related characteristics of populations at geographical limited areas. Findings reveal that a range of methodologies are in use, which can be classified as three distinct set of approaches: i indirect standardisation and individual level modelling; ii multilevel statistical modelling; and iii micro-simulation modelling. Although each approach has its own strengths and weaknesses, it appears that microsimulation- based spatial models have significant robustness over the other methods and also represent a more precise means of estimating health-related population characteristics over small areas.

  8. An overview of meta-analysis for clinicians

    Science.gov (United States)

    Lee, Young Ho

    2018-01-01

    The number of medical studies being published is increasing exponentially, and clinicians must routinely process large amounts of new information. Moreover, the results of individual studies are often insufficient to provide confident answers, as their results are not consistently reproducible. A meta-analysis is a statistical method for combining the results of different studies on the same topic and it may resolve conflicts among studies. Meta-analysis is being used increasingly and plays an important role in medical research. This review introduces the basic concepts, steps, advantages, and caveats of meta-analysis, to help clinicians understand it in clinical practice and research. A major advantage of a meta-analysis is that it produces a precise estimate of the effect size, with considerably increased statistical power, which is important when the power of the primary study is limited because of a small sample size. A meta-analysis may yield conclusive results when individual studies are inconclusive. Furthermore, meta-analyses investigate the source of variation and different effects among subgroups. In summary, a meta-analysis is an objective, quantitative method that provides less biased estimates on a specific topic. Understanding how to conduct a meta-analysis aids clinicians in the process of making clinical decisions. PMID:29277096

  9. An overview of meta-analysis for clinicians.

    Science.gov (United States)

    Lee, Young Ho

    2018-03-01

    The number of medical studies being published is increasing exponentially, and clinicians must routinely process large amounts of new information. Moreover, the results of individual studies are often insufficient to provide confident answers, as their results are not consistently reproducible. A meta-analysis is a statistical method for combining the results of different studies on the same topic and it may resolve conflicts among studies. Meta-analysis is being used increasingly and plays an important role in medical research. This review introduces the basic concepts, steps, advantages, and caveats of meta-analysis, to help clinicians understand it in clinical practice and research. A major advantage of a meta-analysis is that it produces a precise estimate of the effect size, with considerably increased statistical power, which is important when the power of the primary study is limited because of a small sample size. A meta-analysis may yield conclusive results when individual studies are inconclusive. Furthermore, meta-analyses investigate the source of variation and different effects among subgroups. In summary, a meta-analysis is an objective, quantitative method that provides less biased estimates on a specific topic. Understanding how to conduct a meta-analysis aids clinicians in the process of making clinical decisions.

  10. Systematic review and meta-analysis in cardiac surgery: a primer.

    Science.gov (United States)

    Yanagawa, Bobby; Tam, Derrick Y; Mazine, Amine; Tricco, Andrea C

    2018-03-01

    The purpose of this article is to review the strengths and weaknesses of systematic reviews and meta-analyses to inform our current understanding of cardiac surgery. A systematic review and meta-analysis of a focused topic can provide a quantitative estimate for the effect of a treatment intervention or exposure. In cardiac surgery, observational studies and small, single-center prospective trials provide most of the clinical outcomes that form the evidence base for patient management and guideline recommendations. As such, meta-analyses can be particularly valuable in synthesizing the literature for a particular focused surgical question. Since the year 2000, there are over 800 meta-analysis-related publications in our field. There are some limitations to this technique, including clinical, methodological and statistical heterogeneity, among other challenges. Despite these caveats, results of meta-analyses have been useful in forming treatment recommendations or in providing guidance in the design of future clinical trials. There is a growing number of meta-analyses in the field of cardiac surgery. Knowledge translation via meta-analyses will continue to guide and inform cardiac surgical practice and our practice guidelines.

  11. MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments

    Directory of Open Access Journals (Sweden)

    Charcosset Alain

    2007-02-01

    Full Text Available Abstract Background Integration of multiple results from Quantitative Trait Loci (QTL studies is a key point to understand the genetic determinism of complex traits. Up to now many efforts have been made by public database developers to facilitate the storage, compilation and visualization of multiple QTL mapping experiment results. However, studying the congruency between these results still remains a complex task. Presently, the few computational and statistical frameworks to do so are mainly based on empirical methods (e.g. consensus genetic maps are generally built by iterative projection. Results In this article, we present a new computational and statistical package, called MetaQTL, for carrying out whole-genome meta-analysis of QTL mapping experiments. Contrary to existing methods, MetaQTL offers a complete statistical process to establish a consensus model for both the marker and the QTL positions on the whole genome. First, MetaQTL implements a new statistical approach to merge multiple distinct genetic maps into a single consensus map which is optimal in terms of weighted least squares and can be used to investigate recombination rate heterogeneity between studies. Secondly, assuming that QTL can be projected on the consensus map, MetaQTL offers a new clustering approach based on a Gaussian mixture model to decide how many QTL underly the distribution of the observed QTL. Conclusion We demonstrate using simulations that the usual model choice criteria from mixture model literature perform relatively well in this context. As expected, simulations also show that this new clustering algorithm leads to a reduction in the length of the confidence interval of QTL location provided that across studies there are enough observed QTL for each underlying true QTL location. The usefulness of our approach is illustrated on published QTL detection results of flowering time in maize. Finally, MetaQTL is freely available at http://bioinformatics.org/mqtl.

  12. A Systematic Review and Meta-analysis of Childhood Health Utilities.

    Science.gov (United States)

    Kwon, Joseph; Kim, Sung Wook; Ungar, Wendy J; Tsiplova, Kate; Madan, Jason; Petrou, Stavros

    2018-04-01

    A common feature of most reviews or catalogues of health utilities has been their focus on adult health states or derivation of values from adult populations. More generally, utility measurement in or on behalf of children has been constrained by several methodological concerns. The objective of this study was to conduct the first comprehensive systematic review and meta-analysis of primary utility data for childhood conditions and descriptors, and to determine the effects of methodological factors on childhood utilities. The review followed PRISMA guidelines. PubMed, Embase, Web of Science, PsycINFO, EconLit, CINAHL and Cochrane Library were searched for primary studies reporting health utilities for childhood conditions or descriptors using direct or indirect valuation methods. The Paediatric Economic Database Evaluation (PEDE) Porject was also searched for cost-utility analyses with primary utility values. Mean or median utilities for each of the main samples were catalogued, and weighted averages of utilities for each health condition were estimated, by valuation method. Mixed-effects meta-regression using hierarchical linear modeling was conducted for the most common valuation methods to estimate the utility decrement for each health condition category relative to general childhood population health, as well as the independent effects of methodological factors. The literature searches resulted in 272 eligible studies. These yielded 3,414 utilities when all sub-groups were considered, covering all ICD-10 chapters relevant to childhood health, 19 valuation methods, 12 respondent types, 8 modes of administration, and data from 36 countries. A total of 1,191 utility values were obtained when only main study samples were considered, and these were catalogued by health condition or descriptor, and methodological characteristics. 1,073 mean utilities for main samples were used for fixed-effects meta-analysis by health condition and valuation method. Mixed

  13. Lower cognitive function in patients with age-related macular degeneration: a meta-analysis

    Science.gov (United States)

    Zhou, Li-Xiao; Sun, Cheng-Lin; Wei, Li-Juan; Gu, Zhi-Min; Lv, Liang; Dang, Yalong

    2016-01-01

    Objective To investigate the cognitive impairment in patients with age-related macular degeneration (AMD). Methods Relevant articles were identified through a search of the following electronic databases through October 2015, without language restriction: 1) PubMed; 2) the Cochrane Library; 3) EMBASE; 4) ScienceDirect. Meta-analysis was conducted using STATA 12.0 software. Standardized mean differences with corresponding 95% confidence intervals were calculated. All of the included studies met the following four criteria: 1) the study design was a case–control or randomized controlled trial (RCT) study; 2) the study investigated cognitive function in the patient with AMD; 3) the diagnoses of AMD must be provided; 4) there were sufficient scores data to extract for evaluating cognitive function between cases and controls. The Newcastle–Ottawa Scale criteria were used to assess the methodological quality of the studies. Results Of the initial 278 literatures, only six case–control and one RCT studies met all of the inclusion criteria. A total of 794 AMD patients and 1,227 controls were included in this study. Five studies were performed with mini-mental state examination (MMSE), two studies with animal fluency, two studies with trail making test (TMT)-A and -B, one study with Mini-Cog. Results of the meta-analysis revealed lower cognitive function test scores in patients with AMD, especially with MMSE and Mini-Cog test (P≤0.001 for all). The results also showed that differences in the TMT-A (except AMD [total] vs controls) and TMT-B test had no statistical significance (P>0.01). The Newcastle–Ottawa Scale score was ≥5 for all of the included studies. Based on the sensitivity analysis, no single study influenced the overall pooled estimates. Conclusion This meta-analysis suggests lower cognitive function test scores in patients with AMD, especially with MMSE and Mini-Cog test. The other cognitive impairment screening tests, such as animal fluency test and

  14. Meta-analysis for genome-wide association studies using case-control design: application and practice.

    Science.gov (United States)

    Shim, Sungryul; Kim, Jiyoung; Jung, Wonguen; Shin, In-Soo; Bae, Jong-Myon

    2016-01-01

    This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy-Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The 'genhwcci' and 'metan' commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the 'metareg' command of STATA should be conducted to evaluate related factors of heterogeneities.

  15. APPLYING TEACHING-LEARNING TO ARTIFICIAL BEE COLONY FOR PARAMETER OPTIMIZATION OF SOFTWARE EFFORT ESTIMATION MODEL

    Directory of Open Access Journals (Sweden)

    THANH TUNG KHUAT

    2017-05-01

    Full Text Available Artificial Bee Colony inspired by the foraging behaviour of honey bees is a novel meta-heuristic optimization algorithm in the community of swarm intelligence algorithms. Nevertheless, it is still insufficient in the speed of convergence and the quality of solutions. This paper proposes an approach in order to tackle these downsides by combining the positive aspects of TeachingLearning based optimization and Artificial Bee Colony. The performance of the proposed method is assessed on the software effort estimation problem, which is the complex and important issue in the project management. Software developers often carry out the software estimation in the early stages of the software development life cycle to derive the required cost and schedule for a project. There are a large number of methods for effort estimation in which COCOMO II is one of the most widely used models. However, this model has some restricts because its parameters have not been optimized yet. In this work, therefore, we will present the approach to overcome this limitation of COCOMO II model. The experiments have been conducted on NASA software project dataset and the obtained results indicated that the improvement of parameters provided better estimation capabilities compared to the original COCOMO II model.

  16. Prognostic factors for return to work after depression-related work disability: A systematic review and meta-analysis.

    Science.gov (United States)

    Ervasti, Jenni; Joensuu, Matti; Pentti, Jaana; Oksanen, Tuula; Ahola, Kirsi; Vahtera, Jussi; Kivimäki, Mika; Virtanen, Marianna

    2017-12-01

    Knowledge about factors influencing return to work (RTW) after depression-related absence is highly relevant, but the evidence is scattered. We performed a systematic search of PubMed and Embase databases up to February 1, 2016 to retrieve cohort studies on the association between various predictive factors and return to work among employees with depression for review and meta-analysis. We also analyzed unpublished data from the Finnish Public Sector study. Most-adjusted estimates were pooled using fixed effects meta-analysis. Eleven published studies fulfilled the eligibility criteria, representing 22 358 person-observations from five different countries. With the additional unpublished data from the 14 101 person-observations from the Finnish Public Sector study, the total number of person-observations was 36 459. The pooled estimates were derived from 2 to 5 studies, with the number of observations ranging from 260 to 26 348. Older age (pooled relative risk [RR] 0.95; 95% confidence interval [CI] 0.84-0.87), somatic comorbidity (RR = 0.80, 95% CI 0.77-0.83), psychiatric comorbidity (RR = 0.86, 95% CI 0.83-0.88) and more severe depression (RR = 0.96, 95% CI 0.94-0.98) were associated with a lower rate of return to work, and personality trait conscientiousness with higher (RR = 1.06, 95% CI 1.02-1.10) return to work. While older age and clinical factors predicted slower return, significant heterogeneity was observed between the studies. There is a dearth of observational studies on the predictors of RTW after depression. Future research should pay attention to quality aspects and particularly focus on the role of workplace and labor market factors as well as individual and clinical characteristics on RTW. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Judgments in the selection of path generation techniques: a meta-analytic approach

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo

    2012-01-01

    objective judgments for effective route choice set generation. Initially, path generation techniques are implemented within a synthetic network to generate possible subjective choice sets considered by travelers. Next, “true model estimates” and “postulated predicted routes” are assumed from the simulation...... of a route choice model. Then, objective choice sets are applied for model estimation and results are compared to the “true model estimates”. Last, predictions from the simulation of models estimated with objective choice sets are compared to the “postulated predicted routes”. Meta-analysis allows...

  18. Parameter Estimation of Nonlinear Models in Forestry.

    OpenAIRE

    Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.

    1999-01-01

    Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...

  19. Data analysis with the DIANA meta-scheduling approach

    International Nuclear Information System (INIS)

    Anjum, A; McClatchey, R; Willers, I

    2008-01-01

    The concepts, design and evaluation of the Data Intensive and Network Aware (DIANA) meta-scheduling approach for solving the challenges of data analysis being faced by CERN experiments are discussed in this paper. Our results suggest that data analysis can be made robust by employing fault tolerant and decentralized meta-scheduling algorithms supported in our DIANA meta-scheduler. The DIANA meta-scheduler supports data intensive bulk scheduling, is network aware and follows a policy centric meta-scheduling. In this paper, we demonstrate that a decentralized and dynamic meta-scheduling approach is an effective strategy to cope with increasing numbers of users, jobs and datasets. We present 'quality of service' related statistics for physics analysis through the application of a policy centric fair-share scheduling model. The DIANA meta-schedulers create a peer-to-peer hierarchy of schedulers to accomplish resource management that changes with evolving loads and is dynamic and adapts to the volatile nature of the resources

  20. Data Sources for the Model-based Small Area Estimates of Cancer-Related Knowledge - Small Area Estimates

    Science.gov (United States)

    The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).

  1. Aggregate meta-models for evolutionary multiobjective and many-objective optimization

    Czech Academy of Sciences Publication Activity Database

    Pilát, Martin; Neruda, Roman

    Roč. 116, 20 September (2013), s. 392-402 ISSN 0925-2312 R&D Projects: GA ČR GAP202/11/1368 Institutional support: RVO:67985807 Keywords : evolutionary algorithms * multiobjective optimization * many-objective optimization * surrogate models * meta-models * memetic algorithm Subject RIV: IN - Informatics, Computer Science Impact factor: 2.005, year: 2013

  2. Statistical Power in Meta-Analysis

    Science.gov (United States)

    Liu, Jin

    2015-01-01

    Statistical power is important in a meta-analysis study, although few studies have examined the performance of simulated power in meta-analysis. The purpose of this study is to inform researchers about statistical power estimation on two sample mean difference test under different situations: (1) the discrepancy between the analytical power and…

  3. Estimating the incidence of breast cancer in Africa: a systematic review and meta-analysis

    Science.gov (United States)

    Adeloye, Davies; Sowunmi, Olaperi Y.; Jacobs, Wura; David, Rotimi A; Adeosun, Adeyemi A; Amuta, Ann O.; Misra, Sanjay; Gadanya, Muktar; Auta, Asa; Harhay, Michael O; Chan, Kit Yee

    2018-01-01

    Background Breast cancer is estimated to be the most common cancer worldwide. We sought to assemble publicly available data from Africa to provide estimates of the incidence of breast cancer on the continent. Methods A systematic search of Medline, EMBASE, Global Health and African Journals Online (AJOL) was conducted. We included population- or hospital-based registry studies on breast cancer conducted in Africa, and providing estimates of the crude incidence of breast cancer among women. A random effects meta-analysis was employed to determine the pooled incidence of breast cancer across studies. Results The literature search returned 4648 records, with 41 studies conducted across 54 study sites in 22 African countries selected. We observed important variations in reported cancer incidence between population- and hospital-based cancer registries. The overall pooled crude incidence of breast cancer from population-based registries was 24.5 per 100 000 person years (95% confidence interval (CI) 20.1-28.9). The incidence in North Africa was higher at 29.3 per 100 000 (95% CI 20.0-38.7) than Sub-Saharan Africa (SSA) at 22.4 per 100 000 (95% CI 17.2-28.0). In hospital-based registries, the overall pooled crude incidence rate was estimated at 23.6 per 100 000 (95% CI 18.5-28.7). SSA and Northern Africa had relatively comparable rates at 24.0 per 100 000 (95% CI 17.5-30.4) and 23.2 per 100 000 (95% CI 6.6-39.7), respectively. Across both registries, incidence rates increased considerably between 2000 and 2015. Conclusions The available evidence suggests a growing incidence of breast cancer in Africa. The representativeness of these estimates is uncertain due to the paucity of data in several countries and calendar years, as well as inconsistency in data collation and quality across existing cancer registries. PMID:29740502

  4. Migraine Headache and Ischemic Stroke Risk: An Updated Meta-analysis

    Science.gov (United States)

    Spector, June T.; Kahn, Susan R.; Jones, Miranda R.; Jayakumar, Monisha; Dalal, Deepan; Nazarian, Saman

    2010-01-01

    Background Observational studies, including recent large cohort studies which were unavailable for prior meta-analysis, have suggested an association between migraine headache and ischemic stroke. We performed an updated meta-analysis to quantitatively summarize the strength of association between migraine and ischemic stroke risk. Methods We systematically searched electronic databases, including MEDLINE and EMBASE, through February 2009 for studies of human subjects in the English language. Study selection using a priori selection criteria, data extraction, and assessment of study quality were conducted independently by reviewer pairs using standardized forms. Results Twenty-one (60%) of 35 studies met the selection criteria, for a total of 622,381 participants (13 case-control, 8 cohort studies) included in the meta-analysis. The pooled adjusted odds ratio of ischemic stroke comparing migraineurs to non-migraineurs using a random effects model was 2.30 (95% confidence interval [CI], 1.91-2.76). The pooled adjusted effect estimates for studies that reported relative risks and hazard ratios, respectively, were 2.41 (95% CI, 1.81-3.20) and 1.52 (95% CI, 0.99-2.35). The overall pooled effect estimate was 2.04 (95% CI, 1.72-2.43). Results were robust to sensitivity analyses excluding lower quality studies. Conclusions Migraine is associated with increased ischemic stroke risk. These findings underscore the importance of identifying high-risk migraineurs with other modifiable stroke risk factors. Future studies of the effect of migraine treatment and modifiable risk factor reduction on stroke risk in migraineurs are warranted. PMID:20493462

  5. Meta-analysis for heritability estimates of vegetative and reproductive traits of Coffea arabica L.Meta-análise para estimativas de herdabilidade de caracteres vegetativos e reprodutivos de Coffea arabica L.

    Directory of Open Access Journals (Sweden)

    Danielle Pereira Baliza

    2012-08-01

    Full Text Available The compilation of informations resulting from independent studies has been difficulted in almost all scientific fields, mainly due to the great number of scientific papers published in recent years. As a result, summarizing information became a need. In this context, a meta-analysis was conducted with the objective of summarizing the estimates for the heritability for vegetative and reproductive traits of coffee (Coffea arabica L.. Heritability estimates were appraised regarding the following traits: average height of plant, average diameter of the canopy, vegetative vigor, production of processed coffee, yield and rust. The data regarding the heritability estimates are from scientific articles published in national and international journals, congress annals, PhD thesis and Master dissertations. The technique of meta-analysis summarized the estimates heritability from different studies and made possible to conclude that all of the appraised traits are highly inherited, reflecting the great genetic variety of coffee plants, and that is possible to reach satisfactory genetic gains in improvement programs in which those traits are evaluated. A compilação de informações advindas de estudos independentes tem sido dificultada em quase todos os campos da ciência, devido principalmente, ao grande número de trabalhos científicos publicados nos últimos anos. Assim, sumarizar informações tornou-se uma necessidade. Neste contexto, uma meta-análise foi conduzida com o objetivo de sistematizar as estimativas para a herdabilidade de caracteres vegetativos e reprodutivos de cafeeiros (Coffea arabica L.. Foram avaliadas as estimativas de herdabilidade referentes aos seguintes caracteres: altura média da planta, diâmetro médio da copa, vigor vegetativo, produção de café beneficiado, rendimento e resistência a ferrugem. Os dados referentes às estimativas de herdabilidade são provenientes de artigos científicos publicados em revistas

  6. A meta-analysis of changes in brain activity in clinical depression

    Directory of Open Access Journals (Sweden)

    Susan Mary Palmer

    2015-01-01

    Full Text Available Insights into neurobiological mechanisms of depression are increasingly being sought via brain imaging studies. Our aim was to quantitatively summarize overlap and divergence in regions of altered brain activation associated with depression under emotionally-valenced compared to cognitively-demanding task conditions, with reference to intrinsic functional connectivity. We hypothesized differences reflective of task demands. A coordinate-based meta-analysis technique, Activation Likelihood Estimation (ALE, was used to analyze relevant imaging literature. These studies compared brain activity in depressed adults relative to healthy controls during three conditions: (i emotionally-valenced (cognitively easy tasks (n=29; (ii cognitively-demanding tasks (n=15; and (iii resting conditions (n=21.The meta-analyses identified 5, 8 and 7 significant clusters of altered brain activity under emotion, cognition and resting conditions respectively in depressed individuals compared to healthy controls. Regions of overlap and divergence between pairs of the three separate meta-analyses were quantified. There were no significant regions of overlap between emotion and cognition meta-analyses, but several divergent clusters were found. Cognitively-demanding conditions were associated with greater activation of right medial frontal and insula regions while bilateral amygdala was more significantly altered during emotion (cognitively-undemanding conditions; consistent with task demands.Overlap was present in left amygdala and right subcallosal cingulate between emotion and resting meta-analyses, with no significant divergence.Our meta-analyses highlight alteration of common brain regions, during cognitively-undemanding emotional tasks and resting conditions but divergence of regions between emotional and cognitively-demanding tasks. Regions altered reflect current biological and system-level models of depression and highlight the relationship with task condition and

  7. Design-related bias in estimates of accuracy when comparing imaging tests: examples from breast imaging research

    International Nuclear Information System (INIS)

    Houssami, Nehmat; Ciatto, Stefano

    2010-01-01

    This work highlights concepts on the potential for design-related factors to bias estimates of test accuracy in comparative imaging research. We chose two design factors, selection of eligible subjects and the reference standard, to examine the effect of design limitations on estimates of accuracy. Estimates of sensitivity in a study of the comparative accuracy of mammography and ultrasound differed according to how subjects were selected. Comparison of a new imaging test with an existing test should distinguish whether the new test is to be used as a replacement for, or as an adjunct to, the conventional test, to guide the method for subject selection. Quality of the reference standard, examined in a meta-analysis of preoperative breast MRI, varied across studies and was associated with estimates of incremental accuracy. Potential solutions to deal with the reference standard are outlined where an ideal reference standard may not be available in all subjects. These examples of breast imaging research demonstrate that design-related bias, when comparing a new imaging test with a conventional imaging test, may bias accuracy in a direction that favours the new test by overestimating the accuracy of the new test or by underestimating that of the conventional test. (orig.)

  8. Estimating terrestrial aboveground biomass estimation using lidar remote sensing: a meta-analysis

    Science.gov (United States)

    Zolkos, S. G.; Goetz, S. J.; Dubayah, R.

    2012-12-01

    Estimating biomass of terrestrial vegetation is a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD). The accuracy of biomass estimates is important in the context carbon markets emerging under REDD, since areas with more accurate estimates command higher prices, but also for characterizing uncertainty in estimates of carbon cycling and the global carbon budget. There is particular interest in mapping biomass so that carbon stocks and stock changes can be monitored consistently across a range of scales - from relatively small projects (tens of hectares) to national or continental scales - but also so that other benefits of forest conservation can be factored into decision making (e.g. biodiversity and habitat corridors). We conducted an analysis of reported biomass accuracy estimates from more than 60 refereed articles using different remote sensing platforms (aircraft and satellite) and sensor types (optical, radar, lidar), with a particular focus on lidar since those papers reported the greatest efficacy (lowest errors) when used in the a synergistic manner with other coincident multi-sensor measurements. We show systematic differences in accuracy between different types of lidar systems flown on different platforms but, perhaps more importantly, differences between forest types (biomes) and plot sizes used for field calibration and assessment. We discuss these findings in relation to monitoring, reporting and verification under REDD, and also in the context of more systematic assessment of factors that influence accuracy and error estimation.

  9. Content analysis of advertisements related to oral health in children: a systematic review and meta-analysis.

    Science.gov (United States)

    Pournaghi Azar, F; Mamizadeh, M; Nikniaz, Z; Ghojazadeh, M; Hajebrahimi, S; Salehnia, F; Mashhadi Abdolahi, H

    2018-03-01

    The evidence about the content of TV advertisements broadcast during children's viewing times with an emphasis on the number of food advertisements and the number of cariogenic food advertisements was systematically reviewed and meta-analyzed. A systematic review and meta-analysis. Articles published up until October 2017 in PubMed, Scopus, Embase, Web of Science, Cochrane Library, and Persian databases such as Magiran, IranDoc, and Iranmedex with the keywords that were related to advertising and oral health in children were searched and screened by two reviewers independently, and the outcomes of interest were extracted. Meta-analysis was performed using the Comprehensive Meta-Analysis, version 2.0. A total of 480 titles were retrieved and reduced to 256 eligible studies after deletion of duplicates, and finally, after closer assessment of titles and abstracts, five articles were selected for systematic review and meta-analysis. Of the included studies, three were conducted in the UK, one in India, and one in Greece. About 38.0% (95% confidence interval: 19.6-60.6, P = 0.296) of advertisements were related to food and also about 70.6% (95% confidence interval: 53.7-83.3, P < 0.019) of food advertisements were related to cariogenic foods. Food advertising during children's programs is dominated by food items that are potentially harmful to oral health. Moreover, the advertisements shifted toward food items that appeared healthy but contain a large amount of hidden sugar. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  10. The semiotics of control and modeling relations in complex systems.

    Science.gov (United States)

    Joslyn, C

    2001-01-01

    We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.

  11. Diagnostics for generalized linear hierarchical models in network meta-analysis.

    Science.gov (United States)

    Zhao, Hong; Hodges, James S; Carlin, Bradley P

    2017-09-01

    Network meta-analysis (NMA) combines direct and indirect evidence comparing more than 2 treatments. Inconsistency arises when these 2 information sources differ. Previous work focuses on inconsistency detection, but little has been done on how to proceed after identifying inconsistency. The key issue is whether inconsistency changes an NMA's substantive conclusions. In this paper, we examine such discrepancies from a diagnostic point of view. Our methods seek to detect influential and outlying observations in NMA at a trial-by-arm level. These observations may have a large effect on the parameter estimates in NMA, or they may deviate markedly from other observations. We develop formal diagnostics for a Bayesian hierarchical model to check the effect of deleting any observation. Diagnostics are specified for generalized linear hierarchical NMA models and investigated for both published and simulated datasets. Results from our example dataset using either contrast- or arm-based models and from the simulated datasets indicate that the sources of inconsistency in NMA tend not to be influential, though results from the example dataset suggest that they are likely to be outliers. This mimics a familiar result from linear model theory, in which outliers with low leverage are not influential. Future extensions include incorporating baseline covariates and individual-level patient data. Copyright © 2017 John Wiley & Sons, Ltd.

  12. Updated Value of Service Reliability Estimates for Electric Utility Customers in the United States

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, Michael [Nexant Inc., Burlington, MA (United States); Schellenberg, Josh [Nexant Inc., Burlington, MA (United States); Blundell, Marshall [Nexant Inc., Burlington, MA (United States)

    2015-01-01

    This report updates the 2009 meta-analysis that provides estimates of the value of service reliability for electricity customers in the United States (U.S.). The meta-dataset now includes 34 different datasets from surveys fielded by 10 different utility companies between 1989 and 2012. Because these studies used nearly identical interruption cost estimation or willingness-to-pay/accept methods, it was possible to integrate their results into a single meta-dataset describing the value of electric service reliability observed in all of them. Once the datasets from the various studies were combined, a two-part regression model was used to estimate customer damage functions that can be generally applied to calculate customer interruption costs per event by season, time of day, day of week, and geographical regions within the U.S. for industrial, commercial, and residential customers. This report focuses on the backwards stepwise selection process that was used to develop the final revised model for all customer classes. Across customer classes, the revised customer interruption cost model has improved significantly because it incorporates more data and does not include the many extraneous variables that were in the original specification from the 2009 meta-analysis. The backwards stepwise selection process led to a more parsimonious model that only included key variables, while still achieving comparable out-of-sample predictive performance. In turn, users of interruption cost estimation tools such as the Interruption Cost Estimate (ICE) Calculator will have less customer characteristics information to provide and the associated inputs page will be far less cumbersome. The upcoming new version of the ICE Calculator is anticipated to be released in 2015.

  13. Parametric estimation of covariance function in Gaussian-process based Kriging models. Application to uncertainty quantification for computer experiments

    International Nuclear Information System (INIS)

    Bachoc, F.

    2013-01-01

    The parametric estimation of the covariance function of a Gaussian process is studied, in the framework of the Kriging model. Maximum Likelihood and Cross Validation estimators are considered. The correctly specified case, in which the covariance function of the Gaussian process does belong to the parametric set used for estimation, is first studied in an increasing-domain asymptotic framework. The sampling considered is a randomly perturbed multidimensional regular grid. Consistency and asymptotic normality are proved for the two estimators. It is then put into evidence that strong perturbations of the regular grid are always beneficial to Maximum Likelihood estimation. The incorrectly specified case, in which the covariance function of the Gaussian process does not belong to the parametric set used for estimation, is then studied. It is shown that Cross Validation is more robust than Maximum Likelihood in this case. Finally, two applications of the Kriging model with Gaussian processes are carried out on industrial data. For a validation problem of the friction model of the thermal-hydraulic code FLICA 4, where experimental results are available, it is shown that Gaussian process modeling of the FLICA 4 code model error enables to considerably improve its predictions. Finally, for a meta modeling problem of the GERMINAL thermal-mechanical code, the interest of the Kriging model with Gaussian processes, compared to neural network methods, is shown. (author) [fr

  14. Meta-analysis with R

    CERN Document Server

    Schwarzer, Guido; Rücker, Gerta

    2015-01-01

    This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.  .

  15. Explaining development aid allocation by growth: A meta study

    DEFF Research Database (Denmark)

    Doucouliagos, Hristos; Paldam, Martin

      an interesting factor for two reasons: (1) It is relatively easy to interpret the results, and (2) it  is an important piece in the picture which suggests aid ineffectiveness. The paper is a meta-analysis of the 211 growth-aid estimates found in the 30 empirical studies. Additionally, we present new evidence...... using a panel data for 147 countries for the period 1967-2004. The result from both the meta-analysis and the primary data analysis is that growth does generate aid, so the dominating sign is positive. This result is driven partly by the large development banks....

  16. Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis.

    Science.gov (United States)

    Clark, Douglas B; Tanner-Smith, Emily E; Killingsworth, Stephen S

    2016-03-01

    In this meta-analysis, we systematically reviewed research on digital games and learning for K-16 students. We synthesized comparisons of game versus nongame conditions (i.e., media comparisons) and comparisons of augmented games versus standard game designs (i.e., value-added comparisons). We used random-effects meta-regression models with robust variance estimates to summarize overall effects and explore potential moderator effects. Results from media comparisons indicated that digital games significantly enhanced student learning relative to nongame conditions ([Formula: see text] = 0.33, 95% confidence interval [0.19, 0.48], k = 57, n = 209). Results from value-added comparisons indicated significant learning benefits associated with augmented game designs ([Formula: see text] = 0.34, 95% confidence interval [0.17, 0.51], k = 20, n = 40). Moderator analyses demonstrated that effects varied across various game mechanics characteristics, visual and narrative characteristics, and research quality characteristics. Taken together, the results highlight the affordances of games for learning as well as the key role of design beyond medium.

  17. Bias and precision of methods for estimating the difference in restricted mean survival time from an individual patient data meta-analysis

    Directory of Open Access Journals (Sweden)

    Béranger Lueza

    2016-03-01

    Full Text Available Abstract Background The difference in restricted mean survival time ( rmstD t ∗ $$ rmstD\\left({t}^{\\ast}\\right $$ , the area between two survival curves up to time horizon t ∗ $$ {t}^{\\ast } $$ , is often used in cost-effectiveness analyses to estimate the treatment effect in randomized controlled trials. A challenge in individual patient data (IPD meta-analyses is to account for the trial effect. We aimed at comparing different methods to estimate the rmstD t ∗ $$ rmstD\\left({t}^{\\ast}\\right $$ from an IPD meta-analysis. Methods We compared four methods: the area between Kaplan-Meier curves (experimental vs. control arm ignoring the trial effect (Naïve Kaplan-Meier; the area between Peto curves computed at quintiles of event times (Peto-quintile; the weighted average of the areas between either trial-specific Kaplan-Meier curves (Pooled Kaplan-Meier or trial-specific exponential curves (Pooled Exponential. In a simulation study, we varied the between-trial heterogeneity for the baseline hazard and for the treatment effect (possibly correlated, the overall treatment effect, the time horizon t ∗ $$ {t}^{\\ast } $$ , the number of trials and of patients, the use of fixed or DerSimonian-Laird random effects model, and the proportionality of hazards. We compared the methods in terms of bias, empirical and average standard errors. We used IPD from the Meta-Analysis of Chemotherapy in Nasopharynx Carcinoma (MAC-NPC and its updated version MAC-NPC2 for illustration that included respectively 1,975 and 5,028 patients in 11 and 23 comparisons. Results The Naïve Kaplan-Meier method was unbiased, whereas the Pooled Exponential and, to a much lesser extent, the Pooled Kaplan-Meier methods showed a bias with non-proportional hazards. The Peto-quintile method underestimated the rmstD t ∗ $$ rmstD\\left({t}^{\\ast}\\right $$ , except with non-proportional hazards at t ∗ $$ {t}^{\\ast } $$ = 5 years. In the presence of treatment effect

  18. Meta-analysis for genome-wide association studies using case-control design: application and practice

    Directory of Open Access Journals (Sweden)

    Sungryul Shim

    2016-12-01

    Full Text Available This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA. The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy–Weinberg equilibrium (HWE in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The ‘genhwcci’ and ‘metan’ commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the ‘metareg’ command of STATA should be conducted to evaluate related factors of heterogeneities.

  19. Estimating the burden of pneumococcal pneumonia among adults: a systematic review and meta-analysis of diagnostic techniques.

    Directory of Open Access Journals (Sweden)

    Maria A Said

    Full Text Available Pneumococcal pneumonia causes significant morbidity and mortality among adults. Given limitations of diagnostic tests for non-bacteremic pneumococcal pneumonia, most studies report the incidence of bacteremic or invasive pneumococcal disease (IPD, and thus, grossly underestimate the pneumococcal pneumonia burden. We aimed to develop a conceptual and quantitative strategy to estimate the non-bacteremic disease burden among adults with community-acquired pneumonia (CAP using systematic study methods and the availability of a urine antigen assay.We performed a systematic literature review of studies providing information on the relative yield of various diagnostic assays (BinaxNOW® S. pneumoniae urine antigen test (UAT with blood and/or sputum culture in diagnosing pneumococcal pneumonia. We estimated the proportion of pneumococcal pneumonia that is bacteremic, the proportion of CAP attributable to pneumococcus, and the additional contribution of the Binax UAT beyond conventional diagnostic techniques, using random effects meta-analytic methods and bootstrapping. We included 35 studies in the analysis, predominantly from developed countries. The estimated proportion of pneumococcal pneumonia that is bacteremic was 24.8% (95% CI: 21.3%, 28.9%. The estimated proportion of CAP attributable to pneumococcus was 27.3% (95% CI: 23.9%, 31.1%. The Binax UAT diagnosed an additional 11.4% (95% CI: 9.6, 13.6% of CAP beyond conventional techniques. We were limited by the fact that not all patients underwent all diagnostic tests and by the sensitivity and specificity of the diagnostic tests themselves. We address these resulting biases and provide a range of plausible values in order to estimate the burden of pneumococcal pneumonia among adults.Estimating the adult burden of pneumococcal disease from bacteremic pneumococcal pneumonia data alone significantly underestimates the true burden of disease in adults. For every case of bacteremic pneumococcal pneumonia

  20. Natural funnel asymmetries. A simulation analysis of the three basic tools of meta analysis

    DEFF Research Database (Denmark)

    Callot, Laurent Abdelkader Francois; Paldam, Martin

    Meta-analysis studies a set of estimates of one parameter with three basic tools: The funnel diagram is the distribution of the estimates as a function of their precision; the funnel asymmetry test, FAT; and the meta average, where PET is an estimate. The FAT-PET MRA is a meta regression analysis...

  1. Statistical Model-Based Face Pose Estimation

    Institute of Scientific and Technical Information of China (English)

    GE Xinliang; YANG Jie; LI Feng; WANG Huahua

    2007-01-01

    A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.

  2. Conducting Meta-Analyses Based on p Values

    Science.gov (United States)

    van Aert, Robbie C. M.; Wicherts, Jelte M.; van Assen, Marcel A. L. M.

    2016-01-01

    Because of overwhelming evidence of publication bias in psychology, techniques to correct meta-analytic estimates for such bias are greatly needed. The methodology on which the p-uniform and p-curve methods are based has great promise for providing accurate meta-analytic estimates in the presence of publication bias. However, in this article, we show that in some situations, p-curve behaves erratically, whereas p-uniform may yield implausible estimates of negative effect size. Moreover, we show that (and explain why) p-curve and p-uniform result in overestimation of effect size under moderate-to-large heterogeneity and may yield unpredictable bias when researchers employ p-hacking. We offer hands-on recommendations on applying and interpreting results of meta-analyses in general and p-uniform and p-curve in particular. Both methods as well as traditional methods are applied to a meta-analysis on the effect of weight on judgments of importance. We offer guidance for applying p-uniform or p-curve using R and a user-friendly web application for applying p-uniform. PMID:27694466

  3. Deviation from intention to treat analysis in randomised trials and treatment effect estimates: meta-epidemiological study.

    Science.gov (United States)

    Abraha, Iosief; Cherubini, Antonio; Cozzolino, Francesco; De Florio, Rita; Luchetta, Maria Laura; Rimland, Joseph M; Folletti, Ilenia; Marchesi, Mauro; Germani, Antonella; Orso, Massimiliano; Eusebi, Paolo; Montedori, Alessandro

    2015-05-27

    To examine whether deviation from the standard intention to treat analysis has an influence on treatment effect estimates of randomised trials. Meta-epidemiological study. Medline, via PubMed, searched between 2006 and 2010; 43 systematic reviews of interventions and 310 randomised trials were included. From each year searched, random selection of 5% of intervention reviews with a meta-analysis that included at least one trial that deviated from the standard intention to treat approach. Basic characteristics of the systematic reviews and randomised trials were extracted. Information on the reporting of intention to treat analysis, outcome data, risk of bias items, post-randomisation exclusions, and funding were extracted from each trial. Trials were classified as: ITT (reporting the standard intention to treat approach), mITT (reporting a deviation from the standard approach), and no ITT (reporting no approach). Within each meta-analysis, treatment effects were compared between mITT and ITT trials, and between mITT and no ITT trials. The ratio of odds ratios was calculated (value deviated from the intention to treat analysis showed larger intervention effects than trials that reported the standard approach. Where an intention to treat analysis is impossible to perform, authors should clearly report who is included in the analysis and attempt to perform multiple imputations. © Abraha et al 2015.

  4. Meta II: Multi-Model Language Suite for Cyber Physical Systems

    Science.gov (United States)

    2013-03-01

    AVM META) projects have developed tools for designing cyber physical (or Mechatronic ) Systems . These systems are increasingly complex, take much...projects have developed tools for designing cyber physical (CPS) (or Mechatronic ) systems . Exemplified by modern amphibious and ground military...and parametric interface of Simulink models and defines associations with CyPhy components and component interfaces. 2. Embedded Systems Modeling

  5. Mean-field theory of meta-learning

    International Nuclear Information System (INIS)

    Plewczynski, Dariusz

    2009-01-01

    We discuss here the mean-field theory for a cellular automata model of meta-learning. Meta-learning is the process of combining outcomes of individual learning procedures in order to determine the final decision with higher accuracy than any single learning method. Our method is constructed from an ensemble of interacting, learning agents that acquire and process incoming information using various types, or different versions, of machine learning algorithms. The abstract learning space, where all agents are located, is constructed here using a fully connected model that couples all agents with random strength values. The cellular automata network simulates the higher level integration of information acquired from the independent learning trials. The final classification of incoming input data is therefore defined as the stationary state of the meta-learning system using simple majority rule, yet the minority clusters that share the opposite classification outcome can be observed in the system. Therefore, the probability of selecting a proper class for a given input data, can be estimated even without the prior knowledge of its affiliation. The fuzzy logic can be easily introduced into the system, even if learning agents are built from simple binary classification machine learning algorithms by calculating the percentage of agreeing agents

  6. Estimating the prevalence, hospitalisation and mortality from type 2 diabetes mellitus in Nigeria: a systematic review and meta-analysis.

    Science.gov (United States)

    Adeloye, Davies; Ige, Janet O; Aderemi, Adewale V; Adeleye, Ngozi; Amoo, Emmanuel O; Auta, Asa; Oni, Gbolahan

    2017-05-11

    There is not yet a comprehensive evidence-based epidemiological report on type 2 diabetes mellitus (T2DM) in Nigeria. We aimed to estimate country-wide and zonal prevalence, hospitalisation and mortality rates of T2DM in Nigeria. We searched MEDLINE, EMBASE, Global Health, Africa Journals Online (AJOL) and Google Scholar for population and hospital-based studies on T2DM in Nigeria. We conducted a random-effects meta-analysis on extracted crude estimates, and applied a meta-regression epidemiological model, using the United Nations demographics for Nigeria in 1990 and 2015 to determine estimates of diabetes in Nigeria for the two years. 42 studies, with a total population of 91 320, met our selection criteria. Most of the studies selected were of medium quality (90.5%). The age-adjusted prevalence rates of T2DM in Nigeria among persons aged 20-79 years increased from 2.0% (95% CI 1.9% to 2.1%) in 1990 to 5.7% (95% CI 5.5% to 5.8%) in 2015, accounting for over 874 000 and 4.7 million cases, respectively. The pooled prevalence rate of impaired glucose tolerance was 10.0% (95% CI 4.5% to 15.6%), while impaired fasting glucose was 5.8% (95% CI 3.8% to 7.8%). Hospital admission rate for T2DM was 222.6 (95% CI 133.1 to 312.1) per 100 000 population with hyperglycaemic emergencies, diabetic foot and cardiovascular diseases being most common complications. The overall mortality rate was 30.2 (95% CI 14.6 to 45.8) per 100 000 population, with a case fatality rate of 22.0% (95% CI 8.0% to 36.0%). Our findings suggest an increasing burden of T2DM in Nigeria with many persons currently undiagnosed, and few known cases on treatment. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  7. The effect of S-adenosylmethionine on cognitive performance in mice: an animal model meta-analysis.

    Directory of Open Access Journals (Sweden)

    Sarah E Montgomery

    Full Text Available Alzheimer's disease (AD is the most frequently diagnosed form of dementia resulting in cognitive impairment. Many AD mouse studies, using the methyl donor S-adenosylmethionine (SAM, report improved cognitive ability, but conflicting results between and within studies currently exist. To address this, we conducted a meta-analysis to evaluate the effect of SAM on cognitive ability as measured by Y maze performance. As supporting evidence, we include further discussion of improvements in cognitive ability, by SAM, as measured by the Morris water maze (MWM.We conducted a comprehensive literature review up to April 2014 based on searches querying MEDLINE, EMBASE, Web of Science, the Cochrane Library and Proquest Theses and Dissertation databases. We identified three studies containing a total of 12 experiments that met our inclusion criteria and one study for qualitative review. The data from these studies were used to evaluate the effect of SAM on cognitive performance according to two scenarios: 1. SAM supplemented folate deficient (SFD diet compared to a folate deficient (FD diet and 2. SFD diet compared to a nutrient complete (NC diet. Hedge's g was used to calculate effect sizes and mixed effects model meta-regression was used to evaluate moderating factors.Our findings showed that the SFD diet was associated with improvements in cognitive performance. SFD diet mice also had superior cognitive performance compared to mice on an NC diet. Further to this, meta-regression analyses indicated a significant positive effect of study quality score and treatment duration on the effect size estimate for both the FD vs SFD analysis and the SFD vs NC analysis.The findings of this meta-analysis demonstrate efficacy of SAM in acting as a cognitive performance-enhancing agent. As a corollary, SAM may be useful in improving spatial memory in patients suffering from many dementia forms including AD.

  8. Prevalence of Depression among University Students: A Systematic Review and Meta-Analysis Study

    OpenAIRE

    Diana Sarokhani; Ali Delpisheh; Yousef Veisani; Mohamad Taher Sarokhani; Rohollah Esmaeli Manesh; Kourosh Sayehmiri

    2013-01-01

    Introduction. Depression is one of the four major diseases in the world and is the most common cause of disability from diseases. The aim of this study is to estimate the prevalence of depression among Iranian university students using meta-analysis method. Materials and Methods. Keyword depression was searched in electronic databases such as PubMed, Scopus, MAGIran, Medlib, and SID. Data was analyzed using meta-analysis (random-effects model). Heterogeneity of studies was assessed using ...

  9. A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.

    Science.gov (United States)

    Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D

    2012-04-01

    A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the

  10. Study Heterogeneity and Estimation of Prevalence of Primary Aldosteronism: A Systematic Review and Meta-Regression Analysis.

    Science.gov (United States)

    Käyser, Sabine C; Dekkers, Tanja; Groenewoud, Hans J; van der Wilt, Gert Jan; Carel Bakx, J; van der Wel, Mark C; Hermus, Ad R; Lenders, Jacques W; Deinum, Jaap

    2016-07-01

    For health care planning and allocation of resources, realistic estimation of the prevalence of primary aldosteronism is necessary. Reported prevalences of primary aldosteronism are highly variable, possibly due to study heterogeneity. Our objective was to identify and explain heterogeneity in studies that aimed to establish the prevalence of primary aldosteronism in hypertensive patients. PubMed, EMBASE, Web of Science, Cochrane Library, and reference lists from January 1, 1990, to January 31, 2015, were used as data sources. Description of an adult hypertensive patient population with confirmed diagnosis of primary aldosteronism was included in this study. Dual extraction and quality assessment were the forms of data extraction. Thirty-nine studies provided data on 42 510 patients (nine studies, 5896 patients from primary care). Prevalence estimates varied from 3.2% to 12.7% in primary care and from 1% to 29.8% in referral centers. Heterogeneity was too high to establish point estimates (I(2) = 57.6% in primary care; 97.1% in referral centers). Meta-regression analysis showed higher prevalences in studies 1) published after 2000, 2) from Australia, 3) aimed at assessing prevalence of secondary hypertension, 4) that were retrospective, 5) that selected consecutive patients, and 6) not using a screening test. All studies had minor or major flaws. This study demonstrates that it is pointless to claim low or high prevalence of primary aldosteronism based on published reports. Because of the significant impact of a diagnosis of primary aldosteronism on health care resources and the necessary facilities, our findings urge for a prevalence study whose design takes into account the factors identified in the meta-regression analysis.

  11. Bayesian Meta-Analysis of Coefficient Alpha

    Science.gov (United States)

    Brannick, Michael T.; Zhang, Nanhua

    2013-01-01

    The current paper describes and illustrates a Bayesian approach to the meta-analysis of coefficient alpha. Alpha is the most commonly used estimate of the reliability or consistency (freedom from measurement error) for educational and psychological measures. The conventional approach to meta-analysis uses inverse variance weights to combine…

  12. Global Prevalence of Elder Abuse: A Meta-analysis and Meta-regression.

    Science.gov (United States)

    Ho, C Sh; Wong, S Y; Chiu, M M; Ho, R Cm

    2017-06-01

    Elder abuse is increasingly recognised as a global public health and social problem. There has been limited inter-study comparison of the prevalence and risk factors for elder abuse. This study aimed to estimate the pooled and subtype prevalence of elder abuse worldwide and identify significant associated risk factors. We conducted a meta-analysis and meta-regression of 34 population-based and 17 non-population-based studies. The pooled prevalences of elder abuse were 10.0% (95% confidence interval, 5.2%-18.6%) and 34.3% (95% confidence interval, 22.9%-47.8%) in population-based studies and third party- or caregiver-reported studies, respectively. Being in a marital relationship was found to be a significant moderator using random-effects model. This meta-analysis revealed that third parties or caregivers were more likely to report abuse than older abused adults. Subgroup analyses showed that females and those resident in non-western countries were more likely to be abused. Emotional abuse was the most prevalent elder abuse subtype and financial abuse was less commonly reported by third parties or caregivers. Heterogeneity in the prevalence was due to the high proportion of married older adults in the sample. Subgroup analysis showed that cultural factors, subtypes of abuse, and gender also contributed to heterogeneity in the pooled prevalence of elder abuse.

  13. Introducing Meta-Partition, a Useful Methodology to Explore Factors That Influence Ecological Effect Sizes.

    Directory of Open Access Journals (Sweden)

    Zaida Ortega

    Full Text Available The study of the heterogeneity of effect sizes is a key aspect of ecological meta-analyses. Here we propose a meta-analytic methodology to study the influence of moderators in effect sizes by splitting heterogeneity: meta-partition. To introduce this methodology, we performed a meta-partition of published data about the traits that influence species sensitivity to habitat loss, that have been previously analyzed through meta-regression. Thus, here we aim to introduce meta-partition and to make an initial comparison with meta-regression. Meta-partition algorithm consists of three steps. Step 1 is to study the heterogeneity of effect sizes under the assumption of fixed effect model. If heterogeneity is found, we perform step 2, that is, to partition the heterogeneity by the moderator that minimizes heterogeneity within a subset while maximizing heterogeneity between subsets. Then, if effect sizes of the subset are still heterogeneous, we repeat step 1 and 2 until we reach final subsets. Finally, step 3 is to integrate effect sizes of final subsets, with fixed effect model if there is homogeneity, and with random effects model if there is heterogeneity. Results show that meta-partition is valuable to assess the importance of moderators in explaining heterogeneity of effect sizes, as well as to assess the directions of these relations and to detect possible interactions between moderators. With meta-partition we have been able to evaluate the importance of moderators in a more objective way than with meta-regression, and to visualize the complex relations that may exist between them. As ecological issues are often influenced by several factors interacting in complex ways, ranking the importance of possible moderators and detecting possible interactions would make meta-partition a useful exploration tool for ecological meta-analyses.

  14. Model-based estimation for dynamic cardiac studies using ECT.

    Science.gov (United States)

    Chiao, P C; Rogers, W L; Clinthorne, N H; Fessler, J A; Hero, A O

    1994-01-01

    The authors develop a strategy for joint estimation of physiological parameters and myocardial boundaries using ECT (emission computed tomography). They construct an observation model to relate parameters of interest to the projection data and to account for limited ECT system resolution and measurement noise. The authors then use a maximum likelihood (ML) estimator to jointly estimate all the parameters directly from the projection data without reconstruction of intermediate images. They also simulate myocardial perfusion studies based on a simplified heart model to evaluate the performance of the model-based joint ML estimator and compare this performance to the Cramer-Rao lower bound. Finally, the authors discuss model assumptions and potential uses of the joint estimation strategy.

  15. Humor styles and personality: A meta-analysis of the relation between humor styles and the Big Five personality traits.

    Science.gov (United States)

    Mendiburo-Seguel, Andrés; Páez, Darío; Martínez-Sánchez, Francisco

    2015-06-01

    This research summarizes the knowledge generated in social psychology and positive psychology about the relationship between humor styles, personality and wellbeing. Specifically, a meta-analysis was performed with the results of 15 studies on humor styles measured by the Humor Styles Questionnaire (Martin, Puhlik-Doris, Larsen, Gray & Weir, 2003) in correlation with the personality traits measured by the Big Five Personality model (measured with different scales). Following the steps presented by Rosenthal (1991) for meta-analysis in the case of correlational research, we calculated the total mean r as an indicator of effect size. Results show that affiliative humor has a strong and homogeneous relation to neuroticism and extraversion. The homogeneity and heterogeneity found between variables and possible explanations are discussed in the conclusion. © 2015 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  16. Detecting and correcting for publication bias in meta-analysis - A truncated normal distribution approach.

    Science.gov (United States)

    Zhu, Qiaohao; Carriere, K C

    2016-01-01

    Publication bias can significantly limit the validity of meta-analysis when trying to draw conclusion about a research question from independent studies. Most research on detection and correction for publication bias in meta-analysis focus mainly on funnel plot-based methodologies or selection models. In this paper, we formulate publication bias as a truncated distribution problem, and propose new parametric solutions. We develop methodologies of estimating the underlying overall effect size and the severity of publication bias. We distinguish the two major situations, in which publication bias may be induced by: (1) small effect size or (2) large p-value. We consider both fixed and random effects models, and derive estimators for the overall mean and the truncation proportion. These estimators will be obtained using maximum likelihood estimation and method of moments under fixed- and random-effects models, respectively. We carried out extensive simulation studies to evaluate the performance of our methodology, and to compare with the non-parametric Trim and Fill method based on funnel plot. We find that our methods based on truncated normal distribution perform consistently well, both in detecting and correcting publication bias under various situations.

  17. Alcohol and the risk of sleep apnoea: a systematic review and meta-analysis.

    Science.gov (United States)

    Simou, Evangelia; Britton, John; Leonardi-Bee, Jo

    2018-02-01

    A systematic review and meta-analysis of the association between alcohol consumption and risk of sleep apnoea in adults. We searched Medline, EMBASE and Web of Science databases from 1985 to 2015 for comparative epidemiological studies assessing the relation between alcohol consumption and sleep apnoea. Two authors independently screened and extracted data. Random effects meta-analysis was used to estimate pooled effect sizes with 95% confidence intervals (CI). Heterogeneity was quantified using I 2 and explored using subgroup analyses based on study exposure and outcome measures, quality, design, adjustment for confounders and geographical location. Publication bias was assessed using a funnel plot and Egger's test. We identified 21 studies from which estimates of relative risk could be obtained. Meta-analysis of these estimates demonstrated that higher levels of alcohol consumption increased the risk of sleep apnoea by 25% (RR 1.25, 95%CI 1.13-1.38, I 2  = 82%, p Country locations. We detected evidence of publication bias (p = 0.001). A further eight included studies reported average alcohol consumption in people with and without sleep apnoea. Meta-analysis revealed that mean alcohol intake was two units/week higher in those with sleep apnoea, but this difference was not statistically significant (p = 0.41). These findings suggest that alcohol consumption is associated with a higher risk of sleep apnoea, further supporting evidence that reducing alcohol intake is of potential therapeutic and preventive value in this condition. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  18. Promoting Continuous Quality Improvement in Online Teaching: The META Model

    Science.gov (United States)

    Dittmar, Eileen; McCracken, Holly

    2012-01-01

    Experienced e-learning faculty members share strategies for implementing a comprehensive postsecondary faculty development program essential to continuous improvement of instructional skills. The high-impact META Model (centered around Mentoring, Engagement, Technology, and Assessment) promotes information sharing and content creation, and fosters…

  19. Meta-analysis of the relative sensitivity of semi-natural vegetation species to ozone

    International Nuclear Information System (INIS)

    Hayes, F.; Jones, M.L.M.; Mills, G.; Ashmore, M.

    2007-01-01

    This study identified 83 species from existing publications suitable for inclusion in a database of sensitivity of species to ozone (OZOVEG database). An index, the relative sensitivity to ozone, was calculated for each species based on changes in biomass in order to test for species traits associated with ozone sensitivity. Meta-analysis of the ozone sensitivity data showed a wide inter-specific range in response to ozone. Some relationships in comparison to plant physiological and ecological characteristics were identified. Plants of the therophyte lifeform were particularly sensitive to ozone. Species with higher mature leaf N concentration were more sensitive to ozone than those with lower leaf N concentration. Some relationships between relative sensitivity to ozone and Ellenberg habitat requirements were also identified. In contrast, no relationships between relative sensitivity to ozone and mature leaf P concentration, Grime's CSR strategy, leaf longevity, flowering season, stomatal density and maximum altitude were found. The relative sensitivity of species and relationships with plant characteristics identified in this study could be used to predict sensitivity to ozone of untested species and communities. - Meta-analysis of the relative sensitivity of semi-natural vegetation species to ozone showed some relationships with physiological and ecological characteristics

  20. Estimation of environment-related properties of chemicals for design of sustainable processes: Development of group-contribution+ (GC+) models and uncertainty analysis

    DEFF Research Database (Denmark)

    Hukkerikar, Amol; Kalakul, Sawitree; Sarup, Bent

    2012-01-01

    The aim of this work is to develop group-3 contribution+ (GC+)method (combined group-contribution (GC) method and atom connectivity index (CI)) based 15 property models to provide reliable estimations of environment-related properties of organic chemicals together with uncertainties of estimated...... property values. For this purpose, a systematic methodology for property modeling and uncertainty analysis is used. The methodology includes a parameter estimation step to determine parameters of property models and an uncertainty analysis step to establish statistical information about the quality......, poly functional chemicals, etc.) taken from the database of the US Environmental Protection Agency (EPA) and from the database of USEtox is used. For property modeling and uncertainty analysis, the Marrero and Gani GC method and atom connectivity index method have been considered. In total, 22...

  1. Lack of association of poultry and eggs intake with risk of non-Hodgkin lymphoma: a meta-analysis of observational studies.

    Science.gov (United States)

    Dong, Y; Wu, G

    2017-09-01

    We carried out a meta-analysis to explore the association between poultry and eggs consumption and non-Hodgkin lymphoma (NHL) risk according to the published observational studies. A search of databases was performed in MEDLINE and EMBASE from their inception to March 2015. We derived meta-analytic estimates using random-effects models, and assessed between-study heterogeneity using the Cochran's Q and I 2 statistics. We identified a total of nine case-control and three prospective cohort studies, including 11,271 subjects with NHL. The summary relative risks for high vs. low analyses were 1.04 (95% confidence intervals [CIs]: 0.86-1.27; p heterogeneity poultry consumption and 1.15 (95% CIs: 0.87-1.51; p heterogeneity poultry consumption, whereas no significant factors were responsible for the high heterogeneity among the studies on eggs consumption. Limited data suggested a null association between consumption of poultry and eggs and NHL subtypes. Findings from our meta-analysis indicate that consumption of poultry and eggs may be not related to NHL risk. © 2016 John Wiley & Sons Ltd.

  2. Systematic review using meta-analyses to estimate dose-response relationships between iodine intake and biomarkers of iodine status in different population groups

    NARCIS (Netherlands)

    Ristic-Medic, D.; Dullemeijer, C.; Tepsic, J.; Petrovic-Oggiano, G.; Popovic, Z.; Arsic, A.; Glibetic, M.; Souverein, O.W.; Collings, R.; Cavelaars, A.J.E.M.; Groot, de C.P.G.M.; Veer, van 't P.; Gurinovic, M.

    2014-01-01

    The objective of this systematic review was to identify studies investigating iodine intake and biomarkers of iodine status, to assess the data of the selected studies, and to estimate dose-response relationships using meta-analysis. All randomized controlled trials, prospective cohort studies,

  3. Measuring Parental Meta-Emotion: Psychometric Properties of the Emotion-Related Parenting Styles Self-Test

    Science.gov (United States)

    Hakim-Larson, Julie; Parker, Alison; Lee, Catharine; Goodwin, Jacqueline; Voelker, Sylvia

    2006-01-01

    Parental meta-emotion, assessed through interviews, involves parents' philosophy about emotions and has been found to be related to parenting behaviors and children's emotional and social competence (e.g., Gottman, Katz, & Hooven, 1996; Katz & Windecker-Nelson, 2004). The Emotion-Related Parenting Styles Self-Test is a true-false…

  4. Constraints on the nuclear equation of state from nuclear masses and radii in a Thomas-Fermi meta-modeling approach

    Science.gov (United States)

    Chatterjee, D.; Gulminelli, F.; Raduta, Ad. R.; Margueron, J.

    2017-12-01

    The question of correlations among empirical equation of state (EoS) parameters constrained by nuclear observables is addressed in a Thomas-Fermi meta-modeling approach. A recently proposed meta-modeling for the nuclear EoS in nuclear matter is augmented with a single finite size term to produce a minimal unified EoS functional able to describe the smooth part of the nuclear ground state properties. This meta-model can reproduce the predictions of a large variety of models, and interpolate continuously between them. An analytical approximation to the full Thomas-Fermi integrals is further proposed giving a fully analytical meta-model for nuclear masses. The parameter space is sampled and filtered through the constraint of nuclear mass reproduction with Bayesian statistical tools. We show that this simple analytical meta-modeling has a predictive power on masses, radii, and skins comparable to full Hartree-Fock or extended Thomas-Fermi calculations with realistic energy functionals. The covariance analysis on the posterior distribution shows that no physical correlation is present between the different EoS parameters. Concerning nuclear observables, a strong correlation between the slope of the symmetry energy and the neutron skin is observed, in agreement with previous studies.

  5. Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

    Science.gov (United States)

    Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

    2017-07-01

    Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

  6. Model-based estimation for dynamic cardiac studies using ECT

    International Nuclear Information System (INIS)

    Chiao, P.C.; Rogers, W.L.; Clinthorne, N.H.; Fessler, J.A.; Hero, A.O.

    1994-01-01

    In this paper, the authors develop a strategy for joint estimation of physiological parameters and myocardial boundaries using ECT (Emission Computed Tomography). The authors construct an observation model to relate parameters of interest to the projection data and to account for limited ECT system resolution and measurement noise. The authors then use a maximum likelihood (ML) estimator to jointly estimate all the parameters directly from the projection data without reconstruction of intermediate images. The authors also simulate myocardial perfusion studies based on a simplified heart model to evaluate the performance of the model-based joint ML estimator and compare this performance to the Cramer-Rao lower bound. Finally, model assumptions and potential uses of the joint estimation strategy are discussed

  7. Meta-Analysis of the Structural Equation Models' Parameters for the Estimation of Brain Connectivity with fMRI

    Directory of Open Access Journals (Sweden)

    Joan Guàrdia-Olmos

    2018-02-01

    Full Text Available Structural Equation Models (SEM is among of the most extensively applied statistical techniques in the study of human behavior in the fields of Neuroscience and Cognitive Neuroscience. This paper reviews the application of SEM to estimate functional and effective connectivity models in work published since 2001. The articles analyzed were compiled from Journal Citation Reports, PsycInfo, Pubmed, and Scopus, after searching with the following keywords: fMRI, SEMs, and Connectivity.Results: A 100 papers were found, of which 25 were rejected due to a lack of sufficient data on basic aspects of the construction of SEM. The other 75 were included and contained a total of 160 models to analyze, since most papers included more than one model. The analysis of the explained variance (R2 of each model yields an effect of the type of design used, the type of population studied, the type of study, the existence of recursive effects in the model, and the number of paths defined in the model. Along with these comments, a series of recommendations are included for the use of SEM to estimate of functional and effective connectivity models.

  8. Safety and functional outcome of thrombolysis in dissection-related ischemic stroke: a meta-analysis of individual patient data

    NARCIS (Netherlands)

    Zinkstok, Sanne M.; Vergouwen, Mervyn D. I.; Engelter, Stefan T.; Lyrer, Philippe A.; Bonati, Leo H.; Arnold, Marcel; Mattle, Heinrich P.; Fischer, Urs; Sarikaya, Hakan; Baumgartner, Ralf W.; Georgiadis, Dimitrios; Odier, Céline; Michel, Patrik; Putaala, Jukka; Griebe, Martin; Wahlgren, Nils; Ahmed, Niaz; van Geloven, Nan; de Haan, Rob J.; Nederkoorn, Paul J.

    2011-01-01

    The safety and efficacy of thrombolysis in cervical artery dissection (CAD) are controversial. The aim of this meta-analysis was to pool all individual patient data and provide a valid estimate of safety and outcome of thrombolysis in CAD. We performed a systematic literature search on intravenous

  9. Fruits, vegetables and breast cancer risk: a systematic review and meta-analysis of prospective studies.

    Science.gov (United States)

    Aune, D; Chan, D S M; Vieira, A R; Rosenblatt, D A Navarro; Vieira, R; Greenwood, D C; Norat, T

    2012-07-01

    Evidence for an association between fruit and vegetable intake and breast cancer risk is inconclusive. To clarify the association, we conducted a systematic review and meta-analysis of the evidence from prospective studies. We searched PubMed for prospective studies of fruit and vegetable intake and breast cancer risk until April 30, 2011. We included fifteen prospective studies that reported relative risk estimates and 95 % confidence intervals (CIs) of breast cancer associated with fruit and vegetable intake. Random effects models were used to estimate summary relative risks. The summary relative risk (RR) for the highest versus the lowest intake was 0.89 (95 % CI: 0.80-0.99, I (2) = 0 %) for fruits and vegetables combined, 0.92 (95 % CI: 0.86-0.98, I (2) = 9 %) for fruits, and 0.99 (95 % CI: 0.92-1.06, I (2) = 20 %) for vegetables. In dose-response analyses, the summary RR per 200 g/day was 0.96 (95 % CI: 0.93-1.00, I (2) = 2 %) for fruits and vegetables combined, 0.94 (95 % CI: 0.89-1.00, I (2) = 39 %) for fruits, and 1.00 (95 % CI: 0.95-1.06, I (2) = 17 %) for vegetables. In this meta-analysis of prospective studies, high intake of fruits, and fruits and vegetables combined, but not vegetables, is associated with a weak reduction in risk of breast cancer.

  10. Blood pressure and kidney cancer risk: meta-analysis of prospective studies.

    Science.gov (United States)

    Hidayat, Khemayanto; Du, Xuan; Zou, Sheng-Yi; Shi, Bi-Min

    2017-07-01

    Globally, kidney cancer is the twelfth most common cancer, accounting for 337 860 cases recorded in 2012. By 2020, this number has been estimated to reach 412 929 or increase by 22%. Over the past few decades, a number of prospective studies have investigated the association between blood pressure (BP) and risk of kidney cancer, using either recorded BP levels or reported hypertension as the principal exposure variable. However, the relation of BP to kidney cancer remains incompletely understood, and the data on sex-specific differences in risk estimates have been inconsistent. PubMed and Web of Science databases were searched for studies assessing the association between BP and kidney cancer through July 2016. The summary relative risk with 95% confidence intervals was calculated using a random-effects model. A total of 18 prospective studies with 8097 kidney cancer cases from 3 628 479 participants were included in our meta-analysis. History of hypertension was associated with 67% increased risk of kidney cancer. Significant heterogeneity and evidence of publication bias were observed. However, the results remain unchanged after introducing the trim and fill method to correct the publication bias. Accordingly, each 10-mmHg increase in SBP and DBP was associated with 10 and 22% increased risk of kidney cancer. Collectively, the present meta-analysis of 18 prospective studies provides further support for a positive association between hypertension and kidney cancer risk.

  11. Visualizing the flow of evidence in network meta-analysis and characterizing mixed treatment comparisons.

    Science.gov (United States)

    König, Jochem; Krahn, Ulrike; Binder, Harald

    2013-12-30

    Network meta-analysis techniques allow for pooling evidence from different studies with only partially overlapping designs for getting a broader basis for decision support. The results are network-based effect estimates that take indirect evidence into account for all pairs of treatments. The results critically depend on homogeneity and consistency assumptions, which are sometimes difficult to investigate. To support such evaluation, we propose a display of the flow of evidence and introduce new measures that characterize the structure of a mixed treatment comparison. Specifically, a linear fixed effects model for network meta-analysis is considered, where the network estimates for two treatments are linear combinations of direct effect estimates comparing these or other treatments. The linear coefficients can be seen as the generalization of weights known from classical meta-analysis. We summarize properties of these coefficients and display them as a weighted directed acyclic graph, representing the flow of evidence. Furthermore, measures are introduced that quantify the direct evidence proportion, the mean path length, and the minimal parallelism of mixed treatment comparisons. The graphical display and the measures are illustrated for two published network meta-analyses. In these applications, the proposed methods are seen to render transparent the process of data pooling in mixed treatment comparisons. They can be expected to be more generally useful for guiding and facilitating the validity assessment in network meta-analysis. Copyright © 2013 John Wiley & Sons, Ltd.

  12. Estimates of Between-Study Heterogeneity for 705 Meta-Analyses Reported in Psychological Bulletin From 1990–2013

    Directory of Open Access Journals (Sweden)

    Sara van Erp

    2017-08-01

    Full Text Available We present a data set containing 705 between-study heterogeneity estimates τ2 as reported in 61 articles published in 'Psychological Bulletin' from 1990–2013. The data set also includes information about the number and type of effect sizes, the 'Q'- and 'I'2-statistics, and publication bias. The data set is stored in the Open Science Framework repository (https://osf.io/wyhve/ and can be used for several purposes: (1 to compare a specific heterogeneity estimate to the distribution of between-study heterogeneity estimates in psychology; (2 to construct an informed prior distribution for the between-study heterogeneity in psychology; (3 to obtain realistic population values for Monte Carlo simulations investigating the performance of meta-analytic methods.   Funding statement: This research was supported by the ERC project “Bayes or Bust”.

  13. Can statistic adjustment of OR minimize the potential confounding bias for meta-analysis of case-control study? A secondary data analysis.

    Science.gov (United States)

    Liu, Tianyi; Nie, Xiaolu; Wu, Zehao; Zhang, Ying; Feng, Guoshuang; Cai, Siyu; Lv, Yaqi; Peng, Xiaoxia

    2017-12-29

    Different confounder adjustment strategies were used to estimate odds ratios (ORs) in case-control study, i.e. how many confounders original studies adjusted and what the variables are. This secondary data analysis is aimed to detect whether there are potential biases caused by difference of confounding factor adjustment strategies in case-control study, and whether such bias would impact the summary effect size of meta-analysis. We included all meta-analyses that focused on the association between breast cancer and passive smoking among non-smoking women, as well as each original case-control studies included in these meta-analyses. The relative deviations (RDs) of each original study were calculated to detect how magnitude the adjustment would impact the estimation of ORs, compared with crude ORs. At the same time, a scatter diagram was sketched to describe the distribution of adjusted ORs with different number of adjusted confounders. Substantial inconsistency existed in meta-analysis of case-control studies, which would influence the precision of the summary effect size. First, mixed unadjusted and adjusted ORs were used to combine individual OR in majority of meta-analysis. Second, original studies with different adjustment strategies of confounders were combined, i.e. the number of adjusted confounders and different factors being adjusted in each original study. Third, adjustment did not make the effect size of original studies trend to constringency, which suggested that model fitting might have failed to correct the systematic error caused by confounding. The heterogeneity of confounder adjustment strategies in case-control studies may lead to further bias for summary effect size in meta-analyses, especially for weak or medium associations so that the direction of causal inference would be even reversed. Therefore, further methodological researches are needed, referring to the assessment of confounder adjustment strategies, as well as how to take this kind

  14. Exploring association between statin use and breast cancer risk: an updated meta-analysis.

    Science.gov (United States)

    Islam, Md Mohaimenul; Yang, Hsuan-Chia; Nguyen, Phung-Anh; Poly, Tahmina Nasrin; Huang, Chih-Wei; Kekade, Shwetambara; Khalfan, Abdulwahed Mohammed; Debnath, Tonmoy; Li, Yu-Chuan Jack; Abdul, Shabbir Syed

    2017-12-01

    The benefits of statin treatment for preventing cardiac disease are well established. However, preclinical studies suggested that statins may influence mammary cancer growth, but the clinical evidence is still inconsistent. We, therefore, performed an updated meta-analysis to provide a precise estimate of the risk of breast cancer in individuals undergoing statin therapy. For this meta-analysis, we searched PubMed, the Cochrane Library, Web of Science, Embase, and CINAHL for published studies up to January 31, 2017. Articles were included if they (1) were published in English; (2) had an observational study design with individual-level exposure and outcome data, examined the effect of statin therapy, and reported the incidence of breast cancer; and (3) reported estimates of either the relative risk, odds ratios, or hazard ratios with 95% confidence intervals (CIs). We used random-effect models to pool the estimates. Of 2754 unique abstracts, 39 were selected for full-text review, and 36 studies reporting on 121,399 patients met all inclusion criteria. The overall pooled risks of breast cancer in patients using statins were 0.94 (95% CI 0.86-1.03) in random-effect models with significant heterogeneity between estimates (I 2  = 83.79%, p = 0.0001). However, we also stratified by region, the duration of statin therapy, methodological design, statin properties, and individual stain use. Our results suggest that there is no association between statin use and breast cancer risk. However, observational studies cannot clarify whether the observed epidemiologic association is a causal effect or the result of some unmeasured confounding variable. Therefore, more research is needed.

  15. Remaining lifetime modeling using State-of-Health estimation

    Science.gov (United States)

    Beganovic, Nejra; Söffker, Dirk

    2017-08-01

    Technical systems and system's components undergo gradual degradation over time. Continuous degradation occurred in system is reflected in decreased system's reliability and unavoidably lead to a system failure. Therefore, continuous evaluation of State-of-Health (SoH) is inevitable to provide at least predefined lifetime of the system defined by manufacturer, or even better, to extend the lifetime given by manufacturer. However, precondition for lifetime extension is accurate estimation of SoH as well as the estimation and prediction of Remaining Useful Lifetime (RUL). For this purpose, lifetime models describing the relation between system/component degradation and consumed lifetime have to be established. In this contribution modeling and selection of suitable lifetime models from database based on current SoH conditions are discussed. Main contribution of this paper is the development of new modeling strategies capable to describe complex relations between measurable system variables, related system degradation, and RUL. Two approaches with accompanying advantages and disadvantages are introduced and compared. Both approaches are capable to model stochastic aging processes of a system by simultaneous adaption of RUL models to current SoH. The first approach requires a priori knowledge about aging processes in the system and accurate estimation of SoH. An estimation of SoH here is conditioned by tracking actual accumulated damage into the system, so that particular model parameters are defined according to a priori known assumptions about system's aging. Prediction accuracy in this case is highly dependent on accurate estimation of SoH but includes high number of degrees of freedom. The second approach in this contribution does not require a priori knowledge about system's aging as particular model parameters are defined in accordance to multi-objective optimization procedure. Prediction accuracy of this model does not highly depend on estimated SoH. This model

  16. Hypnosis and pain perception: An Activation Likelihood Estimation (ALE) meta-analysis of functional neuroimaging studies.

    Science.gov (United States)

    Del Casale, Antonio; Ferracuti, Stefano; Rapinesi, Chiara; De Rossi, Pietro; Angeletti, Gloria; Sani, Gabriele; Kotzalidis, Georgios D; Girardi, Paolo

    2015-12-01

    Several studies reported that hypnosis can modulate pain perception and tolerance by affecting cortical and subcortical activity in brain regions involved in these processes. We conducted an Activation Likelihood Estimation (ALE) meta-analysis on functional neuroimaging studies of pain perception under hypnosis to identify brain activation-deactivation patterns occurring during hypnotic suggestions aiming at pain reduction, including hypnotic analgesic, pleasant, or depersonalization suggestions (HASs). We searched the PubMed, Embase and PsycInfo databases; we included papers published in peer-reviewed journals dealing with functional neuroimaging and hypnosis-modulated pain perception. The ALE meta-analysis encompassed data from 75 healthy volunteers reported in 8 functional neuroimaging studies. HASs during experimentally-induced pain compared to control conditions correlated with significant activations of the right anterior cingulate cortex (Brodmann's Area [BA] 32), left superior frontal gyrus (BA 6), and right insula, and deactivation of right midline nuclei of the thalamus. HASs during experimental pain impact both cortical and subcortical brain activity. The anterior cingulate, left superior frontal, and right insular cortices activation increases could induce a thalamic deactivation (top-down inhibition), which may correlate with reductions in pain intensity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Host-Country Related Risk Factors in International Construction: Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Güzin AYDOGAN

    2014-09-01

    Full Text Available Internationalization has been on the agenda of construction firms as a strategic option in global competition. Due to globalization every sector including the construction industry has faced with high levels of competitiveness, uncertainty, and risk. International construction involves common risks to domestic construction, as well as risks that are related to the host country. These risks have serious effects on the performance of international projects. Since the sustainable competitiveness of international contractors depends largely on the effective management of these risks, their assessment becomes vital for the success of international contractors. The main aim of this study is to analyse the risks for international construction projects that are related to the host country. Meta-analysis technique is used in order to determine these risks. This paper, therefore, reviews the literature that has been published in four most respected construction and management journals, these being; Journal of Construction Engineering and Management, Journal of Management in Engineering, Construction Management and Economics, and International Journal of Project Management for the period of 2000-2010. International construction risk assessment models are also reviewed within the context of this study, since host country related risk factors were found to have serious effects on the profitability of international contractors due to literature review. As a result; political stability, law and regulations, exchange rate risk, cultural differences, inflation, expropriation, tax discrimination, language barrier, bribery and corruption, force majeure, and societal conflicts in the host country are found to be the most important risk factors in international construction. Findings of this study can be used in risk assessment models for international construction projects.

  18. Kolb's Experiential Learning Theory: A Meta-Model for Career Exploration.

    Science.gov (United States)

    Atkinson, George, Jr.; Murrell, Patricia H.

    1988-01-01

    Kolb's experiential learning theory offers the career counselor a meta-model with which to structure career exploration exercises and ensure a thorough investigation of self and the world of work in a manner that provides the client with an optimal amount of learning and personal development. (Author)

  19. Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

    Science.gov (United States)

    van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

    2015-01-01

    Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

  20. Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

    Science.gov (United States)

    Cook, James P; Mahajan, Anubha; Morris, Andrew P

    2017-02-01

    Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

  1. Systematic review with meta-analysis of the epidemiological evidence in the 1900s relating smoking to lung cancer

    Science.gov (United States)

    2012-01-01

    Background Smoking is a known lung cancer cause, but no detailed quantitative systematic review exists. We summarize evidence for various indices. Methods Papers published before 2000 describing epidemiological studies involving 100+ lung cancer cases were obtained from Medline and other sources. Studies were classified as principal, or subsidiary where cases overlapped with principal studies. Data were extracted on design, exposures, histological types and confounder adjustment. RRs/ORs and 95% CIs were extracted for ever, current and ex smoking of cigarettes, pipes and cigars and indices of cigarette type and dose–response. Meta-analyses and meta-regressions investigated how relationships varied by study and RR characteristics, mainly for outcomes exactly or closely equivalent to all lung cancer, squamous cell carcinoma (“squamous”) and adenocarcinoma (“adeno”). Results 287 studies (20 subsidiary) were identified. Although RR estimates were markedly heterogeneous, the meta-analyses demonstrated a relationship of smoking with lung cancer risk, clearly seen for ever smoking (random-effects RR 5.50, CI 5.07-5.96) current smoking (8.43, 7.63-9.31), ex smoking (4.30, 3.93-4.71) and pipe/cigar only smoking (2.92, 2.38-3.57). It was stronger for squamous (current smoking RR 16.91, 13.14-21.76) than adeno (4.21, 3.32-5.34), and evident in both sexes (RRs somewhat higher in males), all continents (RRs highest for North America and lowest for Asia, particularly China), and both study types (RRs higher for prospective studies). Relationships were somewhat stronger in later starting and larger studies. RR estimates were similar in cigarette only and mixed smokers, and similar in smokers of pipes/cigars only, pipes only and cigars only. Exceptionally no increase in adeno risk was seen for pipe/cigar only smokers (0.93, 0.62-1.40). RRs were unrelated to mentholation, and higher for non-filter and handrolled cigarettes. RRs increased with amount smoked, duration

  2. Exposure to benzene at work and the risk of leukemia: a systematic review and meta-analysis

    Directory of Open Access Journals (Sweden)

    Pukkala Eero

    2010-06-01

    Full Text Available Abstract Background A substantial number of epidemiologic studies have provided estimates of the relation between exposure to benzene at work and the risk of leukemia, but the results have been heterogeneous. To bridge this gap in knowledge, we synthesized the existing epidemiologic evidence on the relation between occupational exposure to benzene and the risk of leukemia, including all types combined and the four main subgroups acute myeloid leukemia (AML, acute lymphocytic leukemia (ALL, chronic lymphocytic leukemia (CLL, and chronic myeloid leukemia (CML. Methods A systematic literature review was carried out using two databases 'Medline' and 'Embase' from 1950 through to July 2009. We selected articles which provided information that can be used to estimate the relation between benzene exposure and cancer risk (effect size. Results In total 15 studies were identified in the search, providing 16 effect estimates for the main analysis. The summary effect size for any leukemia from the fixed-effects model was 1.40 (95% CI, 1.23-1.57, but the study-specific estimates were strongly heterogeneous (I2 = 56.5%, Q stat = 34.47, p = 0.003. The random-effects model yielded a summary- effect size estimate of 1.72 (95% CI, 1.37-2.17. Effect estimates from 9 studies were based on cumulative exposures. In these studies the risk of leukemia increased with a dose-response pattern with a summary-effect estimate of 1.64 (95% CI, 1.13-2.39 for low ( 100 ppm-years. In a meta-regression, the trend was statistically significant (P = 0.015. Use of cumulative exposure eliminated heterogeneity. The risk of AML also increased from low (1.94, 95% CI, 0.95-3.95, medium (2.32, 95% CI, 0.91-5.94 to high exposure category (3.20, 95% CI, 1.09-9.45, but the trend was not statistically significant. Conclusions Our study provides consistent evidence that exposure to benzene at work increases the risk of leukemia with a dose-response pattern. There was some evidence of an

  3. Exercise training on skill-related physical fitness in adolescents with intellectual disability: A systematic review and meta-analysis.

    Science.gov (United States)

    Jeng, Shiau-Chian; Chang, Chia-Wei; Liu, Wen-Yu; Hou, Yu-Jen; Lin, Yang-Hua

    2017-04-01

    Skill-related fitness (SRF) is a component of physical fitness related to sports or occupational performance. Adolescents with intellectual disability (ID) can take advantage of SRF for enhancing work performance and enjoying participation with peers in leisure activities. However, few studies have examined the benefits of exercise on SRF in adolescents with ID. This study synthesized the results from the reviewed studies and determined whether exercise training improves SRF in adolescents with ID. We searched ten electronic databases and used the Physiotherapy Evidence Database (PEDro) scale to assess the methodological quality of included studies. This study pooled quantitative data where possible in statistical meta-analyses and expressed the effect sizes (ESs) as Cohen's d and converted it to Hedges's g. Eighteen studies met inclusion criteria for systematic review, of which 14 for further meta-analyses. Nine meta-analyses were conducted in this study. The results supported positive exercise training effects on agility, power, RT, and speed, but not balance (Hedges's g range -1.465-0.760) in adolescents with ID. We found only a limited number of studies exhibiting high quality evidence and were being included in the meta-analyses. Therefore, the results of our systematic review and meta-analyses should be interpreted with caution. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. A consensus approach for estimating the predictive accuracy of dynamic models in biology.

    Science.gov (United States)

    Villaverde, Alejandro F; Bongard, Sophia; Mauch, Klaus; Müller, Dirk; Balsa-Canto, Eva; Schmid, Joachim; Banga, Julio R

    2015-04-01

    Mathematical models that predict the complex dynamic behaviour of cellular networks are fundamental in systems biology, and provide an important basis for biomedical and biotechnological applications. However, obtaining reliable predictions from large-scale dynamic models is commonly a challenging task due to lack of identifiability. The present work addresses this challenge by presenting a methodology for obtaining high-confidence predictions from dynamic models using time-series data. First, to preserve the complex behaviour of the network while reducing the number of estimated parameters, model parameters are combined in sets of meta-parameters, which are obtained from correlations between biochemical reaction rates and between concentrations of the chemical species. Next, an ensemble of models with different parameterizations is constructed and calibrated. Finally, the ensemble is used for assessing the reliability of model predictions by defining a measure of convergence of model outputs (consensus) that is used as an indicator of confidence. We report results of computational tests carried out on a metabolic model of Chinese Hamster Ovary (CHO) cells, which are used for recombinant protein production. Using noisy simulated data, we find that the aggregated ensemble predictions are on average more accurate than the predictions of individual ensemble models. Furthermore, ensemble predictions with high consensus are statistically more accurate than ensemble predictions with large variance. The procedure provides quantitative estimates of the confidence in model predictions and enables the analysis of sufficiently complex networks as required for practical applications. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  5. Food Groups and Risk of Hypertension: A Systematic Review and Dose-Response Meta-Analysis of Prospective Studies.

    Science.gov (United States)

    Schwingshackl, Lukas; Schwedhelm, Carolina; Hoffmann, Georg; Knüppel, Sven; Iqbal, Khalid; Andriolo, Violetta; Bechthold, Angela; Schlesinger, Sabrina; Boeing, Heiner

    2017-11-01

    The aim of this systematic review and meta-analysis was to summarize the evidence on the relation of the intakes of 12 major food groups, including whole grains, refined grains, vegetables, fruits, nuts, legumes, eggs, dairy, fish, red meat, processed meat, and sugar-sweetened beverages (SSBs) with the risk of hypertension. PubMed, Scopus, and Web of Science were searched systematically until June 2017 for prospective studies having quantitatively investigated the above-mentioned foods. We conducted meta-analysis on the highest compared with the lowest intake categories and linear and nonlinear dose-response meta-analyses to analyze the association. Summary RRs and 95% CIs were estimated by using a random-effects model. Overall, 28 reports were included in the meta-analysis. An inverse association for the risk of hypertension was observed for 30 g whole grains/d (RR: 0.92; 95% CI: 0.87, 0.98), 100 g fruits/d (RR: 0.97; 95% CI: 0.96, 0.99), 28 g nuts/d (RR: 0.70; 95% CI: 0.45, 1.08), and 200 g dairy/d (RR: 0.95; 95% CI: 0.94, 0.97), whereas a positive association for 100 g red meat/d (RR: 1.14; 95% CI: 1.02, 1.28), 50 g processed meat/d (RR: 1.12; 95% CI: 1.00, 1.26), and 250 mL SSB/d (RR: 1.07; 95% CI: 1.04, 1.10) was seen in the linear dose-response meta-analysis. Indication for nonlinear relations of the intakes of whole grains, fruits, fish, and processed meats with the risk of hypertension was detected. In summary, this comprehensive dose-response meta-analysis of 28 reports identified optimal intakes of whole grains, fruits, nuts, legumes, dairy, red and processed meats, and SSBs related to the risk of hypertension. These findings need to be seen under the light of very-low to low quality of meta-evidence. However, the findings support the current dietary guidelines in the prevention of hypertension. © 2017 American Society for Nutrition.

  6. Parameter estimation of component reliability models in PSA model of Krsko NPP

    International Nuclear Information System (INIS)

    Jordan Cizelj, R.; Vrbanic, I.

    2001-01-01

    In the paper, the uncertainty analysis of component reliability models for independent failures is shown. The present approach for parameter estimation of component reliability models in NPP Krsko is presented. Mathematical approaches for different types of uncertainty analyses are introduced and used in accordance with some predisposed requirements. Results of the uncertainty analyses are shown in an example for time-related components. As the most appropriate uncertainty analysis proved the Bayesian estimation with the numerical estimation of a posterior, which can be approximated with some appropriate probability distribution, in this paper with lognormal distribution.(author)

  7. Head Injury as a Risk Factor for Dementia and Alzheimer's Disease: A Systematic Review and Meta-Analysis of 32 Observational Studies.

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    Yanjun Li

    Full Text Available Head injury is reported to be associated with increased risks of dementia and Alzheimer's disease (AD in many but not all the epidemiological studies. We conducted a systematic review and meta-analysis to estimate the relative effect of head injury on dementia and AD risks.Relevant cohort and case-control studies published between Jan 1, 1990, and Mar 31, 2015 were searched in PubMed, Web of Science, Scopus, and ScienceDirect. We used the random-effect model in this meta-analysis to take into account heterogeneity among studies.Data from 32 studies, representing 2,013,197 individuals, 13,866 dementia events and 8,166 AD events, were included in the analysis. Overall, the pooled relative risk (RR estimates showed that head injury significantly increased the risks of any dementia (RR = 1.63, 95% CI 1.34-1.99 and AD (RR = 1.51, 95% CI 1.26-1.80, with no evidence of publication bias. However, when considering the status of unconsciousness, head injury with loss of consciousness did not show significant association with dementia (RR = 0.92, 95% CI 0.67-1.27 and AD (RR = 1.49, 95% CI 0.91-2.43. Additionally, this positive association did not reach statistical significance in female participants.The findings from this meta-analysis indicate that head injury is associated with increased risks of dementia and AD.

  8. In Sync and in Control: A Meta-Analysis of Parent-Child Positive Behavioral Synchrony and Youth Self-Regulation.

    Science.gov (United States)

    Davis, Molly; Bilms, Joanie; Suveg, Cynthia

    2017-12-01

    A growing body of research has highlighted the connection between parent-child positive behavioral synchrony and youth self-regulation; however, this association has yet to be the focus of a meta-analytic review. Therefore, the present meta-analysis aimed to estimate the magnitude of the relation between parent-child positive behavioral synchrony and youth self-regulation and to identify moderator variables that can explain the variability in the degree of this association across the extant literature. A thorough literature search of two major databases, in addition to scanning the reference sections of relevant articles, yielded a total of 10 peer-reviewed articles (24 effect sizes, 658 children) that were eligible for inclusion in the current meta-analysis. Results from the overall mean effect size calculation using a random-effects model indicated that parent-child positive behavioral synchrony was significantly, positively correlated with youth self-regulation and the effect size was medium. Children's ages at the time of synchrony and self-regulation measurements, as well as parent gender, served as significant moderator variables. Findings from the present meta-analysis can help to refine existing theoretical models on the role of the parent-child relationship in youth adjustment. Prevention and intervention efforts may benefit from an increased emphasis on building parent-child positive behavioral synchrony to promote youth self-regulation and thus children's overall well-being. © 2016 Family Process Institute.

  9. Risk of Motor Vehicle Accidents Related to Sleepiness at the Wheel: A Systematic Review and Meta-Analysis.

    Science.gov (United States)

    Bioulac, Stéphanie; Franchi, Jean-Arthur Micoulaud; Arnaud, Mickael; Sagaspe, Patricia; Moore, Nicholas; Salvo, Francesco; Philip, Pierre

    2017-10-01

    Sleepiness at the wheel is widely believed to be a cause of motor vehicle accidents. Nevertheless, a systematic review of studies investigating this relationship has not yet been published. The objective of this study was to quantify the relationship between sleepiness at the wheel and motor vehicle accidents. A systematic review was performed using Medline, Scopus, and ISI Web of Science. The outcome measure of interest was motor vehicle accident defined as involving four- or two-wheeled vehicles in road traffic, professional and nonprofessional drivers, with or without objective consequences. The exposure was sleepiness at the wheel defined as self-reported sleepiness at the wheel. Studies were included if they provided adjusted risk estimates of motor vehicle accidents related to sleepiness at the wheel. Risk estimates and 95% confidence intervals (95% CIs) were extracted and pooled as odds ratios (ORs) using a random-effect model. Heterogeneity was quantified using Q statistics and the I2 index. The potential causes of heterogeneity were investigated using meta-regressions. Ten cross-sectional studies (51,520 participants), six case-control studies (4904 participants), and one cohort study (13,674 participants) were included. Sleepiness at the wheel was associated with an increased risk of motor vehicle accidents (pooled OR 2.51 [95% CI 1.87; 3.39]). A significant heterogeneity was found between the individual risk estimates (Q = 93.21; I2 = 83%). Sleepiness at the wheel increases the risk of motor vehicle accidents and should be considered when investigating fitness to drive. Further studies are required to explore the nature of this relationship. PROSPERO 2015 CRD42015024805. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

  10. Hepatitis C in HIV-infected individuals: a systematic review and meta-analysis of estimated prevalence in Africa.

    Science.gov (United States)

    Azevedo, Tiago Castro Lopes; Zwahlen, Marcel; Rauch, Andri; Egger, Matthias; Wandeler, Gilles

    2016-01-01

    Although hepatitis C virus (HCV) screening is recommended for all HIV-infected patients initiating antiretroviral therapy, data on epidemiologic characteristics of HCV infection in resource-limited settings are scarce. We searched PubMed and EMBASE for studies assessing the prevalence of HCV infection among HIV-infected individuals in Africa and extracted data on laboratory methods used. Prevalence estimates from individual studies were combined for each country using random-effects meta-analysis. The importance of study design, population and setting as well as type of test (anti-HCV antibody tests and polymerase chain reactions) was examined with meta-regression. Three randomized controlled trials, 28 cohort studies and 121 cross-sectional analyses with 108,180 HIV-infected individuals from 35 countries were included. The majority of data came from outpatient populations (55%), followed by blood donors (15%) and pregnant women (14%). Based on estimates from 159 study populations, anti-HCV positivity prevalence ranged between 3.3% (95% confidence interval (CI) 1.8-4.7) in Southern Africa and 42.3% (95% CI 4.1-80.5) in North Africa. Study design, type of setting and age distribution did not influence this prevalence significantly. The prevalence of replicating HCV infection, estimated from data of 29 cohorts, was 2.0% (95% CI 1.5-2.6). Ten studies from nine countries reported the HCV genotype of 74 samples, 53% were genotype 1, 24% genotype 2, 14% genotype 4 and 9% genotypes 3, 5 or 6. The prevalence of anti-HCV antibodies is high in HIV-infected patients in Africa, but replicating HCV infection is rare and varies widely across countries.

  11. Are Urinary Tubular Injury Markers Useful in Chronic Kidney Disease? A Systematic Review and Meta Analysis.

    Science.gov (United States)

    Zhou, Le-Ting; Lv, Lin-Li; Pan, Ming-Ming; Cao, Yu-Han; Liu, Hong; Feng, Ye; Ni, Hai-Feng; Liu, Bi-Cheng

    2016-01-01

    Adverse outcome of chronic kidney disease, such as end stage renal disease, is a significant burden on personal health and healthcare costs. Urinary tubular injury markers, such as NGAL, KIM-1 and NAG, could provide useful prognostic value for the early identification of high-risk patients. However, discrepancies between recent large prospective studies have resulted in controversy regarding the potential clinical value of these markers. Therefore, we conducted the first meta-analysis to provide a more persuasive argument to this debate. In the current meta-analysis, based on ten prospective studies involving 29366 participants, we evaluated the role of urinary tubular injury markers (NGAL, KIM-1 and NAG) in predicting clinical outcomes including CKD stage 3, end stage renal disease and mortality. The prognostic values of these biomarkers were estimated using relative risks and 95% confidence interval in adjusted models. All risk estimates were normalized to those of 1 standard deviation increase in log-scale concentrations to minimize heterogeneity. Fixed-effects models were adopted to combine risk estimates. The quality of the research and between-study heterogeneity were evaluated. The level of research evidence was identified according to the GRADE profiler. uNGAL was identified as an independent risk predictor of ESRD (pooled adjusted relative risk: 1.40[1.21 to 1.61], pchronic kidney disease. A borderline significance of uKIM-1 in predicting CKD stage 3 independently in the community-based population was observed (pooled adjusted relative risk: 1.13[1.00 to 1.27], p = 0.057). Only the prognostic value of uNGAL for ESRD was supported by a grade B level of evidence. The concentration of uNGAL can be used in practice as an independent predictor of end stage renal disease among patients with chronic kidney disease, but it may be not useful in predicting disease progression to CKD stage 3 among community-based population.

  12. Estimation of a multivariate mean under model selection uncertainty

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    Georges Nguefack-Tsague

    2014-05-01

    Full Text Available Model selection uncertainty would occur if we selected a model based on one data set and subsequently applied it for statistical inferences, because the "correct" model would not be selected with certainty.  When the selection and inference are based on the same dataset, some additional problems arise due to the correlation of the two stages (selection and inference. In this paper model selection uncertainty is considered and model averaging is proposed. The proposal is related to the theory of James and Stein of estimating more than three parameters from independent normal observations. We suggest that a model averaging scheme taking into account the selection procedure could be more appropriate than model selection alone. Some properties of this model averaging estimator are investigated; in particular we show using Stein's results that it is a minimax estimator and can outperform Stein-type estimators.

  13. ALE Meta-Analysis of Schizophrenics Performing the N-Back Task

    Science.gov (United States)

    Harrell, Zachary

    2010-10-01

    MRI/fMRI has already proven itself as a valuable tool in the diagnosis and treatment of many illnesses of the brain, including cognitive problems. By exploiting the differences in magnetic susceptibility between oxygenated and deoxygenated hemoglobin, fMRI can measure blood flow in various regions of interest within the brain. This can determine the level of brain activity in relation to motor or cognitive functions and provide a metric for tissue damage or illness symptoms. Structural imaging techniques have shown lesions or deficiencies in tissue volumes in schizophrenics corresponding to areas primarily in the frontal and temporal lobes. These areas are currently known to be involved in working memory and attention, which many schizophrenics have trouble with. The ALE (Activation Likelihood Estimation) Meta-Analysis is able to statistically determine the significance of brain area activations based on the post-hoc combination of multiple studies. This process is useful for giving a general model of brain function in relation to a particular task designed to engage the affected areas (such as working memory for the n-back task). The advantages of the ALE Meta-Analysis include elimination of single subject anomalies, elimination of false/extremely weak activations, and verification of function/location hypotheses.

  14. A review of cognitive conflicts research: a meta-analytic study of prevalence and relation to symptoms

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    Montesano A

    2015-12-01

    Full Text Available Adrián Montesano,1 María Angeles López-González,2 Luis Angel Saúl,2 Guillem Feixas1 1Department of Personality, Assessment and Psychological Treatments, University of Barcelona, Barcelona, 2Department of Personality, Assessment and Psychological Treatments, Faculty of Psychology, National Distance Education University, Madrid, Spain Abstract: Recent research has highlighted the role of implicative dilemmas in a variety of clinical conditions. These dilemmas are a type of cognitive conflict, in which different aspects of the self are countered in such a way that a desired change in a personal dimension (eg, symptom improvement may be hindered by the need of personal coherence in another dimension. The aim of this study was to summarize, using a meta-analytical approach, the evidence relating to the presence and the level of this conflict, as well as its relationship with well-being, in various clinical samples. A systematic review using multiple electronic databases found that out of 37 articles assessed for eligibility, nine fulfilled the inclusion criteria for meta-analysis. Random effects model was applied when computing mean effect sizes and testing for heterogeneity level. Statistically significant associations were observed between the clinical status and the presence of dilemmas, as well as level of conflict across several clinical conditions. Likewise, the level of conflict was associated with symptom severity. Results highlighted the clinical relevance and the transdiagnostic nature of implicative dilemmas. Keywords: implicative dilemmas, cognitive conflicts, intrapersonal conflicts, meta-analysis

  15. Tackling Biocomplexity with Meta-models for Species Risk Assessment

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    Philip J. Nyhus

    2007-06-01

    Full Text Available We describe results of a multi-year effort to strengthen consideration of the human dimension into endangered species risk assessments and to strengthen research capacity to understand biodiversity risk assessment in the context of coupled human-natural systems. A core group of social and biological scientists have worked with a network of more than 50 individuals from four countries to develop a conceptual framework illustrating how human-mediated processes influence biological systems and to develop tools to gather, translate, and incorporate these data into existing simulation models. A central theme of our research focused on (1 the difficulties often encountered in identifying and securing diverse bodies of expertise and information that is necessary to adequately address complex species conservation issues; and (2 the development of quantitative simulation modeling tools that could explicitly link these datasets as a way to gain deeper insight into these issues. To address these important challenges, we promote a "meta-modeling" approach where computational links are constructed between discipline-specific models already in existence. In this approach, each model can function as a powerful stand-alone program, but interaction between applications is achieved by passing data structures describing the state of the system between programs. As one example of this concept, an integrated meta-model of wildlife disease and population biology is described. A goal of this effort is to improve science-based capabilities for decision making by scientists, natural resource managers, and policy makers addressing environmental problems in general, and focusing on biodiversity risk assessment in particular.

  16. Meta-Analyst: software for meta-analysis of binary, continuous and diagnostic data

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    Schmid Christopher H

    2009-12-01

    Full Text Available Abstract Background Meta-analysis is increasingly used as a key source of evidence synthesis to inform clinical practice. The theory and statistical foundations of meta-analysis continually evolve, providing solutions to many new and challenging problems. In practice, most meta-analyses are performed in general statistical packages or dedicated meta-analysis programs. Results Herein, we introduce Meta-Analyst, a novel, powerful, intuitive, and free meta-analysis program for the meta-analysis of a variety of problems. Meta-Analyst is implemented in C# atop of the Microsoft .NET framework, and features a graphical user interface. The software performs several meta-analysis and meta-regression models for binary and continuous outcomes, as well as analyses for diagnostic and prognostic test studies in the frequentist and Bayesian frameworks. Moreover, Meta-Analyst includes a flexible tool to edit and customize generated meta-analysis graphs (e.g., forest plots and provides output in many formats (images, Adobe PDF, Microsoft Word-ready RTF. The software architecture employed allows for rapid changes to be made to either the Graphical User Interface (GUI or to the analytic modules. We verified the numerical precision of Meta-Analyst by comparing its output with that from standard meta-analysis routines in Stata over a large database of 11,803 meta-analyses of binary outcome data, and 6,881 meta-analyses of continuous outcome data from the Cochrane Library of Systematic Reviews. Results from analyses of diagnostic and prognostic test studies have been verified in a limited number of meta-analyses versus MetaDisc and MetaTest. Bayesian statistical analyses use the OpenBUGS calculation engine (and are thus as accurate as the standalone OpenBUGS software. Conclusion We have developed and validated a new program for conducting meta-analyses that combines the advantages of existing software for this task.

  17. Updated meta-analysis of the relation between heart disease and androgenic alopecia or alopecia areata

    Directory of Open Access Journals (Sweden)

    Misato Amamoto

    2018-01-01

    Full Text Available Background The relationship between baldness and heart disease is still controversial. We performed an updated meta-analysis of observational studies to evaluate the relation between heart disease and androgenic alopecia or alopecia areata. Aims To evaluate the relation between heart disease and androgenic alopecia or alopecia areata. Methods Studies were identified by searching Medline and Embase up to October 20, 2017 without language restriction. Metaanalysis was performed by using a random-effects model. Results Nine studies were included in the meta-analysis (eight on androgenic alopecia and one on alopecia areata: 44,806 participants. Compared to men without baldness, men with androgenic alopecia had an increased risk of heart disease (relative risk (RR: 1.32, 95 per cent CI: 1.08 to 1.63, p=0.01, I2 =25 per cent, and younger men (<55 or ≤60 years showed a stronger association (RR: 1.44, 95 per cent CI: 1.11 to 1.86, p=0.01, I2 =0 per cent. The positive relation depended on the severity of baldness and decreased in order of severe vertex (RR: 1.60, 95 per cent CI: 1.19 to 2.16, p=0.002, moderate vertex (RR: 1.41, 95 per cent CI: 1.22 to 1.64, p<0.001, mild vertex (RR: 1.18, 95 per cent CI: 1.05 to 1.33, p=0.007, and frontal baldness (RR: 1.10, 95 per cent CI: 0.92 to 1.32, p=0.28. In contrast, there was no significant relation between alopecia areata and heart disease (RR: 0.91, 95 per cent CI: 0.60 to 1.39, p=0.66. Conclusion Androgenic alopecia is associated with heart disease, but alopecia areata is not.

  18. Meta-Analysis of the Related Nutritional Supplements Dimethyl Sulfoxide and Methylsulfonylmethane in the Treatment of Osteoarthritis of the Knee

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    Sarah Brien

    2011-01-01

    Full Text Available Dimethyl sulphoxide and methylsulfonylmethane are two related nutritional supplements used for symptomatic relief of osteoarthritis (OA. We conducted a meta-analysis to evaluate their efficacy in reducing pain associated with OA. Randomized or quasi-randomized controlled trials (RCTs, identified by systematic electronic searches, citation tracking and searches of clinical trial registries, assessing these supplements in osteoarthritis of any joint were considered for inclusion. Meta-analysis, based on difference in mean pain related outcomes between treatment and comparator groups, was carried out based on a random effect model. Seven potential trials were identified of which three RCTs, two DMSO and one MSM (total N=326 patients were eligible for inclusion. All three trials were considered high methodological quality. A significant degree of heterogeneity (χ2=6.28, P=.043 was revealed. Two studies demonstrated statistically significant (but not clinically relevant reduction in pain compared with controls; with one showing no group difference. The meta-analysis confirmed a non significant reduction of pain on visual analogue scale of 6.34 mm (SE = 3.49, 95% CI, −0.49, 13.17. The overall effect size of 1.82 was neither statistically nor clinically significant. Current evidence suggests DMSO and MSM are not clinically effective in the reduction of pain in the treatment of OA. No definitive conclusions can currently be drawn from the data due to the mixed findings and the use of inadequate dosing periods.

  19. Estimating the proportion of persons with diabetes developing diabetic retinopathy in India: A systematic review and meta-analysis

    Directory of Open Access Journals (Sweden)

    A T Jotheeswaran

    2016-01-01

    Full Text Available Background: Available evidence from India shows that the control of diabetes is poor in majority of the population. This escalates the risk of complications. There is no systematic review to estimate the magnitude of diabetic retinopathy (DR in India. Materials and Methods: A systematic literature search was carried out in Ovid Medline and EMBASE databases using Mesh and key search terms. Studies which reported the proportion of people with diabetes with DR in a representative community population were included. Two independent reviewers reviewed all the retrieved publications. Data were extracted using a predefined form. Review Manager software was used to perform meta-analysis to provide a pooled estimate. Studies included were assessed for methodological quality using selected items from the STROBE checklist. Results: Seven studies (1999–2014; n = 8315 persons with diabetes were included in the review. In the meta-analysis, 14.9% (95% confidence interval [CI] 10.7–19.0% of known diabetics aged ≥30 years and 18.1% (95% CI 14.8–21.4 among those aged ≥50 years had DR. Heterogeneity around this estimate ranged from I2= 79–87%. No linear trend was observed between age and the proportion with DR. The overall methodological quality of included studies was moderate. Conclusions: Early detection of DR is currently not prioritized in public health policies for noncommunicable diseases and blindness programs. Methodological issues in studies suggest that the proportion of diabetics with DR is underestimated in the Indian population. Future research should emphasize more robust methodology for assessing diabetes and DR status.

  20. Wood dust exposure and lung cancer risk: a meta-analysis.

    Science.gov (United States)

    Hancock, David G; Langley, Mary E; Chia, Kwan Leung; Woodman, Richard J; Shanahan, E Michael

    2015-12-01

    Occupational lung cancers represent a major health burden due to their increasing prevalence and poor long-term outcomes. While wood dust is a confirmed human carcinogen, its association with lung cancer remains unclear due to inconsistent findings in the literature. We aimed to clarify this association using meta-analysis. We performed a search of 10 databases to identify studies published until June 2014. We assessed the lung cancer risk associated with wood dust exposure as the primary outcome and with wood dust-related occupations as a secondary outcome. Random-effects models were used to pool summary risk estimates. 85 publications were included in the meta-analysis. A significantly increased risk for developing lung cancer was observed among studies that directly assessed wood dust exposure (RR 1.21, 95% CI 1.05 to 1.39, n=33) and that assessed wood dust-related occupations (RR 1.15, 95% CI 1.07 to 1.23, n=59). In contrast, a reduced risk for lung cancer was observed among wood dust (RR 0.63, 95% CI 0.39 to 0.99, n=5) and occupation (RR 0.96, 95% CI 0.95 to 0.98, n=1) studies originating in Nordic countries, where softwood dust is the primary exposure. These results were independent of the presence of adjustment for smoking and exposure classification methods. Only minor differences in risk between the histological subtypes were identified. This meta-analysis provides strong evidence for an association between wood dust and lung cancer, which is critically influenced by the geographic region of the study. The reasons for this region-specific effect estimates remain to be clarified, but may suggest a differential effect for hardwood and softwood dusts. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  1. Breastfeeding and intelligence: a systematic review and meta-analysis.

    Science.gov (United States)

    Horta, Bernardo L; Loret de Mola, Christian; Victora, Cesar G

    2015-12-01

    This study was aimed at systematically reviewing evidence of the association between breastfeeding and performance in intelligence tests. Two independent searches were carried out using Medline, LILACS, SCIELO and Web of Science. Studies restricted to infants and those where estimates were not adjusted for stimulation or interaction at home were excluded. Fixed- and random-effects models were used to pool the effect estimates, and a random-effects regression was used to assess potential sources of heterogeneity. We included 17 studies with 18 estimates of the relationship between breastfeeding and performance in intelligence tests. In a random-effects model, breastfed subjects achieved a higher IQ [mean difference: 3.44 points (95% confidence interval: 2.30; 4.58)]. We found no evidence of publication bias. Studies that controlled for maternal IQ showed a smaller benefit from breastfeeding [mean difference 2.62 points (95% confidence interval: 1.25; 3.98)]. In the meta-regression, none of the study characteristics explained the heterogeneity among the studies. Breastfeeding is related to improved performance in intelligence tests. A positive effect of breastfeeding on cognition was also observed in a randomised trial. This suggests that the association is causal. ©2015 The Authors. Acta Paediatrica published by John Wiley & Sons Ltd on behalf of Foundation Acta Paediatrica.

  2. Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

    Science.gov (United States)

    Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

    2014-07-21

    Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on

  3. A Meta-analysis of the Association of Estimated GFR, Albuminuria, Diabetes Mellitus, and Hypertension With Acute Kidney Injury.

    Science.gov (United States)

    James, Matthew T; Grams, Morgan E; Woodward, Mark; Elley, C Raina; Green, Jamie A; Wheeler, David C; de Jong, Paul; Gansevoort, Ron T; Levey, Andrew S; Warnock, David G; Sarnak, Mark J

    2015-10-01

    Diabetes mellitus and hypertension are risk factors for acute kidney injury (AKI). Whether estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio (ACR) remain risk factors for AKI in the presence and absence of these conditions is uncertain. Meta-analysis of cohort studies. 8 general-population (1,285,045 participants) and 5 chronic kidney disease (CKD; 79,519 participants) cohorts. Cohorts participating in the CKD Prognosis Consortium. Diabetes and hypertension status, eGFR by the 2009 CKD Epidemiology Collaboration creatinine equation, urine ACR, and interactions. Hospitalization with AKI, using Cox proportional hazards models to estimate HRs of AKI and random-effects meta-analysis to pool results. During a mean follow-up of 4 years, there were 16,480 episodes of AKI in the general-population and 2,087 episodes in the CKD cohorts. Low eGFRs and high ACRs were associated with higher risks of AKI in individuals with or without diabetes and with or without hypertension. When compared to a common reference of eGFR of 80mL/min/1.73m(2) in nondiabetic patients, HRs for AKI were generally higher in diabetic patients at any level of eGFR. The same was true for diabetic patients at all levels of ACR compared with nondiabetic patients. The risk gradient for AKI with lower eGFRs was greater in those without diabetes than with diabetes, but similar with higher ACRs in those without versus with diabetes. Those with hypertension had a higher risk of AKI at eGFRs>60mL/min/1.73m(2) than those without hypertension. However, risk gradients for AKI with both lower eGFRs and higher ACRs were greater for those without than with hypertension. AKI identified by diagnostic code. Lower eGFRs and higher ACRs are associated with higher risks of AKI among individuals with or without either diabetes or hypertension. Copyright © 2015 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

  4. Substantia nigra fractional anisotropy is not a diagnostic biomarker of Parkinson's disease: A diagnostic performance study and meta-analysis

    Energy Technology Data Exchange (ETDEWEB)

    Hirata, Fabiana C.C.; Vieira, Gilson; Lucato, Leandro T.; Leite, Claudia C.; Pastorello, Bruno F.; Otaduy, Maria C.G.; Chaim, Khallil T.; Campanholo, Kenia R. [University of Sao Paulo, LIM-44, Department of Radiology, Sao Paulo, SP (Brazil); Sato, Joao R. [University of Sao Paulo, LIM-44, Department of Radiology, Sao Paulo, SP (Brazil); Universidade Federal do ABC, Center of Mathematics, Computation and Cognition, Santo Andre (Brazil); Bor-Seng-Shu, Edson; Novaes, Natalia P. [Hospital Israelita Albert Einstein, Sao Paulo (Brazil); University of Sao Paulo, Department of Neurology, Sao Paulo (Brazil); Magalhaes Melo, Luciano; Goncalves, Marcia R.; Reis Barbosa, Egberto [University of Sao Paulo, Department of Neurology, Sao Paulo (Brazil); Pereira do Nascimento, Felipe Barjud; Amaro, Edson [University of Sao Paulo, LIM-44, Department of Radiology, Sao Paulo, SP (Brazil); Hospital Israelita Albert Einstein, Sao Paulo (Brazil); Jacobsen Teixeira, Manoel [University of Sao Paulo, Department of Neurosurgery, Sao Paulo (Brazil); Cardoso, Ellison Fernando [University of Sao Paulo, LIM-44, Department of Radiology, Sao Paulo, SP (Brazil); Hospital Israelita Albert Einstein, Sao Paulo (Brazil); Institute of Mathematics and Statistics University of Sao Paulo (IME-USP), Sao Paulo (Brazil)

    2017-06-15

    Our goal was to estimate the diagnostic accuracy of substantia nigra fractional anisotropy (SN-FA) for Parkinson's disease (PD) diagnosis in a sample similar to the clinical setting, including patients with essential tremor (ET) and healthy controls (HC). We also performed a systematic review and meta-analysis to estimate mean change in SN-FA induced by PD and its diagnostic accuracy. Our sample consisted of 135 subjects: 72 PD, 21 ET and 42 HC. To address inter-scanner variability, two 3.0-T MRI scans were performed. MRI results of this sample were pooled into a meta-analysis that included 1,432 subjects (806 PD and 626 HC). A bivariate model was used to evaluate diagnostic accuracy measures. In our sample, we did not observe a significant effect of disease on SN-FA and it was uninformative for diagnosis. The results of the meta-analysis estimated a 0.03 decrease in mean SN-FA in PD relative to HC (CI: 0.01-0.05). However, the discriminatory capability of SN-FA to diagnose PD was low: pooled sensitivity and specificity were 72 % (CI: 68-75) and 63 % (CI: 58-70), respectively. There was high heterogeneity between studies (I{sup 2} = 91.9 %). SN-FA cannot be used as an isolated measure to diagnose PD. (orig.)

  5. The problem of multicollinearity in horizontal solar radiation estimation models and a new model for Turkey

    International Nuclear Information System (INIS)

    Demirhan, Haydar

    2014-01-01

    Highlights: • Impacts of multicollinearity on solar radiation estimation models are discussed. • Accuracy of existing empirical models for Turkey is evaluated. • A new non-linear model for the estimation of average daily horizontal global solar radiation is proposed. • Estimation and prediction performance of the proposed and existing models are compared. - Abstract: Due to the considerable decrease in energy resources and increasing energy demand, solar energy is an appealing field of investment and research. There are various modelling strategies and particular models for the estimation of the amount of solar radiation reaching at a particular point over the Earth. In this article, global solar radiation estimation models are taken into account. To emphasize severity of multicollinearity problem in solar radiation estimation models, some of the models developed for Turkey are revisited. It is observed that these models have been identified as accurate under certain multicollinearity structures, and when the multicollinearity is eliminated, the accuracy of these models is controversial. Thus, a reliable model that does not suffer from multicollinearity and gives precise estimates of global solar radiation for the whole region of Turkey is necessary. A new nonlinear model for the estimation of average daily horizontal solar radiation is proposed making use of the genetic programming technique. There is no multicollinearity problem in the new model, and its estimation accuracy is better than the revisited models in terms of numerous statistical performance measures. According to the proposed model, temperature, precipitation, altitude, longitude, and monthly average daily extraterrestrial horizontal solar radiation have significant effect on the average daily global horizontal solar radiation. Relative humidity and soil temperature are not included in the model due to their high correlation with precipitation and temperature, respectively. While altitude has

  6. Compulsivity-related neurocognitive performance deficits in gambling disorder: A systematic review and meta-analysis.

    Science.gov (United States)

    van Timmeren, Tim; Daams, Joost G; van Holst, Ruth J; Goudriaan, Anna E

    2018-01-01

    Compulsivity is a core feature of addictive disorders, including gambling disorder. However, it is unclear to what extent this compulsive behavior in gambling disorder is associated with abnormal compulsivity-related neurocognitive functioning. Here, we summarize and synthesize the evidence for compulsive behavior, as assessed by compulsivity-related neurocognitive tasks, in individuals with gambling disorder compared to healthy controls (HCs). A total of 29 studies, comprising 41 task-results, were included in the systematic review; 32 datasets (n=1072 individuals with gambling disorder; n=1312 HCs) were also included in the meta-analyses, conducted for each cognitive task separately. Our meta-analyses indicate significant deficits in individuals with gambling disorder in cognitive flexibility, attentional set-shifting, and attentional bias. Overall, these findings support the idea that compulsivity-related performance deficits characterize gambling disorder. This association may provide a possible link between impairments in executive functions related to compulsive action. We discuss the practical relevance of these results, their implications for our understanding of gambling disorder and how they relate to neurobiological factors and other 'disorders of compulsivity'. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  7. Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data

    Directory of Open Access Journals (Sweden)

    Ghosh Debashis

    2004-12-01

    Full Text Available Abstract Background An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. Results By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. Conclusion The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta

  8. Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

    Directory of Open Access Journals (Sweden)

    Miranda van Uitert

    Full Text Available Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite and protein-protein associations (STRING. This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome. The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300 and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

  9. Asymmetric and symmetric meta-correlations in financial markets

    International Nuclear Information System (INIS)

    Li Xiaohui; Shen Xiangying; Huang Jiping

    2016-01-01

    In financial markets, the relation between fluctuations of stock prices and trading behaviors is complex. It is intriguing to quantify this kind of meta-correlation between market fluctuations and the synchronous behaviors. We refine the theoretical index leverage model proposed by Reigneron et al. , to exactly quantify the meta-correlation under various levels of price fluctuations [Reigneron P A, Allez R and Bouchaud J P 2011 Physica A 390 3026]. The characteristics of meta-correlations in times of market losses, are found to be significantly different in Chinese and American financial markets. In addition, unlike the asymmetric results at the daily scale, the correlation behaviors are found to be symmetric at the high-frequency scale. (paper)

  10. Systematic review using meta-analyses to estimate dose-response relationships between iodine intake and biomarkers of iodine status in different population groups.

    Science.gov (United States)

    Ristić-Medić, Danijela; Dullemeijer, Carla; Tepsić, Jasna; Petrović-Oggiano, Gordana; Popović, Tamara; Arsić, Aleksandra; Glibetić, Marija; Souverein, Olga W; Collings, Rachel; Cavelaars, Adriënne; de Groot, Lisette; van't Veer, Pieter; Gurinović, Mirjana

    2014-03-01

    The objective of this systematic review was to identify studies investigating iodine intake and biomarkers of iodine status, to assess the data of the selected studies, and to estimate dose-response relationships using meta-analysis. All randomized controlled trials, prospective cohort studies, nested case-control studies, and cross-sectional studies that supplied or measured dietary iodine and measured iodine biomarkers were included. The overall pooled regression coefficient (β) and the standard error of β were calculated by random-effects meta-analysis on a double-log scale, using the calculated intake-status regression coefficient (β) for each individual study. The results of pooled randomized controlled trials indicated that the doubling of dietary iodine intake increased urinary iodine concentrations by 14% in children and adolescents, by 57% in adults and the elderly, and by 81% in pregnant women. The dose-response relationship between iodine intake and biomarkers of iodine status indicated a 12% decrease in thyroid-stimulating hormone and a 31% decrease in thyroglobulin in pregnant women. The model of dose-response quantification used to describe the relationship between iodine intake and biomarkers of iodine status may be useful for providing complementary evidence to support recommendations for iodine intake in different population groups.

  11. Reasoned versus reactive prediction of behaviour: a meta-analysis of the prototype willingness model.

    Science.gov (United States)

    Todd, Jemma; Kothe, Emily; Mullan, Barbara; Monds, Lauren

    2016-01-01

    The prototype willingness model (PWM) was designed to extend expectancy-value models of health behaviour by also including a heuristic, or social reactive pathway, to better explain health-risk behaviours in adolescents and young adults. The pathway includes prototype, i.e., images of a typical person who engages in a behaviour, and willingness to engage in behaviour. The current study describes a meta-analysis of predictive research using the PWM and explores the role of the heuristic pathway and intentions in predicting behaviour. Eighty-one studies met inclusion criteria. Overall, the PWM was supported and explained 20.5% of the variance in behaviour. Willingness explained 4.9% of the variance in behaviour over and above intention, although intention tended to be more strongly related to behaviour than was willingness. The strength of the PWM relationships tended to vary according to the behaviour being tested, with alcohol consumption being the behaviour best explained. Age was also an important moderator, and, as expected, PWM behaviour was best accounted for within adolescent samples. Results were heterogeneous even after moderators were taken into consideration. This meta-analysis provides support for the PWM and may be used to inform future interventions that can be tailored for at-risk populations.

  12. A systematic review and meta-analysis of factors that relate to aggression perpetrated against nurses by patients/relatives or staff.

    Science.gov (United States)

    Edward, Karen-leigh; Stephenson, John; Ousey, Karen; Lui, Steve; Warelow, Philip; Giandinoto, Jo-Ann

    2016-02-01

    The aim of this meta-analysis was to identify the factors that related to aggression (verbal abuse or physical abuse/assault) perpetrated against the nurse or other health professionals by patients/relatives or staff. In the light of the paucity of systematic reviews on this common issue in nursing, the objective was to present a comprehensive systematic review and meta-analysis of these papers. Aggression towards nurses is common around the world and can be the impetus for nurses leaving the profession or developing anxiety when working in particular settings. Systematic review with meta-analysis. Meta-analyses were conducted to assess the effect of the factors of gender and context (dichotomised as mental health/psychiatric or nonmental health/psychiatric). The databases of Medline (1966-2015), CINAHL (1982-2015) and PsychInfo (1920-2015). A total of 1571 papers were screened by two reviewers. At the final decision 14 were selected for analysis. A higher proportion of female nurses than male nurses were reported to be the victims of verbal abuse, with the difference in proportions being statistically significant. A statistically significant higher proportion of male nurses than female nurses were reported to be the victims of physical abuse. There was a significantly higher proportion of mental health nurses reported experiencing physical abuse as compared to nonmental health nurses. The analysis reveal female nurses have greater odds of verbal abuse than male nurses and male nurses have greater odds of physical abuse than female nurses. Overall mental health nurses had three times higher odds of physical assault than other nurses. In the light of the findings it is recommended organisational support improve in high aggression potential clinical areas and for nursing curriculums to incorporate education about the management of challenging behaviours in undergraduate programmes. © 2015 John Wiley & Sons Ltd.

  13. Confectionery consumption and overweight, obesity, and related outcomes in children and adolescents: a systematic review and meta-analysis.

    Science.gov (United States)

    Gasser, Constantine E; Mensah, Fiona K; Russell, Melissa; Dunn, Sophie E; Wake, Melissa

    2016-05-01

    Many calorie-rich dietary components contribute to obesity. However, the contribution of confectionery to obesity in children and adolescents has not been well established. In this systematic review and meta-analysis, we hypothesized that higher total, chocolate, and nonchocolate confectionery consumption would be associated with higher odds of overweight, obesity, and other obesity-related outcomes [body mass index (BMI), BMI z score, body composition, waist circumference, and percentage body fat] in children and adolescents. We searched Scopus, PubMed, and reference lists of pertinent reviews, supplemented by expert contact, for randomized controlled trials (RCTs) and observational studies published between 1990 and 31 March 2015, and we conducted separate meta-analyses for categorical and continuous ORs and for total, chocolate, and nonchocolate confectioneries with the use of a random-effects model. A total of 19 studies were included in the systematic review, and the cross-sectional results of 11 studies (∼177,260 participants) were included in the meta-analysis. In the meta-analysis, which examined the combined outcome of overweight and obesity, the odds of overweight or obesity were 18% lower (OR: 0.82; 95% CI: 0.69, 0.97) for subjects in the highest category of consumption than for a reference category of consumption. Thus, a 1-time/wk or a 1-U increase in consumption was associated with a 13% (OR: 0.87; 95% CI: 0.85, 0.88) decrease in the odds of overweight or obesity. Associations were similarly inverse for chocolate and nonchocolate confectioneries. In the longitudinal studies and the RCT included in the review, no associations were observed between confectionery consumption and overweight, obesity, or obesity-related outcomes. Instead of overweight and obese children and adolescents having higher confectionery intakes, this review shows the reverse effect. This result might reflect a true inverse association, reverse causality, or differential

  14. Hypnotherapy for disability-related pain: A meta-analysis.

    Science.gov (United States)

    Bowker, Emma; Dorstyn, Diana

    2016-04-01

    Hypnotherapy can address the biopsychosocial aspects of disability-related pain, although the available evidence is limited in quality and quantity. Meta-analytic techniques were utilised to evaluate 10 controlled studies. Hypnotherapy produced significant short-term improvements in fatigue, pain experience and affect. However, a lack of significance was noted at 3- to 6-month follow-up. A beneficial effect size (d(w)= 0.53; confidence interval = 0.28-0.84) in comparison to control conditions was reported, although comparability with other cognitive-behavioural treatments could not be confirmed across the few studies reporting this data (d(w)= 0.06; confidence interval = -0.33 to 0.45). The findings highlight the need for further controlled and longitudinal research in this area. © The Author(s) 2014.

  15. Weighing Evidence "Steampunk" Style via the Meta-Analyser.

    Science.gov (United States)

    Bowden, Jack; Jackson, Chris

    2016-10-01

    The funnel plot is a graphical visualization of summary data estimates from a meta-analysis, and is a useful tool for detecting departures from the standard modeling assumptions. Although perhaps not widely appreciated, a simple extension of the funnel plot can help to facilitate an intuitive interpretation of the mathematics underlying a meta-analysis at a more fundamental level, by equating it to determining the center of mass of a physical system. We used this analogy to explain the concepts of weighing evidence and of biased evidence to a young audience at the Cambridge Science Festival, without recourse to precise definitions or statistical formulas and with a little help from Sherlock Holmes! Following on from the science fair, we have developed an interactive web-application (named the Meta-Analyser) to bring these ideas to a wider audience. We envisage that our application will be a useful tool for researchers when interpreting their data. First, to facilitate a simple understanding of fixed and random effects modeling approaches; second, to assess the importance of outliers; and third, to show the impact of adjusting for small study bias. This final aim is realized by introducing a novel graphical interpretation of the well-known method of Egger regression.

  16. A Bayesian model averaging approach for estimating the relative risk of mortality associated with heat waves in 105 U.S. cities.

    Science.gov (United States)

    Bobb, Jennifer F; Dominici, Francesca; Peng, Roger D

    2011-12-01

    Estimating the risks heat waves pose to human health is a critical part of assessing the future impact of climate change. In this article, we propose a flexible class of time series models to estimate the relative risk of mortality associated with heat waves and conduct Bayesian model averaging (BMA) to account for the multiplicity of potential models. Applying these methods to data from 105 U.S. cities for the period 1987-2005, we identify those cities having a high posterior probability of increased mortality risk during heat waves, examine the heterogeneity of the posterior distributions of mortality risk across cities, assess sensitivity of the results to the selection of prior distributions, and compare our BMA results to a model selection approach. Our results show that no single model best predicts risk across the majority of cities, and that for some cities heat-wave risk estimation is sensitive to model choice. Although model averaging leads to posterior distributions with increased variance as compared to statistical inference conditional on a model obtained through model selection, we find that the posterior mean of heat wave mortality risk is robust to accounting for model uncertainty over a broad class of models. © 2011, The International Biometric Society.

  17. Meta-analýza cenové elasticity poptávky po alkoholu

    OpenAIRE

    Fanta, Nicolas

    2014-01-01

    The own-price elasticity is considered to be one of the key factors describing the demand for alcohol. There have been many estimates computed by now but only a few studies tried to analyse them. The aim of this meta-analysis is to discover more about the eventual effects that publication bias might have in the alcohol-related literature. The first part describes the various types of elasticities and the methods of estimation. This study is estimating the so called true effect elasticity in o...

  18. Trial Sequential Analysis in systematic reviews with meta-analysis

    Directory of Open Access Journals (Sweden)

    Jørn Wetterslev

    2017-03-01

    Full Text Available Abstract Background Most meta-analyses in systematic reviews, including Cochrane ones, do not have sufficient statistical power to detect or refute even large intervention effects. This is why a meta-analysis ought to be regarded as an interim analysis on its way towards a required information size. The results of the meta-analyses should relate the total number of randomised participants to the estimated required meta-analytic information size accounting for statistical diversity. When the number of participants and the corresponding number of trials in a meta-analysis are insufficient, the use of the traditional 95% confidence interval or the 5% statistical significance threshold will lead to too many false positive conclusions (type I errors and too many false negative conclusions (type II errors. Methods We developed a methodology for interpreting meta-analysis results, using generally accepted, valid evidence on how to adjust thresholds for significance in randomised clinical trials when the required sample size has not been reached. Results The Lan-DeMets trial sequential monitoring boundaries in Trial Sequential Analysis offer adjusted confidence intervals and restricted thresholds for statistical significance when the diversity-adjusted required information size and the corresponding number of required trials for the meta-analysis have not been reached. Trial Sequential Analysis provides a frequentistic approach to control both type I and type II errors. We define the required information size and the corresponding number of required trials in a meta-analysis and the diversity (D2 measure of heterogeneity. We explain the reasons for using Trial Sequential Analysis of meta-analysis when the actual information size fails to reach the required information size. We present examples drawn from traditional meta-analyses using unadjusted naïve 95% confidence intervals and 5% thresholds for statistical significance. Spurious conclusions in

  19. Working covariance model selection for generalized estimating equations.

    Science.gov (United States)

    Carey, Vincent J; Wang, You-Gan

    2011-11-20

    We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice. Copyright © 2011 John Wiley & Sons, Ltd.

  20. Meta-analysis for evidence synthesis in plant pathology: an overview.

    Science.gov (United States)

    Madden, L V; Paul, P A

    2011-01-01

    Meta-analysis is the analysis of the results of multiple studies, which is typically performed in order to synthesize evidence from many possible sources in a formal probabilistic manner. In a simple sense, the outcome of each study becomes a single observation in the meta-analysis of all available studies. The methodology was developed originally in the social sciences by Smith, Glass, Rosenthal, Hunter, and Schmidt, based on earlier pioneering contributions in statistics by Fisher, Pearson, Yates, and Cochran, but this approach to research synthesis has now been embraced within many scientific disciplines. However, only a handful of articles have been published in plant pathology and related fields utilizing meta-analysis. After reviewing basic concepts and approaches, methods for estimating parameters and interpreting results are shown. The advantages of meta-analysis are presented in terms of prediction and risk analysis, and the high statistical power that can be achieved for detecting significant effects of treatments or significant relationships between variables. Based on power considerations, the fallacy of naïve counting of P values in a narrative review is demonstrated. Although there are many advantages to meta-analysis, results can be biased if the analysis is based on a nonrepresentative sample of study outcomes. Therefore, novel approaches for characterizing the upper bound on the bias are discussed, in order to show the robustness of meta-analysis to possible violation of assumptions.

  1. Prevalence of rapid eye movement sleep behavior disorder (RBD) in Parkinson's disease: a meta and meta-regression analysis.

    Science.gov (United States)

    Zhang, Xiaona; Sun, Xiaoxuan; Wang, Junhong; Tang, Liou; Xie, Anmu

    2017-01-01

    Rapid eye movement sleep behavior disorder (RBD) is thought to be one of the most frequent preceding symptoms of Parkinson's disease (PD). However, the prevalence of RBD in PD stated in the published studies is still inconsistent. We conducted a meta and meta-regression analysis in this paper to estimate the pooled prevalence. We searched the electronic databases of PubMed, ScienceDirect, EMBASE and EBSCO up to June 2016 for related articles. STATA 12.0 statistics software was used to calculate the available data from each research. The prevalence of RBD in PD patients in each study was combined to a pooled prevalence with a 95 % confidence interval (CI). Subgroup analysis and meta-regression analysis were performed to search for the causes of the heterogeneity. A total of 28 studies with 6869 PD cases were deemed eligible and included in our meta-analysis based on the inclusion and exclusion criteria. The pooled prevalence of RBD in PD was 42.3 % (95 % CI 37.4-47.1 %). In subgroup analysis and meta-regression analysis, we found that the important causes of heterogeneity were the diagnosis criteria of RBD and age of PD patients (P = 0.016, P = 0.019, respectively). The results indicate that nearly half of the PD patients are suffering from RBD. Older age and longer duration are risk factors for RBD in PD. We can use the minimal diagnosis criteria for RBD according to the International Classification of Sleep Disorders to diagnose RBD patients in our daily work if polysomnography is not necessary.

  2. Meta-analysis in microbiology

    Directory of Open Access Journals (Sweden)

    N Pabalan

    2014-01-01

    Full Text Available The use of meta-analysis in microbiology may facilitate decision-making that impacts public health policy. Directed at clinicians and researchers in microbiology, this review outlines the steps in performing this statistical technique, addresses its biases and describes its value in this discipline. The survey to estimate extent of the use of meta-analyses in microbiology shows the remarkable growth in the use of this research methodology, from a minimal Asian output to a level comparable with those of Europe and North America in the last 7 years.

  3. Immunotherapy in advanced melanoma: a network meta-analysis.

    Science.gov (United States)

    Pyo, Jung-Soo; Kang, Guhyun

    2017-05-01

    The aim of this study was to compare the effects of various immunotherapeutic agents and chemotherapy for unresected or metastatic melanomas. We performed a network meta-analysis using a Bayesian statistical model to compare objective response rate (ORR) of various immunotherapies from 12 randomized controlled studies. The estimated ORRs of immunotherapy and chemotherapy were 0.224 and 0.108, respectively. The ORRs of immunotherapy in untreated and pretreated patients were 0.279 and 0.176, respectively. In network meta-analysis, the odds ratios for ORR of nivolumab (1 mg/kg)/ipilmumab (3 mg/kg), pembrolizumab 10 mg/kg and nivolumab 3 mg/kg were 8.54, 5.39 and 4.35, respectively, compared with chemotherapy alone. Our data showed that various immunotherapies had higher ORRs rather than chemotherapy alone.

  4. SWAT meta-modeling as support of the management scenario analysis in large watersheds.

    Science.gov (United States)

    Azzellino, A; Çevirgen, S; Giupponi, C; Parati, P; Ragusa, F; Salvetti, R

    2015-01-01

    In the last two decades, numerous models and modeling techniques have been developed to simulate nonpoint source pollution effects. Most models simulate the hydrological, chemical, and physical processes involved in the entrainment and transport of sediment, nutrients, and pesticides. Very often these models require a distributed modeling approach and are limited in scope by the requirement of homogeneity and by the need to manipulate extensive data sets. Physically based models are extensively used in this field as a decision support for managing the nonpoint source emissions. A common characteristic of this type of model is a demanding input of several state variables that makes the calibration and effort-costing in implementing any simulation scenario more difficult. In this study the USDA Soil and Water Assessment Tool (SWAT) was used to model the Venice Lagoon Watershed (VLW), Northern Italy. A Multi-Layer Perceptron (MLP) network was trained on SWAT simulations and used as a meta-model for scenario analysis. The MLP meta-model was successfully trained and showed an overall accuracy higher than 70% both on the training and on the evaluation set, allowing a significant simplification in conducting scenario analysis.

  5. Meta-analysis of high-latitude nitrogen-addition and warming studies implies ecological mechanisms overlooked by land models

    Science.gov (United States)

    Bouskill, N. J.; Riley, W. J.; Tang, J. Y.

    2014-12-01

    Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowground respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model-observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha-1 yr-1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.

  6. Acupuncture for musculoskeletal pain: A meta-analysis and meta-regression of sham-controlled randomized clinical trials

    Science.gov (United States)

    Yuan, Qi-ling; Wang, Peng; Liu, Liang; Sun, Fu; Cai, Yong-song; Wu, Wen-tao; Ye, Mao-lin; Ma, Jiang-tao; Xu, Bang-bang; Zhang, Yin-gang

    2016-01-01

    The aims of this systematic review were to study the analgesic effect of real acupuncture and to explore whether sham acupuncture (SA) type is related to the estimated effect of real acupuncture for musculoskeletal pain. Five databases were searched. The outcome was pain or disability immediately (≤1 week) following an intervention. Standardized mean differences (SMDs) with 95% confidence intervals were calculated. Meta-regression was used to explore possible sources of heterogeneity. Sixty-three studies (6382 individuals) were included. Eight condition types were included. The pooled effect size was moderate for pain relief (59 trials, 4980 individuals, SMD −0.61, 95% CI −0.76 to −0.47; P acupuncture has a moderate effect (approximate 12-point reduction on the 100-mm visual analogue scale) on musculoskeletal pain. SA type did not appear to be related to the estimated effect of real acupuncture. PMID:27471137

  7. Exposure to Traffic-related Air Pollution During Pregnancy and Term Low Birth Weight: Estimation of Causal Associations in a Semiparametric Model

    Science.gov (United States)

    Padula, Amy M.; Mortimer, Kathleen; Hubbard, Alan; Lurmann, Frederick; Jerrett, Michael; Tager, Ira B.

    2012-01-01

    Traffic-related air pollution is recognized as an important contributor to health problems. Epidemiologic analyses suggest that prenatal exposure to traffic-related air pollutants may be associated with adverse birth outcomes; however, there is insufficient evidence to conclude that the relation is causal. The Study of Air Pollution, Genetics and Early Life Events comprises all births to women living in 4 counties in California's San Joaquin Valley during the years 2000–2006. The probability of low birth weight among full-term infants in the population was estimated using machine learning and targeted maximum likelihood estimation for each quartile of traffic exposure during pregnancy. If everyone lived near high-volume freeways (approximated as the fourth quartile of traffic density), the estimated probability of term low birth weight would be 2.27% (95% confidence interval: 2.16, 2.38) as compared with 2.02% (95% confidence interval: 1.90, 2.12) if everyone lived near smaller local roads (first quartile of traffic density). Assessment of potentially causal associations, in the absence of arbitrary model assumptions applied to the data, should result in relatively unbiased estimates. The current results support findings from previous studies that prenatal exposure to traffic-related air pollution may adversely affect birth weight among full-term infants. PMID:23045474

  8. The association between uterine leiomyoma and placenta abruption: A meta-analysis.

    Science.gov (United States)

    Jenabi, Ensiyeh; Ebrahimzadeh Zagami, Samira

    2017-11-01

    Some epidemiological studies have found that uterine leiomyoma can increase the risk of placenta abruption. To date, the meta-analysis has not been performed for assessing the relationship between uterine leiomyoma and placenta abruption. This meta-analysis was conducted to estimate the association between uterine leiomyoma and the risk of placenta abruption. A literature search was conducted out in major databases PubMed, Web of Science, and Scopus from the earliest possible year to October 2016. The heterogeneity across studies was explored by Q-test and I 2 statistic. The publication bias was assessed by Begg's and Egger's tests. The results were showed using odds ratio (OR) estimate with its 95% confidence intervals (CI) using a random-effects model. The literature search included 953 articles until October 2016 with 232,024 participants. Based on OR estimates obtained from case-control and cohort studies, there was significant association between uterine leiomyoma and placenta abruption (2.63; 95% CI: 1.38, 3.88). We showed based on reports in observational studies that uterine leiomyoma is a risk factor for placenta abruption.

  9. Epilepsy and neurocysticercosis in Latin America: a systematic review and meta-analysis.

    Directory of Open Access Journals (Sweden)

    Elisa Bruno

    Full Text Available The difference in epilepsy burden existing among populations in tropical regions has been attributed to many factors, including the distribution of infectious diseases with neurologic sequels. To define the burden of epilepsy in Latin American Countries (LAC and to investigate the strength of association with neurocysticercosis (NCC, considered one of the leading causes of epilepsy, we performed a systematic review and meta-analysis of the literature.Studies published until 2012 were selected applying predefined inclusion criteria. Lifetime epilepsy (LTE prevalence, active epilepsy (AE prevalence, incidence, mortality, treatment gap (TG and NCC proportion among people with epilepsy (PWE were extracted. Median values were obtained for each estimate using random effects meta-analysis. The impact of NCC prevalence on epilepsy estimates was determined using meta-regression models. To assess the association between NCC and epilepsy, a further meta-analysis was performed on case-control studies.The median LTE prevalence was 15.8/1,000 (95% CI 13.5-18.3, the median AE prevalence was 10.7/1,000 (95% CI 8.4-13.2, the median incidence was 138.2/100,000 (95% CI 83.6-206.4, the overall standardized mortality ratio was 1.4 (95% CI 0.01-6.1 and the overall estimated TG was 60.6% (95% CI 45.3-74.9. The median NCC proportion among PWE was 32.3% (95% CI 26.0-39.0. Higher TG and NCC estimates were associated with higher epilepsy prevalence. The association between NCC and epilepsy was significant (p<0.001 with a common odds ratio of 2.8 (95% CI 1.9-4.0.A high burden of epilepsy and of NCC in LAC and a consistent association between these two diseases were pointed out. Furthermore, NCC prevalence and TG were identified as important factors influencing epilepsy prevalence to be considered in prevention and intervention strategies.

  10. Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

    Science.gov (United States)

    Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

    2018-06-01

    Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  11. A model-based meta-analysis of monoclonal antibody pharmacokinetics to guide optimal first-in-human study design

    Science.gov (United States)

    Davda, Jasmine P; Dodds, Michael G; Gibbs, Megan A; Wisdom, Wendy; Gibbs, John P

    2014-01-01

    The objectives of this retrospective analysis were (1) to characterize the population pharmacokinetics (popPK) of four different monoclonal antibodies (mAbs) in a combined analysis of individual data collected during first-in-human (FIH) studies and (2) to provide a scientific rationale for prospective design of FIH studies with mAbs. The data set was composed of 171 subjects contributing a total of 2716 mAb serum concentrations, following intravenous (IV) and subcutaneous (SC) doses. mAb PK was described by an open 2-compartment model with first-order elimination from the central compartment and a depot compartment with first-order absorption. Parameter values obtained from the popPK model were further used to generate optimal sampling times for a single dose study. A robust fit to the combined data from four mAbs was obtained using the 2-compartment model. Population parameter estimates for systemic clearance and central volume of distribution were 0.20 L/day and 3.6 L with intersubject variability of 31% and 34%, respectively. The random residual error was 14%. Differences (> 2-fold) in PK parameters were not apparent across mAbs. Rich designs (22 samples/subject), minimal designs for popPK (5 samples/subject), and optimal designs for non-compartmental analysis (NCA) and popPK (10 samples/subject) were examined by stochastic simulation and estimation. Single-dose PK studies for linear mAbs executed using the optimal designs are expected to yield high-quality model estimates, and accurate capture of NCA estimations. This model-based meta-analysis has determined typical popPK values for four mAbs with linear elimination and enabled prospective optimization of FIH study designs, potentially improving the efficiency of FIH studies for this class of therapeutics. PMID:24837591

  12. Trends in OSHA Compliance Monitoring Data 1979-2011: Statistical Modeling of Ancillary Information across 77 Chemicals.

    Science.gov (United States)

    Sarazin, Philippe; Burstyn, Igor; Kincl, Laurel; Lavoué, Jérôme

    2016-05-01

    The Integrated Management Information System (IMIS) is the largest multi-industry source of exposure measurements available in North America. However, many have suspected that the criteria through which worksites are selected for inspection are related to exposure levels. We investigated associations between exposure levels and ancillary variables in IMIS in order to understand the predictors of high exposure within an enforcement context. We analyzed the association between nine variables (reason for inspection, establishment size, total amount of penalty, Occupational Safety and Health Administration (OSHA) plan, OSHA region, union status, inspection scope, year, and industry) and exposure levels in IMIS using multimodel inference for 77 agents. For each agent, we used two different types of models: (i) logistic models were used for the odds ratio (OR) of exposure being above the threshold limit value (TLV) and (ii) linear models were used for exposure concentrations restricted to detected results to estimate percent increase in exposure level, i.e. relative index of exposure (RIE). Meta-analytic methods were used to combine results for each variable across agents. A total of 511,047 exposure measurements were modeled for logistic models and 299,791 for linear models. Higher exposures were measured during follow-up inspections than planned inspections [meta-OR = 1.61, 95% confidence interval (CI): 1.44-1.81; meta-RIE = 1.06, 95% CI: 1.03-1.09]. Lower exposures were observed for measurements collected under state OSHA plans compared to measurements collected under federal OSHA (meta-OR = 0.82, 95% CI: 0.73-0.92; meta-RIE = 0.86, 95% CI: 0.81-0.91). A 'high' total historical amount of penalty relative to none was associated with higher exposures (meta-OR = 1.54, 95% CI: 1.40-1.71; meta-RIE = 1.18, 95% CI: 1.13-1.23). The relationships observed between exposure levels and ancillary variables across a vast majority of agents suggest that certain elements of OSHA

  13. Uncertainty relations for approximation and estimation

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jaeha, E-mail: jlee@post.kek.jp [Department of Physics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Tsutsui, Izumi, E-mail: izumi.tsutsui@kek.jp [Department of Physics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Theory Center, Institute of Particle and Nuclear Studies, High Energy Accelerator Research Organization (KEK), 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan)

    2016-05-27

    We present a versatile inequality of uncertainty relations which are useful when one approximates an observable and/or estimates a physical parameter based on the measurement of another observable. It is shown that the optimal choice for proxy functions used for the approximation is given by Aharonov's weak value, which also determines the classical Fisher information in parameter estimation, turning our inequality into the genuine Cramér–Rao inequality. Since the standard form of the uncertainty relation arises as a special case of our inequality, and since the parameter estimation is available as well, our inequality can treat both the position–momentum and the time–energy relations in one framework albeit handled differently. - Highlights: • Several inequalities interpreted as uncertainty relations for approximation/estimation are derived from a single ‘versatile inequality’. • The ‘versatile inequality’ sets a limit on the approximation of an observable and/or the estimation of a parameter by another observable. • The ‘versatile inequality’ turns into an elaboration of the Robertson–Kennard (Schrödinger) inequality and the Cramér–Rao inequality. • Both the position–momentum and the time–energy relation are treated in one framework. • In every case, Aharonov's weak value arises as a key geometrical ingredient, deciding the optimal choice for the proxy functions.

  14. Uncertainty relations for approximation and estimation

    International Nuclear Information System (INIS)

    Lee, Jaeha; Tsutsui, Izumi

    2016-01-01

    We present a versatile inequality of uncertainty relations which are useful when one approximates an observable and/or estimates a physical parameter based on the measurement of another observable. It is shown that the optimal choice for proxy functions used for the approximation is given by Aharonov's weak value, which also determines the classical Fisher information in parameter estimation, turning our inequality into the genuine Cramér–Rao inequality. Since the standard form of the uncertainty relation arises as a special case of our inequality, and since the parameter estimation is available as well, our inequality can treat both the position–momentum and the time–energy relations in one framework albeit handled differently. - Highlights: • Several inequalities interpreted as uncertainty relations for approximation/estimation are derived from a single ‘versatile inequality’. • The ‘versatile inequality’ sets a limit on the approximation of an observable and/or the estimation of a parameter by another observable. • The ‘versatile inequality’ turns into an elaboration of the Robertson–Kennard (Schrödinger) inequality and the Cramér–Rao inequality. • Both the position–momentum and the time–energy relation are treated in one framework. • In every case, Aharonov's weak value arises as a key geometrical ingredient, deciding the optimal choice for the proxy functions.

  15. Efficacy of escitalopram compared to citalopram: a meta-analysis.

    Science.gov (United States)

    Montgomery, Stuart; Hansen, Thomas; Kasper, Siegfried

    2011-03-01

    The aim of this review was to assess the clinical relevance of the relative antidepressant efficacy of escitalopram and citalopram by meta-analysis. Studies in major depressive disorder (MDD) with both escitalopram and citalopram treatment arms were identified. Adult patients had to meet DSM-IV criteria for MDD. The primary outcome measure was the treatment difference in Montgomery-Asberg Depression Rating Scale (MADRS) total score at week 8 (or last assessment if escitalopram, n=995; citalopram, n=1014). Escitalopram was significantly more effective than citalopram in overall treatment effect, with an estimated mean treatment difference of 1.7 points at week 8 (or last assessment if escitalopram. In this meta-analysis, the statistically significant superior efficacy of escitalopram compared to citalopram was shown to be clinically relevant.

  16. No firm evidence that lack of blinding affects estimates of mortality in randomised clinical trials of intensive care interventions: a systematic review and meta-analysis.

    Science.gov (United States)

    Anthon, Carl Thomas; Granholm, Anders; Perner, Anders; Laake, Jon Henrik; Møller, Morten Hylander

    2018-04-26

    To evaluate the effect of blinding on mortality effect estimates in randomised clinical trials (RCTs) in adult intensive care unit (ICU) patients. A systematic review and meta-analysis of RCTs reporting mortality effect estimates of ICU interventions in adult ICU patients. We assessed differences in summarised risk ratios (RRs) with 95% confidence intervals (CIs) between blinded and unblinded RCTs. P firm evidence that lack of blinding affects estimates of mortality in RCTs of ICU interventions. Copyright © 2018. Published by Elsevier Inc.

  17. Prevalence of sleep quality disorder among Iranian drivers: a systematic review and meta-analysis

    Science.gov (United States)

    Tabrizi, Reza; Moosazadeh, Mahmood; Razzaghi, Alireza; Akbari, Maryam; Heydari, Seyed Taghi; Kavari, Seyed Habibollah; Mani, Arash; Kazemi, Maryam; Bagheri Lankarani, Kamran

    2018-01-01

    Abstract: Background: Sleep Quality Disorder (SQD) plays a major role in road accidents. So, this study was carried out to determine the prevalence of SQD among occupational drivers using systematic review and meta-analysis in Iran. Methods: All Persian and English articles between January, 2000 and October, 2015 which had reported the SQD prevalence in Iranian drivers by Pittsburgh Sleep Quality Index (PSQI) with cross-sectional design, after the quality evaluation process and achieving the required score, were selected. The heterogenic index of the studies was distinguished by using Cochran (Q) and I2 tests. Based on heterogeneity results, a random effects model was used to estimate pooled prevalence of SQD. Meta-regression was also used to investigate the heterogeneity of suspected factors. Results: In total, 936 articles were found from national and international databases. Ten articles entered to meta-analysis process, ultimately. Since heterogeneity index suggested that there is a consider-able heterogeneity among the results of primary studies (I-squared = 98.8%, Q= 754.1, p less than 0.001), the overall estimation of SQD among Iranian drivers was conducted using random-effects model and its rate was estimated to be 53.4% (95% CI: 38.9-67.8). Conclusions: Our study demonstrated that more than half of Iranian drivers have SQD. Identifying the drivers with SQD by periodic examinations and providing advice and health care among occupational drivers could be appropriate solutions for decreasing the accident risks. PMID:29362294

  18. Meta-analysis for diagnostic accuracy studies: a new statistical model using beta-binomial distributions and bivariate copulas.

    Science.gov (United States)

    Kuss, Oliver; Hoyer, Annika; Solms, Alexander

    2014-01-15

    There are still challenges when meta-analyzing data from studies on diagnostic accuracy. This is mainly due to the bivariate nature of the response where information on sensitivity and specificity must be summarized while accounting for their correlation within a single trial. In this paper, we propose a new statistical model for the meta-analysis for diagnostic accuracy studies. This model uses beta-binomial distributions for the marginal numbers of true positives and true negatives and links these margins by a bivariate copula distribution. The new model comes with all the features of the current standard model, a bivariate logistic regression model with random effects, but has the additional advantages of a closed likelihood function and a larger flexibility for the correlation structure of sensitivity and specificity. In a simulation study, which compares three copula models and two implementations of the standard model, the Plackett and the Gauss copula do rarely perform worse but frequently better than the standard model. We use an example from a meta-analysis to judge the diagnostic accuracy of telomerase (a urinary tumor marker) for the diagnosis of primary bladder cancer for illustration. Copyright © 2013 John Wiley & Sons, Ltd.

  19. An Activation Likelihood Estimation Meta-Analysis Study of Simple Motor Movements in Older and Young Adults

    Science.gov (United States)

    Turesky, Ted K.; Turkeltaub, Peter E.; Eden, Guinevere F.

    2016-01-01

    The functional neuroanatomy of finger movements has been characterized with neuroimaging in young adults. However, less is known about the aging motor system. Several studies have contrasted movement-related activity in older versus young adults, but there is inconsistency among their findings. To address this, we conducted an activation likelihood estimation (ALE) meta-analysis on within-group data from older adults and young adults performing regularly paced right-hand finger movement tasks in response to external stimuli. We hypothesized that older adults would show a greater likelihood of activation in right cortical motor areas (i.e., ipsilateral to the side of movement) compared to young adults. ALE maps were examined for conjunction and between-group differences. Older adults showed overlapping likelihoods of activation with young adults in left primary sensorimotor cortex (SM1), bilateral supplementary motor area, bilateral insula, left thalamus, and right anterior cerebellum. Their ALE map differed from that of the young adults in right SM1 (extending into dorsal premotor cortex), right supramarginal gyrus, medial premotor cortex, and right posterior cerebellum. The finding that older adults uniquely use ipsilateral regions for right-hand finger movements and show age-dependent modulations in regions recruited by both age groups provides a foundation by which to understand age-related motor decline and motor disorders. PMID:27799910

  20. Meta-Teaching: Meaning and Strategy

    Science.gov (United States)

    Chen, Xiaoduan

    2013-01-01

    Meta-teaching is the knowledge and reflection on teaching based on meta-ideas. It is the teaching about teaching, a teaching process with practice consciously guided by thinking, inspiring teachers to teach more effectively. Meta-teaching is related to the knowledge, inspection and amendment of teaching activities in terms of their design,…

  1. MetaGenyo: a web tool for meta-analysis of genetic association studies.

    Science.gov (United States)

    Martorell-Marugan, Jordi; Toro-Dominguez, Daniel; Alarcon-Riquelme, Marta E; Carmona-Saez, Pedro

    2017-12-16

    Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise. We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results. MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/ .

  2. Comparison of additive (absolute) risk projection models and multiplicative (relative) risk projection models in estimating radiation-induced lifetime cancer risk

    International Nuclear Information System (INIS)

    Kai, Michiaki; Kusama, Tomoko

    1990-01-01

    Lifetime cancer risk estimates depend on risk projection models. While the increasing lengths of follow-up observation periods of atomic bomb survivors in Hiroshima and Nagasaki bring about changes in cancer risk estimates, the validity of the two risk projection models, the additive risk projection model (AR) and multiplicative risk projection model (MR), comes into question. This paper compares the lifetime risk or loss of life-expectancy between the two projection models on the basis of BEIR-III report or recently published RERF report. With Japanese cancer statistics the estimates of MR were greater than those of AR, but a reversal of these results was seen when the cancer hazard function for India was used. When we investigated the validity of the two projection models using epidemiological human data and animal data, the results suggested that MR was superior to AR with respect to temporal change, but there was little evidence to support its validity. (author)

  3. MetaEasy: A Meta-Analysis Add-In for Microsoft Excel

    Directory of Open Access Journals (Sweden)

    Evangelos Kontopantelis

    2009-04-01

    Full Text Available Meta-analysis is a statistical methodology that combines or integrates the results ofseveral independent clinical trials considered by the analyst to be `combinable' (Huque1988. However, completeness and user-friendliness are uncommon both in specialisedmeta-analysis software packages and in mainstream statistical packages that have to relyon user-written commands. We implemented the meta-analysis methodology in an Mi-crosoft Excel add-in which is freely available and incorporates more meta-analysis models(including the iterative maximum likelihood and prole likelihood than are usually avail-able, while paying particular attention to the user-friendliness of the package.

  4. Association of the miR-196a2 C>T and miR-499 A>G polymorphisms with hepatitis B virus-related hepatocellular carcinoma risk: an updated meta-analysis

    Directory of Open Access Journals (Sweden)

    Zhu SL

    2016-04-01

    Full Text Available Shao-Liang Zhu,1,* Jian-Hong Zhong,1,* Wen-Feng Gong,1,* Hang Li,2 Le-Qun Li11Department of Hepatobiliary Surgery, 2Department of Ultrasound, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, People’s Republic of China*These authors contributed equally to this workBackground: This study meta-analyzed data on the possible association of the miR-196a2 C>T (rs11614913 and miR-499 A>G (rs3746444 polymorphisms with risk of hepatitis B virus (HBV-related hepatocellular carcinoma (HCC.Methods: Databases in PubMed, EMBASE, Web of Science, China BioMedicine, and Google Scholar were systematically searched to identify relevant studies. Meta-analyses were performed to examine the association of the miR-196a2 C>T and miR-499 A>G polymorphisms with HBV-related HCC risk. Odds ratios (ORs and 95% confidence intervals (95% CIs were calculated.Results: A total of 13 studies involving 3,964 cases and 5,875 healthy controls were included. Random-effect meta-analysis showed that the T allele and TT genotype of miR-196a2 C>T were associated with significantly lower HBV-related HCC risk (allelic model, OR =0.84, 95% CI =0.71–0.99, P=0.04; homozygous model, OR =0.68, 95% CI =0.47–0.98, P=0.04. In contrast, miR-499 A>G showed no significant association with HBV-related HCC risk in either overall pooled analysis or ethnic subgroup analysis according to any of the four genetic models. Based on analysis of ethnic subgroups, neither miR-196a2 C>T nor miR-499 A>G was significantly associated with risk of HBV-related HCC in Chinese population.Conclusion: The polymorphism miR-196a2 C>T, but not miR-499 A>G, may be associated with decreased HBV-related HCC risk. These conclusions should be verified in large, well-designed studies.Keywords: microRNA, single nucleotide polymorphisms, hepatitis B virus related, meta-analysis, hepatocellular carcinoma

  5. Methodological Quality Assessment of Meta-analyses in Endodontics.

    Science.gov (United States)

    Kattan, Sereen; Lee, Su-Min; Kohli, Meetu R; Setzer, Frank C; Karabucak, Bekir

    2018-01-01

    The objectives of this review were to assess the methodological quality of published meta-analyses related to endodontics using the assessment of multiple systematic reviews (AMSTAR) tool and to provide a follow-up to previously published reviews. Three electronic databases were searched for eligible studies according to the inclusion and exclusion criteria: Embase via Ovid, The Cochrane Library, and Scopus. The electronic search was amended by a hand search of 6 dental journals (International Endodontic Journal; Journal of Endodontics; Australian Endodontic Journal; Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology; Endodontics and Dental Traumatology; and Journal of Dental Research). The searches were conducted to include articles published after July 2009, and the deadline for inclusion of the meta-analyses was November 30, 2016. The AMSTAR assessment tool was used to evaluate the methodological quality of all included studies. A total of 36 reports of meta-analyses were included. The overall quality of the meta-analyses reports was found to be medium, with an estimated mean overall AMSTAR score of 7.25 (95% confidence interval, 6.59-7.90). The most poorly assessed areas were providing an a priori design, the assessment of the status of publication, and publication bias. In recent publications in the field of endodontics, the overall quality of the reported meta-analyses is medium according to AMSTAR. Copyright © 2017 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

  6. Spatial Distribution of Hydrologic Ecosystem Service Estimates: Comparing Two Models

    Science.gov (United States)

    Dennedy-Frank, P. J.; Ghile, Y.; Gorelick, S.; Logsdon, R. A.; Chaubey, I.; Ziv, G.

    2014-12-01

    We compare estimates of the spatial distribution of water quantity provided (annual water yield) from two ecohydrologic models: the widely-used Soil and Water Assessment Tool (SWAT) and the much simpler water models from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) toolbox. These two models differ significantly in terms of complexity, timescale of operation, effort, and data required for calibration, and so are often used in different management contexts. We compare two study sites in the US: the Wildcat Creek Watershed (2083 km2) in Indiana, a largely agricultural watershed in a cold aseasonal climate, and the Upper Upatoi Creek Watershed (876 km2) in Georgia, a mostly forested watershed in a temperate aseasonal climate. We evaluate (1) quantitative estimates of water yield to explore how well each model represents this process, and (2) ranked estimates of water yield to indicate how useful the models are for management purposes where other social and financial factors may play significant roles. The SWAT and InVEST models provide very similar estimates of the water yield of individual subbasins in the Wildcat Creek Watershed (Pearson r = 0.92, slope = 0.89), and a similar ranking of the relative water yield of those subbasins (Spearman r = 0.86). However, the two models provide relatively different estimates of the water yield of individual subbasins in the Upper Upatoi Watershed (Pearson r = 0.25, slope = 0.14), and very different ranking of the relative water yield of those subbasins (Spearman r = -0.10). The Upper Upatoi watershed has a significant baseflow contribution due to its sandy, well-drained soils. InVEST's simple seasonality terms, which assume no change in storage over the time of the model run, may not accurately estimate water yield processes when baseflow provides such a strong contribution. Our results suggest that InVEST users take care in situations where storage changes are significant.

  7. A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests.

    Science.gov (United States)

    Simoneau, Gabrielle; Levis, Brooke; Cuijpers, Pim; Ioannidis, John P A; Patten, Scott B; Shrier, Ian; Bombardier, Charles H; de Lima Osório, Flavia; Fann, Jesse R; Gjerdingen, Dwenda; Lamers, Femke; Lotrakul, Manote; Löwe, Bernd; Shaaban, Juwita; Stafford, Lesley; van Weert, Henk C P M; Whooley, Mary A; Wittkampf, Karin A; Yeung, Albert S; Thombs, Brett D; Benedetti, Andrea

    2017-11-01

    Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Relative Wave Energy based Adaptive Neuro-Fuzzy Inference System model for the Estimation of Depth of Anaesthesia.

    Science.gov (United States)

    Benzy, V K; Jasmin, E A; Koshy, Rachel Cherian; Amal, Frank; Indiradevi, K P

    2018-01-01

    The advancement in medical research and intelligent modeling techniques has lead to the developments in anaesthesia management. The present study is targeted to estimate the depth of anaesthesia using cognitive signal processing and intelligent modeling techniques. The neurophysiological signal that reflects cognitive state of anaesthetic drugs is the electroencephalogram signal. The information available on electroencephalogram signals during anaesthesia are drawn by extracting relative wave energy features from the anaesthetic electroencephalogram signals. Discrete wavelet transform is used to decomposes the electroencephalogram signals into four levels and then relative wave energy is computed from approximate and detail coefficients of sub-band signals. Relative wave energy is extracted to find out the degree of importance of different electroencephalogram frequency bands associated with different anaesthetic phases awake, induction, maintenance and recovery. The Kruskal-Wallis statistical test is applied on the relative wave energy features to check the discriminating capability of relative wave energy features as awake, light anaesthesia, moderate anaesthesia and deep anaesthesia. A novel depth of anaesthesia index is generated by implementing a Adaptive neuro-fuzzy inference system based fuzzy c-means clustering algorithm which uses relative wave energy features as inputs. Finally, the generated depth of anaesthesia index is compared with a commercially available depth of anaesthesia monitor Bispectral index.

  9. Clinical risk factors for age-related macular degeneration: a systematic review and meta-analysis

    Directory of Open Access Journals (Sweden)

    Evans Christopher

    2010-12-01

    Full Text Available Abstract Background Age-related macular degeneration (AMD is the leading cause of blindness in Western countries. Numerous risk factors have been reported but the evidence and strength of association is variable. We aimed to identify those risk factors with strong levels of evidence which could be easily assessed by physicians or ophthalmologists to implement preventive interventions or address current behaviours. Methods A systematic review identified 18 prospective and cross-sectional studies and 6 case control studies involving 113,780 persons with 17,236 cases of late AMD that included an estimate of the association between late AMD and at least one of 16 pre-selected risk factors. Fixed-effects meta-analyses were conducted for each factor to combine odds ratio (OR and/or relative risk (RR outcomes across studies by study design. Overall raw point estimates of each risk factor and associated 95% confidence intervals (CI were calculated. Results Increasing age, current cigarette smoking, previous cataract surgery, and a family history of AMD showed strong and consistent associations with late AMD. Risk factors with moderate and consistent associations were higher body mass index, history of cardiovascular disease, hypertension, and higher plasma fibrinogen. Risk factors with weaker and inconsistent associations were gender, ethnicity, diabetes, iris colour, history of cerebrovascular disease, and serum total and HDL cholesterol and triglyceride levels. Conclusions Smoking, previous cataract surgery and a family history of AMD are consistent risk factors for AMD. Cardiovascular risk factors are also associated with AMD. Knowledge of these risk factors that may be easily assessed by physicians and general ophthalmologists may assist in identification and appropriate referral of persons at risk of AMD.

  10. Burden of Severe Pneumonia, Pneumococcal Pneumonia and Pneumonia Deaths in Indian States: Modelling Based Estimates

    Science.gov (United States)

    Farooqui, Habib; Jit, Mark; Heymann, David L.; Zodpey, Sanjay

    2015-01-01

    The burden of severe pneumonia in terms of morbidity and mortality is unknown in India especially at sub-national level. In this context, we aimed to estimate the number of severe pneumonia episodes, pneumococcal pneumonia episodes and pneumonia deaths in children younger than 5 years in 2010. We adapted and parameterized a mathematical model based on the epidemiological concept of potential impact fraction developed CHERG for this analysis. The key parameters that determine the distribution of severe pneumonia episode across Indian states were state-specific under-5 population, state-specific prevalence of selected definite pneumonia risk factors and meta-estimates of relative risks for each of these risk factors. We applied the incidence estimates and attributable fraction of risk factors to population estimates for 2010 of each Indian state. We then estimated the number of pneumococcal pneumonia cases by applying the vaccine probe methodology to an existing trial. We estimated mortality due to severe pneumonia and pneumococcal pneumonia by combining incidence estimates with case fatality ratios from multi-centric hospital-based studies. Our results suggest that in 2010, 3.6 million (3.3–3.9 million) episodes of severe pneumonia and 0.35 million (0.31–0.40 million) all cause pneumonia deaths occurred in children younger than 5 years in India. The states that merit special mention include Uttar Pradesh where 18.1% children reside but contribute 24% of pneumonia cases and 26% pneumonia deaths, Bihar (11.3% children, 16% cases, 22% deaths) Madhya Pradesh (6.6% children, 9% cases, 12% deaths), and Rajasthan (6.6% children, 8% cases, 11% deaths). Further, we estimated that 0.56 million (0.49–0.64 million) severe episodes of pneumococcal pneumonia and 105 thousand (92–119 thousand) pneumococcal deaths occurred in India. The top contributors to India’s pneumococcal pneumonia burden were Uttar Pradesh, Bihar, Madhya Pradesh and Rajasthan in that order. Our

  11. Burden of Severe Pneumonia, Pneumococcal Pneumonia and Pneumonia Deaths in Indian States: Modelling Based Estimates.

    Science.gov (United States)

    Farooqui, Habib; Jit, Mark; Heymann, David L; Zodpey, Sanjay

    2015-01-01

    The burden of severe pneumonia in terms of morbidity and mortality is unknown in India especially at sub-national level. In this context, we aimed to estimate the number of severe pneumonia episodes, pneumococcal pneumonia episodes and pneumonia deaths in children younger than 5 years in 2010. We adapted and parameterized a mathematical model based on the epidemiological concept of potential impact fraction developed CHERG for this analysis. The key parameters that determine the distribution of severe pneumonia episode across Indian states were state-specific under-5 population, state-specific prevalence of selected definite pneumonia risk factors and meta-estimates of relative risks for each of these risk factors. We applied the incidence estimates and attributable fraction of risk factors to population estimates for 2010 of each Indian state. We then estimated the number of pneumococcal pneumonia cases by applying the vaccine probe methodology to an existing trial. We estimated mortality due to severe pneumonia and pneumococcal pneumonia by combining incidence estimates with case fatality ratios from multi-centric hospital-based studies. Our results suggest that in 2010, 3.6 million (3.3-3.9 million) episodes of severe pneumonia and 0.35 million (0.31-0.40 million) all cause pneumonia deaths occurred in children younger than 5 years in India. The states that merit special mention include Uttar Pradesh where 18.1% children reside but contribute 24% of pneumonia cases and 26% pneumonia deaths, Bihar (11.3% children, 16% cases, 22% deaths) Madhya Pradesh (6.6% children, 9% cases, 12% deaths), and Rajasthan (6.6% children, 8% cases, 11% deaths). Further, we estimated that 0.56 million (0.49-0.64 million) severe episodes of pneumococcal pneumonia and 105 thousand (92-119 thousand) pneumococcal deaths occurred in India. The top contributors to India's pneumococcal pneumonia burden were Uttar Pradesh, Bihar, Madhya Pradesh and Rajasthan in that order. Our results

  12. Burden of Severe Pneumonia, Pneumococcal Pneumonia and Pneumonia Deaths in Indian States: Modelling Based Estimates.

    Directory of Open Access Journals (Sweden)

    Habib Farooqui

    Full Text Available The burden of severe pneumonia in terms of morbidity and mortality is unknown in India especially at sub-national level. In this context, we aimed to estimate the number of severe pneumonia episodes, pneumococcal pneumonia episodes and pneumonia deaths in children younger than 5 years in 2010. We adapted and parameterized a mathematical model based on the epidemiological concept of potential impact fraction developed CHERG for this analysis. The key parameters that determine the distribution of severe pneumonia episode across Indian states were state-specific under-5 population, state-specific prevalence of selected definite pneumonia risk factors and meta-estimates of relative risks for each of these risk factors. We applied the incidence estimates and attributable fraction of risk factors to population estimates for 2010 of each Indian state. We then estimated the number of pneumococcal pneumonia cases by applying the vaccine probe methodology to an existing trial. We estimated mortality due to severe pneumonia and pneumococcal pneumonia by combining incidence estimates with case fatality ratios from multi-centric hospital-based studies. Our results suggest that in 2010, 3.6 million (3.3-3.9 million episodes of severe pneumonia and 0.35 million (0.31-0.40 million all cause pneumonia deaths occurred in children younger than 5 years in India. The states that merit special mention include Uttar Pradesh where 18.1% children reside but contribute 24% of pneumonia cases and 26% pneumonia deaths, Bihar (11.3% children, 16% cases, 22% deaths Madhya Pradesh (6.6% children, 9% cases, 12% deaths, and Rajasthan (6.6% children, 8% cases, 11% deaths. Further, we estimated that 0.56 million (0.49-0.64 million severe episodes of pneumococcal pneumonia and 105 thousand (92-119 thousand pneumococcal deaths occurred in India. The top contributors to India's pneumococcal pneumonia burden were Uttar Pradesh, Bihar, Madhya Pradesh and Rajasthan in that order. Our

  13. A meta-analysis accounting for sources of variability to estimate heat resistance reference parameters of bacteria using hierarchical Bayesian modeling: Estimation of D at 121.1 °C and pH 7, zT and zpH of Geobacillus stearothermophilus.

    Science.gov (United States)

    Rigaux, Clémence; Denis, Jean-Baptiste; Albert, Isabelle; Carlin, Frédéric

    2013-02-01

    Predicting microbial survival requires reference parameters for each micro-organism of concern. When data are abundant and publicly available, a meta-analysis is a useful approach for assessment of these parameters, which can be performed with hierarchical Bayesian modeling. Geobacillus stearothermophilus is a major agent of microbial spoilage of canned foods and is therefore a persistent problem in the food industry. The thermal inactivation parameters of G. stearothermophilus (D(ref), i.e.the decimal reduction time D at the reference temperature 121.1°C and pH 7.0, z(T) and z(pH)) were estimated from a large set of 430 D values mainly collected from scientific literature. Between-study variability hypotheses on the inactivation parameters D(ref), z(T) and z(pH) were explored, using three different hierarchical Bayesian models. Parameter estimations were made using Bayesian inference and the models were compared with a graphical and a Bayesian criterion. Results show the necessity to account for random effects associated with between-study variability. Assuming variability on D(ref), z(T) and z(pH), the resulting distributions for D(ref), z(T) and z(pH) led to a mean of 3.3 min for D(ref) (95% Credible Interval CI=[0.8; 9.6]), to a mean of 9.1°C for z(T) (CI=[5.4; 13.1]) and to a mean of 4.3 pH units for z(pH) (CI=[2.9; 6.3]), in the range pH 3 to pH 7.5. Results are also given separating variability and uncertainty in these distributions, as well as adjusted parametric distributions to facilitate further use of these results in aqueous canned foods such as canned vegetables. Copyright © 2012 Elsevier B.V. All rights reserved.

  14. CrossFit Overview: Systematic Review and Meta-analysis.

    Science.gov (United States)

    Claudino, João Gustavo; Gabbett, Tim J; Bourgeois, Frank; Souza, Helton de Sá; Miranda, Rafael Chagas; Mezêncio, Bruno; Soncin, Rafael; Cardoso Filho, Carlos Alberto; Bottaro, Martim; Hernandez, Arnaldo Jose; Amadio, Alberto Carlos; Serrão, Julio Cerca

    2018-02-26

    CrossFit is recognized as one of the fastest growing high-intensity functional training modes in the world. However, scientific data regarding the practice of CrossFit is sparse. Therefore, the objective of this study is to analyze the findings of scientific literature related to CrossFit via systematic review and meta-analysis. Systematic searches of the PubMed, Web of Science, Scopus, Bireme/MedLine, and SciELO online databases were conducted for articles reporting the effects of CrossFit training. The systematic review followed the PRISMA guidelines. The Oxford Levels of Evidence was used for all included articles, and only studies that investigated the effects of CrossFit as a training program were included in the meta-analysis. For the meta-analysis, effect sizes (ESs) with 95% confidence interval (CI) were calculated and heterogeneity was assessed using a random-effects model. Thirty-one articles were included in the systematic review and four were included in the meta-analysis. However, only two studies had a high level of evidence at low risk of bias. Scientific literature related to CrossFit has reported on body composition, psycho-physiological parameters, musculoskeletal injury risk, life and health aspects, and psycho-social behavior. In the meta-analysis, significant results were not found for any variables. The current scientific literature related to CrossFit has few studies with high level of evidence at low risk of bias. However, preliminary data has suggested that CrossFit practice is associated with higher levels of sense of community, satisfaction, and motivation.

  15. Meta-analysis of the INSIG2 association with obesity including 74,345 individuals: does heterogeneity of estimates relate to study design?

    DEFF Research Database (Denmark)

    Heid, Iris M; Huth, Cornelia; Loos, Ruth J F

    2009-01-01

    with subjects selected for conditions related to a better health status ('healthy population', HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did......The INSIG2 rs7566605 polymorphism was identified for obesity (BMI> or =30 kg/m(2)) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies...... not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-value = 0.27). The I(2) measure of 41% (p-value = 0.015) indicated between-study heterogeneity. Restricting to GP studies resulted in a declined I(2) measure of 11% (p-value = 0.33) and an OR of 1.10 (p...

  16. A Western Dietary Pattern Increases Prostate Cancer Risk: A Systematic Review and Meta-Analysis.

    Science.gov (United States)

    Fabiani, Roberto; Minelli, Liliana; Bertarelli, Gaia; Bacci, Silvia

    2016-10-12

    Dietary patterns were recently applied to examine the relationship between eating habits and prostate cancer (PC) risk. While the associations between PC risk with the glycemic index and Mediterranean score have been reviewed, no meta-analysis is currently available on dietary patterns defined by "a posteriori" methods. A literature search was carried out (PubMed, Web of Science) to identify studies reporting the relationship between dietary patterns and PC risk. Relevant dietary patterns were selected and the risks estimated were calculated by a random-effect model. Multivariable-adjusted odds ratios (ORs), for a first-percentile increase in dietary pattern score, were combined by a dose-response meta-analysis. Twelve observational studies were included in the meta-analysis which identified a "Healthy pattern" and a "Western pattern". The Healthy pattern was not related to PC risk (OR = 0.96; 95% confidence interval (CI): 0.88-1.04) while the Western pattern significantly increased it (OR = 1.34; 95% CI: 1.08-1.65). In addition, the "Carbohydrate pattern", which was analyzed in four articles, was positively associated with a higher PC risk (OR = 1.64; 95% CI: 1.35-2.00). A significant linear trend between the Western ( p = 0.011) pattern, the Carbohydrate ( p = 0.005) pattern, and the increment of PC risk was observed. The small number of studies included in the meta-analysis suggests that further investigation is necessary to support these findings.

  17. Long working hours and depressive symptoms: systematic review and meta-analysis of published studies and unpublished individual participant data

    OpenAIRE

    Virtanen, M.; Jokela, M.; Madsen, I. E.; Magnusson Hanson, L. L.; Lallukka, T.; Nyberg, S. T.; Alfredsson, L.; Batty, D.; Bjorner, J. B.; Borritz, M.; Burr, H.; Dragano, N.; Erbel, R.; Ferrie, J. E.; Heikkilä, K.

    2018-01-01

    Objectives This systematic review and meta-analysis combined published study-level data and unpublished individual-participant data with the aim of quantifying the relation between long working hours and the onset of depressive symptoms. Methods We searched PubMed and Embase for published prospective cohort studies and included available cohorts with unpublished individual-participant data. We used a random-effects meta-analysis to calculate summary estimates across studies. Results We identi...

  18. Does Bruxism Contribute to Dental Implant Failure? A Systematic Review and Meta-Analysis.

    Science.gov (United States)

    Zhou, Yi; Gao, Jinxia; Luo, Le; Wang, Yining

    2016-04-01

    Bruxism was usually considered as a contraindication for oral implanting. The causal relationship between bruxism and dental implant failure was remained controversial in existing literatures. This meta-analysis was performed to investigate the relationship between them. This review conducted an electronic systematic literature search in MEDLINE (PubMed) and EmBase in November 2013 without time and language restrictions. Meanwhile, a hand searching for all the relevant references of included studies was also conducted. Study information extraction and methodological quality assessments were accomplished by two reviewers independently. A discussion ensued if any disagreement occurred, and unresolved issues were solved by consulting a third reviewer. Methodological quality was assessed by using the Newcastle-Ottawa Scale tool. Odds ratio (OR) with 95% confidence interval (CI) was pooled to estimate the relative effect of bruxism on dental implant failures. Fixed effects model was used initially; if the heterogeneity was high, random effects model was chosen for meta-analysis. Statistical analyses were carried out by using Review Manager 5.1. In this meta-analysis review, extracted data were classified into two groups based on different units. Units were based on the number of prostheses (group A) and the number of patients (group B). In group A, the total pooled OR of bruxers versus nonbruxers for all subgroups was 4.72 (95% CI: 2.66-8.36, p = .07). In group B, the total pooled OR of bruxers versus nonbruxers for all subgroups was 3.83 (95% CI: 2.12-6.94, p = .22). This meta-analysis was performed to evaluate the relationship between bruxism and dental implant failure. In contrast to nonbruxers, prostheses in bruxers had a higher failure rate. It suggests that bruxism is a contributing factor of causing the occurrence of dental implant technical/biological complications and plays a role in dental implant failure. © 2015 Wiley Periodicals, Inc.

  19. Combining risk estimates from observational studies with different exposure cutpoints: a meta-analysis on body mass index and diabetes type 2.

    NARCIS (Netherlands)

    Hartemink, Nienke; Boshuizen, Hendriek C; Nagelkerke, Nico J D; Jacobs, Monique A M; Houwelingen, Hans C van

    2006-01-01

    Studies on a dose-response relation often report separate relative risks for several risk classes compared with a referent class. When performing a meta-analysis of such studies, one has to convert these relative risks into an overall relative risk for a continuous effect. Apart from taking the

  20. A meta-analysis of prospective studies of coffee consumption and mortality for all causes, cancers and cardiovascular diseases.

    Science.gov (United States)

    Malerba, Stefano; Turati, Federica; Galeone, Carlotta; Pelucchi, Claudio; Verga, Federica; La Vecchia, Carlo; Tavani, Alessandra

    2013-07-01

    Several prospective studies considered the relation between coffee consumption and mortality. Most studies, however, were underpowered to detect an association, since they included relatively few deaths. To obtain quantitative overall estimates, we combined all published data from prospective studies on the relation of coffee with mortality for all causes, all cancers, cardiovascular disease (CVD), coronary/ischemic heart disease (CHD/IHD) and stroke. A bibliography search, updated to January 2013, was carried out in PubMed and Embase to identify prospective observational studies providing quantitative estimates on mortality from all causes, cancer, CVD, CHD/IHD or stroke in relation to coffee consumption. A systematic review and meta-analysis was conducted to estimate overall relative risks (RR) and 95 % confidence intervals (CI) using random-effects models. The pooled RRs of all cause mortality for the study-specific highest versus low (≤1 cup/day) coffee drinking categories were 0.88 (95 % CI 0.84-0.93) based on all the 23 studies, and 0.87 (95 % CI 0.82-0.93) for the 19 smoking adjusting studies. The combined RRs for CVD mortality were 0.89 (95 % CI 0.77-1.02, 17 smoking adjusting studies) for the highest versus low drinking and 0.98 (95 % CI 0.95-1.00, 16 studies) for the increment of 1 cup/day. Compared with low drinking, the RRs for the highest consumption of coffee were 0.95 (95 % CI 0.78-1.15, 12 smoking adjusting studies) for CHD/IHD, 0.95 (95 % CI 0.70-1.29, 6 studies) for stroke, and 1.03 (95 % CI 0.97-1.10, 10 studies) for all cancers. This meta-analysis provides quantitative evidence that coffee intake is inversely related to all cause and, probably, CVD mortality.

  1. High-intensity interval training for improving health-related fitness in adolescents: a systematic review and meta-analysis.

    Science.gov (United States)

    Costigan, S A; Eather, N; Plotnikoff, R C; Taaffe, D R; Lubans, D R

    2015-10-01

    High-intensity interval training (HIIT) may be a feasible and efficacious strategy for improving health-related fitness in young people. The objective of this systematic review and meta-analysis was to evaluate the utility of HIIT to improve health-related fitness in adolescents and to identify potential moderators of training effects. Studies were considered eligible if they: (1) examined adolescents (13-18 years); (2) examined health-related fitness outcomes; (3) involved an intervention of ≥4 weeks in duration; (4) included a control or moderate intensity comparison group; and (5) prescribed high-intensity activity for the HIIT condition. Meta-analyses were conducted to determine the effect of HIIT on health-related fitness components using Comprehensive Meta-analysis software and potential moderators were explored (ie, study duration, risk of bias and type of comparison group). The effects of HIIT on cardiorespiratory fitness and body composition were large, and medium, respectively. Study duration was a moderator for the effect of HIIT on body fat percentage. Intervention effects for waist circumference and muscular fitness were not statistically significant. HIIT is a feasible and time-efficient approach for improving cardiorespiratory fitness and body composition in adolescent populations. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  2. A Maximum Likelihood Estimation of Vocal-Tract-Related Filter Characteristics for Single Channel Speech Separation

    Directory of Open Access Journals (Sweden)

    Dansereau Richard M

    2007-01-01

    Full Text Available We present a new technique for separating two speech signals from a single recording. The proposed method bridges the gap between underdetermined blind source separation techniques and those techniques that model the human auditory system, that is, computational auditory scene analysis (CASA. For this purpose, we decompose the speech signal into the excitation signal and the vocal-tract-related filter and then estimate the components from the mixed speech using a hybrid model. We first express the probability density function (PDF of the mixed speech's log spectral vectors in terms of the PDFs of the underlying speech signal's vocal-tract-related filters. Then, the mean vectors of PDFs of the vocal-tract-related filters are obtained using a maximum likelihood estimator given the mixed signal. Finally, the estimated vocal-tract-related filters along with the extracted fundamental frequencies are used to reconstruct estimates of the individual speech signals. The proposed technique effectively adds vocal-tract-related filter characteristics as a new cue to CASA models using a new grouping technique based on an underdetermined blind source separation. We compare our model with both an underdetermined blind source separation and a CASA method. The experimental results show that our model outperforms both techniques in terms of SNR improvement and the percentage of crosstalk suppression.

  3. A Maximum Likelihood Estimation of Vocal-Tract-Related Filter Characteristics for Single Channel Speech Separation

    Directory of Open Access Journals (Sweden)

    Mohammad H. Radfar

    2006-11-01

    Full Text Available We present a new technique for separating two speech signals from a single recording. The proposed method bridges the gap between underdetermined blind source separation techniques and those techniques that model the human auditory system, that is, computational auditory scene analysis (CASA. For this purpose, we decompose the speech signal into the excitation signal and the vocal-tract-related filter and then estimate the components from the mixed speech using a hybrid model. We first express the probability density function (PDF of the mixed speech's log spectral vectors in terms of the PDFs of the underlying speech signal's vocal-tract-related filters. Then, the mean vectors of PDFs of the vocal-tract-related filters are obtained using a maximum likelihood estimator given the mixed signal. Finally, the estimated vocal-tract-related filters along with the extracted fundamental frequencies are used to reconstruct estimates of the individual speech signals. The proposed technique effectively adds vocal-tract-related filter characteristics as a new cue to CASA models using a new grouping technique based on an underdetermined blind source separation. We compare our model with both an underdetermined blind source separation and a CASA method. The experimental results show that our model outperforms both techniques in terms of SNR improvement and the percentage of crosstalk suppression.

  4. Relative efficiency of unequal versus equal cluster sizes in cluster randomized trials using generalized estimating equation models.

    Science.gov (United States)

    Liu, Jingxia; Colditz, Graham A

    2018-05-01

    There is growing interest in conducting cluster randomized trials (CRTs). For simplicity in sample size calculation, the cluster sizes are assumed to be identical across all clusters. However, equal cluster sizes are not guaranteed in practice. Therefore, the relative efficiency (RE) of unequal versus equal cluster sizes has been investigated when testing the treatment effect. One of the most important approaches to analyze a set of correlated data is the generalized estimating equation (GEE) proposed by Liang and Zeger, in which the "working correlation structure" is introduced and the association pattern depends on a vector of association parameters denoted by ρ. In this paper, we utilize GEE models to test the treatment effect in a two-group comparison for continuous, binary, or count data in CRTs. The variances of the estimator of the treatment effect are derived for the different types of outcome. RE is defined as the ratio of variance of the estimator of the treatment effect for equal to unequal cluster sizes. We discuss a commonly used structure in CRTs-exchangeable, and derive the simpler formula of RE with continuous, binary, and count outcomes. Finally, REs are investigated for several scenarios of cluster size distributions through simulation studies. We propose an adjusted sample size due to efficiency loss. Additionally, we also propose an optimal sample size estimation based on the GEE models under a fixed budget for known and unknown association parameter (ρ) in the working correlation structure within the cluster. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Meta-analysis of SNPs involved in variance heterogeneity using Levene's test for equal variances

    Science.gov (United States)

    Deng, Wei Q; Asma, Senay; Paré, Guillaume

    2014-01-01

    Meta-analysis is a commonly used approach to increase the sample size for genome-wide association searches when individual studies are otherwise underpowered. Here, we present a meta-analysis procedure to estimate the heterogeneity of the quantitative trait variance attributable to genetic variants using Levene's test without needing to exchange individual-level data. The meta-analysis of Levene's test offers the opportunity to combine the considerable sample size of a genome-wide meta-analysis to identify the genetic basis of phenotypic variability and to prioritize single-nucleotide polymorphisms (SNPs) for gene–gene and gene–environment interactions. The use of Levene's test has several advantages, including robustness to departure from the normality assumption, freedom from the influence of the main effects of SNPs, and no assumption of an additive genetic model. We conducted a meta-analysis of the log-transformed body mass index of 5892 individuals and identified a variant with a highly suggestive Levene's test P-value of 4.28E-06 near the NEGR1 locus known to be associated with extreme obesity. PMID:23921533

  6. Node-Splitting Generalized Linear Mixed Models for Evaluation of Inconsistency in Network Meta-Analysis.

    Science.gov (United States)

    Yu-Kang, Tu

    2016-12-01

    Network meta-analysis for multiple treatment comparisons has been a major development in evidence synthesis methodology. The validity of a network meta-analysis, however, can be threatened by inconsistency in evidence within the network. One particular issue of inconsistency is how to directly evaluate the inconsistency between direct and indirect evidence with regard to the effects difference between two treatments. A Bayesian node-splitting model was first proposed and a similar frequentist side-splitting model has been put forward recently. Yet, assigning the inconsistency parameter to one or the other of the two treatments or splitting the parameter symmetrically between the two treatments can yield different results when multi-arm trials are involved in the evaluation. We aimed to show that a side-splitting model can be viewed as a special case of design-by-treatment interaction model, and different parameterizations correspond to different design-by-treatment interactions. We demonstrated how to evaluate the side-splitting model using the arm-based generalized linear mixed model, and an example data set was used to compare results from the arm-based models with those from the contrast-based models. The three parameterizations of side-splitting make slightly different assumptions: the symmetrical method assumes that both treatments in a treatment contrast contribute to inconsistency between direct and indirect evidence, whereas the other two parameterizations assume that only one of the two treatments contributes to this inconsistency. With this understanding in mind, meta-analysts can then make a choice about how to implement the side-splitting method for their analysis. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  7. Individual and Work-Related Factors Influencing Burnout of Mental Health Professionals: A Meta-Analysis

    Science.gov (United States)

    Lim, Nayoung; Kim, Eun Kyoung; Kim, Hyunjung; Yang, Eunjoo; Lee, Sang Min

    2010-01-01

    The current study identifies and assesses individual and work-related factors as correlates of burnout among mental health professionals. Results of a meta-analysis indicate that age and work setting variables are the most significant indicators of emotional exhaustion and depersonalization. In terms of level of personal accomplishment, the age…

  8. A meta-frontier approach for causal inference in productivity analysis

    DEFF Research Database (Denmark)

    Henningsen, Arne; Mpeta, Daniel F.; Adem, Anwar S.

    (2012) and create a meta-frontier in order to estimate the effects of participation on the farms’ meta-technology ratio, their group technical efficiency, and their meta-technology technical efficiency. The empirical analysis uses a cross-sectional data set from sunflower farmers in Tanzania, where some...... by the contractor’s provision of (additional) extension service and seeds of high-yielding varieties to the contract farmers....

  9. MTLRP genetic polymorphism (214C>A) was associated with Type 2 diabetes in Caucasian population: a meta-analysis

    OpenAIRE

    Chen, Li-Li; Han, Song-Mei; Tang, Fei-Fei; Li, Qiang

    2014-01-01

    Background Previous studies reported the relation between MTLRP genetic polymorphism and type 2 diabetes, however, the conclusion were conflicting. In the present study, we performed a meta-analysis to reveal this association. Methods Literature retrieval, selection and assessment, data extraction, and meta-analyses were performed according to the RevMan 5.0 guidelines. In the meta-analysis, we utilized random-effect model or fixed-effect model to pool the Odds ratio (OR) according to the tes...

  10. Transformational Leadership and Organizational Citizenship Behavior: A Meta-Analytic Test of Underlying Mechanisms.

    Science.gov (United States)

    Nohe, Christoph; Hertel, Guido

    2017-01-01

    Based on social exchange theory, we examined and contrasted attitudinal mediators (affective organizational commitment, job satisfaction) and relational mediators (trust in leader, leader-member exchange; LMX) of the positive relationship between transformational leadership and organizational citizenship behavior (OCB). Hypotheses were tested using meta-analytic path models with correlations from published meta-analyses (761 samples with 227,419 individuals overall). When testing single-mediator models, results supported our expectations that each of the mediators explained the relationship between transformational leadership and OCB. When testing a multi-mediator model, LMX was the strongest mediator. When testing a model with a latent attitudinal mechanism and a latent relational mechanism, the relational mechanism was the stronger mediator of the relationship between transformational leadership and OCB. Our findings help to better understand the underlying mechanisms of the relationship between transformational leadership and OCB.

  11. Meta-analysis for quantitative microbiological risk assessments and benchmarking data

    NARCIS (Netherlands)

    Besten, den H.M.W.; Zwietering, M.H.

    2012-01-01

    Meta-analysis studies are increasingly being conducted in the food microbiology area to quantitatively integrate the findings of many individual studies on specific questions or kinetic parameters of interest. Meta-analyses provide global estimates of parameters and quantify their variabilities, and

  12. Meta-analysis of high-latitude nitrogen-addition and warming studies imply ecological mechanisms overlooked by land models

    Science.gov (United States)

    Bouskill, N. J.; Riley, W. J.; Tang, J.

    2014-08-01

    Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the atmosphere. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the above and belowground high-latitude ecosystem responses to warming and nitrogen addition, and identified mechanisms absent, or poorly parameterized in CLM4.5. While the two model versions predicted similar trajectories for soil carbon stocks following both types of perturbation, other variables (e.g., belowground respiration) differed from the observations in both magnitude and direction, indicating the underlying mechanisms are inadequate for representing high-latitude ecosystems. The observational synthesis attribute these differences to missing representations of microbial dynamics, characterization of above and belowground functional processes, and nutrient competition. We use the observational meta-analyses to discuss potential approaches to improving the current models (e.g., the inclusion of dynamic vegetation or different microbial functional guilds), however, we also raise a cautionary note on the selection of data sets and experiments to be included in a meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average =72 kg ha-1 yr-1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which preclude a rigorous evaluation of the model responses to nitrogen perturbation. Overall, we demonstrate here that elucidating ecological mechanisms via meta-analysis can identify deficiencies in both ecosystem models and empirical experiments.

  13. Dose-response meta-analysis of differences in means

    Directory of Open Access Journals (Sweden)

    Alessio Crippa

    2016-08-01

    Full Text Available Abstract Background Meta-analytical methods are frequently used to combine dose-response findings expressed in terms of relative risks. However, no methodology has been established when results are summarized in terms of differences in means of quantitative outcomes. Methods We proposed a two-stage approach. A flexible dose-response model is estimated within each study (first stage taking into account the covariance of the data points (mean differences, standardized mean differences. Parameters describing the study-specific curves are then combined using a multivariate random-effects model (second stage to address heterogeneity across studies. Results The method is fairly general and can accommodate a variety of parametric functions. Compared to traditional non-linear models (e.g. E max, logistic, spline models do not assume any pre-specified dose-response curve. Spline models allow inclusion of studies with a small number of dose levels, and almost any shape, even non monotonic ones, can be estimated using only two parameters. We illustrated the method using dose-response data arising from five clinical trials on an antipsychotic drug, aripiprazole, and improvement in symptoms in shizoaffective patients. Using the Positive and Negative Syndrome Scale (PANSS, pooled results indicated a non-linear association with the maximum change in mean PANSS score equal to 10.40 (95 % confidence interval 7.48, 13.30 observed for 19.32 mg/day of aripiprazole. No substantial change in PANSS score was observed above this value. An estimated dose of 10.43 mg/day was found to produce 80 % of the maximum predicted response. Conclusion The described approach should be adopted to combine correlated differences in means of quantitative outcomes arising from multiple studies. Sensitivity analysis can be a useful tool to assess the robustness of the overall dose-response curve to different modelling strategies. A user-friendly R package has been developed to facilitate

  14. Self-concept and academic achievement: a meta-analysis of longitudinal relations.

    Science.gov (United States)

    Huang, Chiungjung

    2011-10-01

    The relation between self-concept and academic achievement was examined in 39 independent and longitudinal samples through the integration of meta-analysis and path analysis procedures. For relations with more than 3 independent samples, the mean observed correlations ranged from .20 to .27 between prior self-concept and subsequent academic achievement and from .19 to .25 between prior academic achievement and subsequent self-concept. Globality/specificity of self-concept was the only significant moderating factor in the relation between (a) prior self-concept and subsequent academic achievement and (b) prior academic achievement and subsequent self-concept. As high self-concept is related to high academic performance and vice-versa, intervention programs that combine self-enhancement and skill development should be integrated. Copyright © 2011 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  15. Accuracy of peripheral thermometers for estimating temperature: a systematic review and meta-analysis.

    Science.gov (United States)

    Niven, Daniel J; Gaudet, Jonathan E; Laupland, Kevin B; Mrklas, Kelly J; Roberts, Derek J; Stelfox, Henry Thomas

    2015-11-17

    Body temperature is commonly used to screen patients for infectious diseases, establish diagnoses, monitor therapy, and guide management decisions. To determine the accuracy of peripheral thermometers for estimating core body temperature in adults and children. MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and CINAHL Plus from inception to July 2015. Prospective studies comparing the accuracy of peripheral (tympanic membrane, temporal artery, axillary, or oral) thermometers with central (pulmonary artery catheter, urinary bladder, esophageal, or rectal) thermometers. 2 reviewers extracted data on study characteristics, methods, and outcomes and assessed the quality of individual studies. 75 studies (8682 patients) were included. Most studies were at high or unclear risk of patient selection bias (74%) or index test bias (67%). Compared with central thermometers, peripheral thermometers had pooled 95% limits of agreement (random-effects meta-analysis) outside the predefined clinically acceptable range (± 0.5 °C), especially among patients with fever (-1.44 °C to 1.46 °C for adults; -1.49 °C to 0.43 °C for children) and hypothermia (-2.07 °C to 1.90 °C for adults; no data for children). For detection of fever (bivariate random-effects meta-analysis), sensitivity was low (64% [95% CI, 55% to 72%]; I2 = 95.7%; P temperature measurement techniques are limited. Pooled data are associated with interstudy heterogeneity that is not fully explained by stratified and metaregression analyses. Peripheral thermometers do not have clinically acceptable accuracy and should not be used when accurate measurement of body temperature will influence clinical decisions. None.

  16. Evaluation of the association between acne and smoking: systematic review and meta-analysis of cross-sectional studies

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    Alice Mannocci

    2010-09-01

    Full Text Available MetaPlusBook-Roman; font-size: x-small;">

    Background: Acne vulgaris is one of the most common skin diseases with a multifactorial pathogenesis. Examination of the literature regarding the contribution of smoking to acne shows contradictory results. The aim of this study was to undertake a systematic review of the literature and meta-analysis about the association between acne and smoking.

    Methods: A systematic review and meta-analysis, when possible were performed. The literature review was based on Pubmed, Scopus and Google Scholar searches using the keywords “(smoking OR tobacco OR nicotine OR cigarettes AND acne”. Only cross-sectional studies were included. Meta-analyses were performed using the RevMan software version 5 for Windows. Four different meta-analyses were carried out: one evaluating the association between smoking habit and acne, one including data stratified by gender, one for studies with a quality score > 6, and one relating to acne classification.

    Results: Six studies were selected. The first meta-analysis, including all studies, showed a non significant role of smoke in the development of acne: OR 1.05 (95% CI: 0.66–1.67 with random effect estimate. The second meta-analyses, including data stratified by gender, showed a OR=0.99 (95% CI: 0.57–1.73 for males and a OR of 1.45 (95% CI: 0.08–24.64 for females, using random effect for the heterogeneity in both cases. The third meta-analysis, included studies with a quality score >6 resulted in an estimated OR= 0.69 (95% CI: 0.55–0.85: in this case it was possible to use the fixed effect estimate. The last meta-analysis, concerning the severity grading, showed a non-significant result: OR=1.09 (95% CI: 0.61–1.95 using the random effect approach.

    Conclusions: The first two meta-analyses found no signification association between smoking and

  17. Cycling empirical antibiotic therapy in hospitals: meta-analysis and models.

    Directory of Open Access Journals (Sweden)

    Pia Abel zur Wiesch

    2014-06-01

    Full Text Available The rise of resistance together with the shortage of new broad-spectrum antibiotics underlines the urgency of optimizing the use of available drugs to minimize disease burden. Theoretical studies suggest that coordinating empirical usage of antibiotics in a hospital ward can contain the spread of resistance. However, theoretical and clinical studies came to different conclusions regarding the usefulness of rotating first-line therapy (cycling. Here, we performed a quantitative pathogen-specific meta-analysis of clinical studies comparing cycling to standard practice. We searched PubMed and Google Scholar and identified 46 clinical studies addressing the effect of cycling on nosocomial infections, of which 11 met our selection criteria. We employed a method for multivariate meta-analysis using incidence rates as endpoints and find that cycling reduced the incidence rate/1000 patient days of both total infections by 4.95 [9.43-0.48] and resistant infections by 7.2 [14.00-0.44]. This positive effect was observed in most pathogens despite a large variance between individual species. Our findings remain robust in uni- and multivariate metaregressions. We used theoretical models that reflect various infections and hospital settings to compare cycling to random assignment to different drugs (mixing. We make the realistic assumption that therapy is changed when first line treatment is ineffective, which we call "adjustable cycling/mixing". In concordance with earlier theoretical studies, we find that in strict regimens, cycling is detrimental. However, in adjustable regimens single resistance is suppressed and cycling is successful in most settings. Both a meta-regression and our theoretical model indicate that "adjustable cycling" is especially useful to suppress emergence of multiple resistance. While our model predicts that cycling periods of one month perform well, we expect that too long cycling periods are detrimental. Our results suggest that

  18. Meta-Analysis of the Association of Alcohol-Related Social Media Use with Alcohol Consumption and Alcohol-Related Problems in Adolescents and Young Adults.

    Science.gov (United States)

    Curtis, Brenda L; Lookatch, Samantha J; Ramo, Danielle E; McKay, James R; Feinn, Richard S; Kranzler, Henry R

    2018-06-01

    Despite the pervasive use of social media by young adults, there is comparatively little known about whether, and how, engagement in social media influences this group's drinking patterns and risk of alcohol-related problems. We examined the relations between young adults' alcohol-related social media engagement (defined as the posting, liking, commenting, and viewing of alcohol-related social media content) and their drinking behavior and problems. We conducted a systematic review and meta-analysis of studies evaluating the association of alcohol consumption and alcohol-related problems with alcohol-related social media engagement. Summary baseline variables regarding the social media platform used (e.g., Facebook and Twitter), social media measures assessed (e.g., number of alcohol photographs posted), alcohol measures (e.g., Alcohol Use Disorders Identification Test and Timeline Follow back Interview), and the number of time points at which data were collected were extracted from each published study. We used the Q statistic to examine heterogeneity in the correlations between alcohol-related social media engagement and both drinking behavior and alcohol-related problems. Because there was significant heterogeneity, we used a random-effects model to evaluate the difference from zero of the weighted aggregate correlations. We used metaregression with study characteristics as moderators to test for moderators of the observed heterogeneity. Following screening, 19 articles met inclusion criteria for the meta-analysis. The primary findings indicated a statistically significant relationship and moderate effect sizes between alcohol-related social media engagement and both alcohol consumption (r = 0.36, 95% CI: 0.29 to 0.44, p social media engagement and drinking behavior or these were measured on different occasions and (ii) whether measurements were taken by self-report or observation of social media engagement. We found moderate-sized effects across the 19

  19. Meta-analysis in a nutshell: Techniques and general findings

    DEFF Research Database (Denmark)

    Paldam, Martin

    2015-01-01

    The purpose of this article is to introduce the technique and main findings of meta-analysis to the reader, who is unfamiliar with the field and has the usual objections. A meta-analysis is a quantitative survey of a literature reporting estimates of the same parameter. The funnel showing...

  20. Meta-model of EPortfolio Usage in Different Environments

    Directory of Open Access Journals (Sweden)

    Igor Balaban

    2011-09-01

    Full Text Available EPortfolio offers a new philosophy of teaching and learning, giving the learner an opportunity to express oneself, to show one’s past work and experience to all the interested parties ranging from teachers to potential employers. However, an integral model for ePortfolio implementation in academic institutions that would take into account three different levels of stakeholders: 1. Individual (student and teacher; 2. Institution; and 3. Employer, currently does not exist. In this paper the role of ePortfolio in academic environment as well as the context in which ePortfolio operates is analyzed in detail. As a result of the comprehensive analysis that takes into account individual, academic institution and employer, a meta-model of ePortfolio usage in Lifelong Learning is proposed.

  1. The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study

    Directory of Open Access Journals (Sweden)

    Tania Dehesh

    2015-01-01

    Full Text Available Background. Univariate meta-analysis (UM procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS method as a multivariate meta-analysis approach. Methods. We evaluated the efficiency of four new approaches including zero correlation (ZC, common correlation (CC, estimated correlation (EC, and multivariate multilevel correlation (MMC on the estimation bias, mean square error (MSE, and 95% probability coverage of the confidence interval (CI in the synthesis of Cox proportional hazard models coefficients in a simulation study. Result. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. Conclusion. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

  2. The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study.

    Science.gov (United States)

    Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi

    2015-01-01

    Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

  3. The RTEL1 rs6010620 polymorphism and glioma risk: a meta-analysis based on 12 case-control studies.

    Science.gov (United States)

    Du, Shu-Li; Geng, Ting-Ting; Feng, Tian; Chen, Cui-Ping; Jin, Tian-Bo; Chen, Chao

    2014-01-01

    The association between the RTEL1 rs6010620 single nucleotide polymorphism (SNP) and glioma risk has been extensively studied. However, the results remain inconclusive. To further examine this association, we performed a meta-analysis. A computerized search of the PubMed and Embase databases for publications regarding the RTEL1 rs6010620 polymorphism and glioma cancer risk was performed. Genotype data were analyzed in a meta-analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to assess the association. Sensitivity analyses, tests of heterogeneity, cumulative meta-analyses, and assessments of bias were performed in our meta-analysis. Our meta-analysis confirmed that risk with allele A is lower than with allele G for glioma. The A allele of rs6010620 in RTEL1 decreased the risk of developing glioma in the 12 case-control studies for all genetic models: the allele model (OR=0.752, 95%CI: 0.715-0.792), the dominant model (OR=0.729, 95%CI: 0.685-0.776), the recessive model (OR=0.647, 95%CI: 0.569-0.734), the homozygote comparison (OR=0.528, 95%CI: 0.456-0.612), and the heterozygote comparison (OR=0.761, 95%CI: 0.713-0.812). In all genetic models, the association between the RTEL1 rs6010620 polymorphism and glioma risk was significant. This meta-analysis suggests that the RTEL1 rs6010620 polymorphism may be a risk factor for glioma. Further functional studies evaluating this polymorphism and glioma risk are warranted.

  4. Population pharmacokinetics analysis of olanzapine for Chinese psychotic patients based on clinical therapeutic drug monitoring data with assistance of meta-analysis.

    Science.gov (United States)

    Yin, Anyue; Shang, Dewei; Wen, Yuguan; Li, Liang; Zhou, Tianyan; Lu, Wei

    2016-08-01

    The aim of this study was to build an eligible population pharmacokinetic (PK) model for olanzapine in Chinese psychotic patients based on therapeutic drug monitoring (TDM) data, with assistance of meta-analysis, to facilitate individualized therapy. Population PK analysis for olanzapine was performed using NONMEM software (version 7.3.0). TDM data were collected from Guangzhou Brain Hospital (China). Because of the limitations of TDM data, model-based meta-analysis was performed to construct a structural model to assist the modeling of TDM data as prior estimates. After analyzing related covariates, a simulation was performed to predict concentrations for different types of patients under common dose regimens. A two-compartment model with first-order absorption and elimination was developed for olanzapine oral tablets, based on 23 articles with 390 data points. The model was then applied to the TDM data. Gender and smoking habits were found to be significant covariates that influence the clearance of olanzapine. To achieve a blood concentration of 20 ng/mL (the lower boundary of the recommended therapeutic range), simulation results indicated that the dose regimen of olanzapine should be 5 mg BID (twice a day), ≥ 5 mg QD (every day) plus 10 mg QN (every night), or >10 mg BID for female nonsmokers, male nonsmokers and male smokers, respectively. The population PK model, built using meta-analysis, could facilitate the modeling of TDM data collected from Chinese psychotic patients. The factors that significantly influence olanzapine disposition were determined and the final model could be used for individualized treatment.

  5. Estimating the temporal distribution of exposure-related cancers

    International Nuclear Information System (INIS)

    Carter, R.L.; Sposto, R.; Preston, D.L.

    1993-09-01

    The temporal distribution of exposure-related cancers is relevant to the study of carcinogenic mechanisms. Statistical methods for extracting pertinent information from time-to-tumor data, however, are not well developed. Separation of incidence from 'latency' and the contamination of background cases are two problems. In this paper, we present methods for estimating both the conditional distribution given exposure-related cancers observed during the study period and the unconditional distribution. The methods adjust for confounding influences of background cases and the relationship between time to tumor and incidence. Two alternative methods are proposed. The first is based on a structured, theoretically derived model and produces direct inferences concerning the distribution of interest but often requires more-specialized software. The second relies on conventional modeling of incidence and is implemented through readily available, easily used computer software. Inferences concerning the effects of radiation dose and other covariates, however, are not always obtainable directly. We present three examples to illustrate the use of these two methods and suggest criteria for choosing between them. The first approach was used, with a log-logistic specification of the distribution of interest, to analyze times to bone sarcoma among a group of German patients injected with 224 Ra. Similarly, a log-logistic specification was used in the analysis of time to chronic myelogenous leukemias among male atomic-bomb survivors. We used the alternative approach, involving conventional modeling, to estimate the conditional distribution of exposure-related acute myelogenous leukemias among male atomic-bomb survivors, given occurrence between 1 October 1950 and 31 December 1985. All analyses were performed using Poisson regression methods for analyzing grouped survival data. (J.P.N.)

  6. The Economic Value of Mangroves: A Meta-Analysis

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    Marwa E. Salem

    2012-03-01

    Full Text Available This paper presents a synthesis of the mangrove ecosystem valuation literature through a meta-regression analysis. The main contribution of this study is that it is the first meta-analysis focusing solely on mangrove forests, whereas previous studies have included different types of wetlands. The number of studies included in the regression analysis is 44 for a total of 145 observations. We include several regressions with the objective of addressing outliers in the data as well as the possible correlations between observations of the same study. We also investigate possible interaction effects between type of service and GDP per capita. Our findings indicate that mangroves exhibit decreasing returns to scale, that GDP per capita has a positive effect on mangrove values and that using the replacement cost and contingent valuation methods produce higher estimates than do other methods. We also find that there are statistically significant interaction effects that influence the data. Finally, the results indicate that employing weighted regressions provide a better fit than others. However, in terms of forecast performance we find that all the estimated models performed similarly and were not able to conclude decisively that one outperforms the other.

  7. Publication Bias Currently Makes an Accurate Estimate of the Benefits of Enrichment Programs Difficult: A Postmortem of Two Meta-Analyses Using Statistical Power Analysis

    Science.gov (United States)

    Warne, Russell T.

    2016-01-01

    Recently Kim (2016) published a meta-analysis on the effects of enrichment programs for gifted students. She found that these programs produced substantial effects for academic achievement (g = 0.96) and socioemotional outcomes (g = 0.55). However, given current theory and empirical research these estimates of the benefits of enrichment programs…

  8. Teaching meta-analysis using MetaLight

    Directory of Open Access Journals (Sweden)

    Thomas James

    2012-10-01

    Full Text Available Abstract Background Meta-analysis is a statistical method for combining the results of primary studies. It is often used in systematic reviews and is increasingly a method and topic that appears in student dissertations. MetaLight is a freely available software application that runs simple meta-analyses and contains specific functionality to facilitate the teaching and learning of meta-analysis. While there are many courses and resources for meta-analysis available and numerous software applications to run meta-analyses, there are few pieces of software which are aimed specifically at helping those teaching and learning meta-analysis. Valuable teaching time can be spent learning the mechanics of a new software application, rather than on the principles and practices of meta-analysis. Findings We discuss ways in which the MetaLight tool can be used to present some of the main issues involved in undertaking and interpreting a meta-analysis. Conclusions While there are many software tools available for conducting meta-analysis, in the context of a teaching programme such software can require expenditure both in terms of money and in terms of the time it takes to learn how to use it. MetaLight was developed specifically as a tool to facilitate the teaching and learning of meta-analysis and we have presented here some of the ways it might be used in a training situation.

  9. The Effectiveness of the Problem-Based Learning Teaching Model for Use in Introductory Chinese Undergraduate Medical Courses: A Systematic Review and Meta-Analysis

    Science.gov (United States)

    Zhang, Yanqi; Zhou, Liang; Liu, Xiaoyu; Liu, Ling; Wu, Yazhou; Zhao, Zengwei; Yi, Dali; Yi, Dong

    2015-01-01

    Background Although the problem-based learning (PBL) emerged in 1969 and was soon widely applied internationally, the rapid development in China only occurred in the last 10 years. This study aims to compare the effect of PBL and lecture-based learning (LBL) on student course examination results for introductory Chinese undergraduate medical courses. Methods Randomized and nonrandomized controlled trial studies on PBL use in Chinese undergraduate medical education were retrieved through PubMed, the Excerpta Medica Database (EMBASE), Chinese National Knowledge Infrastructure (CNKI) and VIP China Science and Technology Journal Database (VIP-CSTJ) with publication dates from 1st January 1966 till 31 August 2014. The pass rate, excellence rate and examination scores of course examination were collected. Methodological quality was evaluated based on the modified Jadad scale. The I-square statistic and Chi-square test of heterogeneity were used to assess the statistical heterogeneity. Overall RRs or SMDs with their 95% CIs were calculated in meta-analysis. Meta-regression and subgroup meta-analyses were also performed based on comparators and other confounding factors. Funnel plots and Egger’s tests were performed to assess degrees of publication bias. Results The meta-analysis included 31studies and 4,699 subjects. Fourteen studies were of high quality with modified Jadad scores of 4 to 6, and 17 studies were of low quality with scores of 1 to 3. Relative to the LBL model, the PBL model yielded higher course examination pass rates [RR = 1.09, 95%CI (1.03, 1.17)], excellence rates [RR = 1.66, 95%CI (1.33, 2.06)] and examination scores [SMD = 0.82, 95%CI (0.63, 1.01)]. The meta-regression results show that course type was the significant confounding factor that caused heterogeneity in the examination-score meta-analysis (t = 0.410, Pteaching model application in introductory undergraduate medical courses can increase course examination excellence rates and scores in

  10. Does the association of prostate cancer with night-shift work differ according to rotating vs. fixed schedule? A systematic review and meta-analysis.

    Science.gov (United States)

    Mancio, Jennifer; Leal, Cátia; Ferreira, Marta; Norton, Pedro; Lunet, Nuno

    2018-04-27

    Recent studies suggested that the relation between night-shift work and prostate cancer may differ between rotating and fixed schedules. We aimed to quantify the independent association between night-shift work and prostate cancer, for rotating and fixed schedules. We searched MEDLINE for studies assessing the association of night-shift work, by rotating or fixed schedules, with prostate cancer. We computed summary relative risk (RR) estimates with 95% confidence intervals (95% CI) using the inverse variance method and quantified heterogeneity using the I 2 statistic. Meta-regression analysis was used to compare the summary RR estimates for rotating and fixed schedules, while reducing heterogeneity. A total of nine studies assessed the effect of rotating and, in addition, four of them provided the effect of fixed night-shift work, in relation to daytime workers. Rotating night-shift work was associated with a significantly increased risk of prostate cancer (RR = 1.06, 95% CI of 1.01 to 1.12; I 2  = 50%), but not fixed night-shift work (RR of 1.01, 95% CI of 0.81 to 1.26; I 2  = 33%). In meta-regression model including study design, type of population, and control of confounding, the summary RR was 20% higher for rotating vs. fixed schedule, with heterogeneity fully explained by these variables. This is the first meta-analysis suggesting that an increased risk of prostate cancer may be restricted to workers with rotating night shifts. However, the association was weak and additional studies are needed to further clarify this relation before it can be translated into measures for risk reduction in occupational settings.

  11. Saving lives: A meta-analysis of team training in healthcare.

    Science.gov (United States)

    Hughes, Ashley M; Gregory, Megan E; Joseph, Dana L; Sonesh, Shirley C; Marlow, Shannon L; Lacerenza, Christina N; Benishek, Lauren E; King, Heidi B; Salas, Eduardo

    2016-09-01

    As the nature of work becomes more complex, teams have become necessary to ensure effective functioning within organizations. The healthcare industry is no exception. As such, the prevalence of training interventions designed to optimize teamwork in this industry has increased substantially over the last 10 years (Weaver, Dy, & Rosen, 2014). Using Kirkpatrick's (1956, 1996) training evaluation framework, we conducted a meta-analytic examination of healthcare team training to quantify its effectiveness and understand the conditions under which it is most successful. Results demonstrate that healthcare team training improves each of Kirkpatrick's criteria (reactions, learning, transfer, results; d = .37 to .89). Second, findings indicate that healthcare team training is largely robust to trainee composition, training strategy, and characteristics of the work environment, with the only exception being the reduced effectiveness of team training programs that involve feedback. As a tertiary goal, we proposed and found empirical support for a sequential model of healthcare team training where team training affects results via learning, which leads to transfer, which increases results. We find support for this sequential model in the healthcare industry (i.e., the current meta-analysis) and in training across all industries (i.e., using meta-analytic estimates from Arthur, Bennett, Edens, & Bell, 2003), suggesting the sequential benefits of training are not unique to medical teams. Ultimately, this meta-analysis supports the expanded use of team training and points toward recommendations for optimizing its effectiveness within healthcare settings. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  12. Systematizing Web Search through a Meta-Cognitive, Systems-Based, Information Structuring Model (McSIS)

    Science.gov (United States)

    Abuhamdieh, Ayman H.; Harder, Joseph T.

    2015-01-01

    This paper proposes a meta-cognitive, systems-based, information structuring model (McSIS) to systematize online information search behavior based on literature review of information-seeking models. The General Systems Theory's (GST) prepositions serve as its framework. Factors influencing information-seekers, such as the individual learning…

  13. Meta-analyses of the proportion of Japanese encephalitis virus infection in vectors and vertebrate hosts.

    Science.gov (United States)

    Oliveira, Ana R S; Cohnstaedt, Lee W; Strathe, Erin; Hernández, Luciana Etcheverry; McVey, D Scott; Piaggio, José; Cernicchiaro, Natalia

    2017-09-07

    Japanese encephalitis (JE) is a zoonosis in Southeast Asia vectored by mosquitoes infected with the Japanese encephalitis virus (JEV). Japanese encephalitis is considered an emerging exotic infectious disease with potential for introduction in currently JEV-free countries. Pigs and ardeid birds are reservoir hosts and play a major role on the transmission dynamics of the disease. The objective of the study was to quantitatively summarize the proportion of JEV infection in vectors and vertebrate hosts from data pertaining to observational studies obtained in a systematic review of the literature on vector and host competence for JEV, using meta-analyses. Data gathered in this study pertained to three outcomes: proportion of JEV infection in vectors, proportion of JEV infection in vertebrate hosts, and minimum infection rate (MIR) in vectors. Random-effects subgroup meta-analysis models were fitted by species (mosquito or vertebrate host species) to estimate pooled summary measures, as well as to compute the variance between studies. Meta-regression models were fitted to assess the association between different predictors and the outcomes of interest and to identify sources of heterogeneity among studies. Predictors included in all models were mosquito/vertebrate host species, diagnostic methods, mosquito capture methods, season, country/region, age category, and number of mosquitos per pool. Mosquito species, diagnostic method, country, and capture method represented important sources of heterogeneity associated with the proportion of JEV infection; host species and region were considered sources of heterogeneity associated with the proportion of JEV infection in hosts; and diagnostic and mosquito capture methods were deemed important contributors of heterogeneity for the MIR outcome. Our findings provide reference pooled summary estimates of vector competence for JEV for some mosquito species, as well as of sources of variability for these outcomes. Moreover, this

  14. Dynamic sensitivity analysis of long running landslide models through basis set expansion and meta-modelling

    Science.gov (United States)

    Rohmer, Jeremy

    2016-04-01

    Predicting the temporal evolution of landslides is typically supported by numerical modelling. Dynamic sensitivity analysis aims at assessing the influence of the landslide properties on the time-dependent predictions (e.g., time series of landslide displacements). Yet two major difficulties arise: 1. Global sensitivity analysis require running the landslide model a high number of times (> 1000), which may become impracticable when the landslide model has a high computation time cost (> several hours); 2. Landslide model outputs are not scalar, but function of time, i.e. they are n-dimensional vectors with n usually ranging from 100 to 1000. In this article, I explore the use of a basis set expansion, such as principal component analysis, to reduce the output dimensionality to a few components, each of them being interpreted as a dominant mode of variation in the overall structure of the temporal evolution. The computationally intensive calculation of the Sobol' indices for each of these components are then achieved through meta-modelling, i.e. by replacing the landslide model by a "costless-to-evaluate" approximation (e.g., a projection pursuit regression model). The methodology combining "basis set expansion - meta-model - Sobol' indices" is then applied to the La Frasse landslide to investigate the dynamic sensitivity analysis of the surface horizontal displacements to the slip surface properties during the pore pressure changes. I show how to extract information on the sensitivity of each main modes of temporal behaviour using a limited number (a few tens) of long running simulations. In particular, I identify the parameters, which trigger the occurrence of a turning point marking a shift between a regime of low values of landslide displacements and one of high values.

  15. Fuel Burn Estimation Model

    Science.gov (United States)

    Chatterji, Gano

    2011-01-01

    Conclusions: Validated the fuel estimation procedure using flight test data. A good fuel model can be created if weight and fuel data are available. Error in assumed takeoff weight results in similar amount of error in the fuel estimate. Fuel estimation error bounds can be determined.

  16. Association of LPP and TAGAP Polymorphisms with Celiac Disease Risk: A Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Shi-Qi Huang

    2017-02-01

    Full Text Available Background: Lipoma preferred partner (LPP and T-cell activation Rho GTPase activating protein (TAGAP polymorphisms might influence the susceptibility to celiac disease. Therefore, we performed a meta-analysis by identifying relevant studies to estimate the risks of these polymorphisms on celiac disease. Methods: The PubMed, Web of Science and Embase databases were searched (up to October 2016 for LPP rs1464510 and TAGAP rs1738074 polymorphisms. Results: This meta-analysis included the same 7 studies for LPP rs1464510 and TAGAP rs1738074. The minor risk A allele at both rs1464510 and rs1738074 carried risks (odds ratios of 1.26 (95% CI: 1.22–1.30 and 1.17 (95% CI: 1.14–1.21, respectively, which contributed to increased risks in all celiac disease patients by 10.72% and 6.59%, respectively. The estimated lambdas were 0.512 and 0.496, respectively, suggesting that a co-dominant model would be suitable for both gene effects. Conclusions: This meta-analysis provides robust estimates that polymorphisms in LPP and TAGAP genes are potential risk factors for celiac disease in European and American. Prospective studies and more genome-wide association studies (GWAS are needed to confirm these findings, and some corresponding molecular biology experiments should be carried out to clarify the pathogenic mechanisms of celiac disease.

  17. Fruits, vegetables, and bladder cancer risk: a systematic review and meta-analysis.

    Science.gov (United States)

    Vieira, Ana R; Vingeliene, Snieguole; Chan, Doris S M; Aune, Dagfinn; Abar, Leila; Navarro Rosenblatt, Deborah; Greenwood, Darren C; Norat, Teresa

    2015-01-01

    Smoking is estimated to cause about half of all bladder cancer cases. Case-control studies have provided evidence of an inverse association between fruit and vegetable intake and bladder cancer risk. As part of the World Cancer Research/American Institute for Cancer Research Continuous Update Project, we conducted a systematic review and meta-analysis of prospective studies to assess the dose-response relationship between fruit and vegetables and incidence and mortality of bladder cancer. We searched PubMed up to December 2013 for relevant prospective studies. We conducted highest compared with lowest meta-analyses and dose-response meta-analyses using random effects models to estimate summary relative risks (RRs) and 95% confidence intervals (CIs), and used restricted cubic splines to examine possible nonlinear associations. Fifteen prospective studies were included in the review. The summary RR for an increase of 1 serving/day (80 g) were 0.97 (95% CI: 0.95-0.99) I(2)  = 0%, eight studies for fruits and vegetables, 0.97 (95% CI: 0.94-1.00, I(2)  = 10%, 10 studies) for vegetables and 0.98 (95% CI: 0.96-1.00, I(2)  = 0%, 12 studies) for fruits. Results were similar in men and women and in current, former and nonsmokers. Amongst fruits and vegetables subgroups, for citrus fruits the summary RR for the highest compared with the lowest intake was 0.87 (95% CI: 0.76-0.99, I(2)  = 0%, eight studies) and for cruciferous vegetables there was evidence of a nonlinear relationship (P = 0.001). The current evidence from cohort studies is not consistent with a role for fruits and vegetables in preventing bladder cancer. © 2014 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  18. Insulin glargine and cancer risk in patients with diabetes: a meta-analysis.

    Directory of Open Access Journals (Sweden)

    Xulei Tang

    Full Text Available AIM: The role of insulin glargine as a risk factor for cancer is controversial in human studies. The aim of this meta-analysis was to evaluate the relationship between insulin glargine and cancer incidence. METHODS: All observational studies and randomized controlled trials evaluating the relationship of insulin glargine and cancer risk were identified in PubMed, Embase, Web of Science, Cochrane Library and the Chinese Biomedical Medical Literature Database, through March 2012. Odds ratios (ORs with corresponding 95% confidence interval (CI were calculated with a random-effects model. Confidence in the estimates of the obtained effects (quality of evidence was assessed by using the Grading of Recommendations Assessment, Development, and Evaluation approach. RESULTS: A total of 11 studies including 448,928 study subjects and 19,128 cancer patients were finally identified for the meta-analysis. Insulin glargine use was associated with a lower odds of cancer compared with non-glargine insulin use (OR 0.81, 95% CI 0.68 to 0.98, P = 0.03; very low-quality evidence. Glargine did not increase the odds of breast cancer (OR 0.99, 95% CI 0.68 to 1.46, P = 0.966; very low-quality evidence. Compared with non-glargine insulin, no significant association was found between insulin glargine and prostate cancer, pancreatic cancer and respiratory tract cancer. Insulin glargine use was associated with lower odds of other site-specific cancer. CONCLUSIONS: Results from the meta-analysis don't support the link between insulin glargine and an increased risk of cancer and the confidence in the estimates of the effects is very low. Further studies are needed to examine the relation between insulin glargine and cancer risk, especially breast cancer.

  19. Using NLP meta, Milton, metaphor models, for improving the activity of the organization

    Directory of Open Access Journals (Sweden)

    Cornel Marian IOSIF

    2010-12-01

    Full Text Available The objective of this paper is the improving of the three methods from the neuro- linguistic programming – metaphor, Milton model and the meta-model, so by using this in daily activities by an organization to improve the activities witch, are performed and to have a more efficient allocation of the available resources.

  20. Meta-Analytical Studies in Transport Economics. Methodology and Applications

    Energy Technology Data Exchange (ETDEWEB)

    Brons, M.R.E.

    2006-05-18

    Vast increases in the external costs of transport in the late twentieth century have caused national and international governmental bodies to worry about the sustainability of their transport systems. In this thesis we use meta-analysis as a research method to study various topics in transport economics that are relevant for sustainable transport policymaking. Meta-analysis is a research methodology that is based on the quantitative summarisation of a body of previously documented empirical evidence. In several fields of economic, meta-analysis has become a well-accepted research tool. Despite the appeal of the meta-analytical approach, there are methodological difficulties that need to be acknowledged. We study a specific methodological problem which is common in meta-analysis in economics, viz., within-study dependence caused by multiple sampling techniques. By means of Monte Carlo analysis we investigate the effect of such dependence on the performance of various multivariate estimators. In the applied part of the thesis we use and develop meta-analytical techniques to study the empirical variation in indicators of the price sensitivity of demand for aviation transport, the price sensitivity of demand for gasoline, the efficiency of urban public transport and the valuation of the external costs of noise from rail transport. We focus on the estimation of mean values for these indicators and on the identification of the impact of conditioning factors.

  1. Association between mental health-related stigma and active help-seeking: systematic review and meta-analysis.

    Science.gov (United States)

    Schnyder, Nina; Panczak, Radoslaw; Groth, Nicola; Schultze-Lutter, Frauke

    2017-04-01

    Background Mental disorders create high individual and societal costs and burden, partly because help-seeking is often delayed or completely avoided. Stigma related to mental disorders or mental health services is regarded as a main reason for insufficient help-seeking. Aims To estimate the impact of four stigma types (help-seeking attitudes and personal, self and perceived public stigma) on active help-seeking in the general population. Method A systematic review of three electronic databases was followed by random effect meta-analyses according to the stigma types. Results Twenty-seven studies fulfilled eligibility criteria. Participants' own negative attitudes towards mental health help-seeking (OR = 0.80, 95% CI 0.73-0.88) and their stigmatising attitudes towards people with a mental illness (OR = 0.82, 95% CI 0.69-0.98) were associated with less active help-seeking. Self-stigma showed insignificant association (OR = 0.88, 95% CI 0.76-1.03), whereas perceived public stigma was not associated. Conclusions Personal attitudes towards mental illness or help-seeking are associated with active help-seeking for mental problems. Campaigns promoting help-seeking and fighting mental illness-related stigma should target these personal attitudes rather than broad public opinion. © The Royal College of Psychiatrists 2017.

  2. ADHD and personality: a meta-analytic review

    OpenAIRE

    Gomez, R.; Corr, P. J.

    2014-01-01

    We report a meta-analysis of up to 40 data sets that examined the personality dimensions in the Five-Factor Model (FFM) and the integrated Five-Factor Model (IFFM) in relation to ADHD symptom domains of inattention (IA) and hyperactivity/impulsivity (HI). The IFFM incorporated the dimensions of other personality models (in particular, those of Eysenck, Tellegen, and Cloninger, as well as the FFM). Major findings were: (1) IA and HI were both associated with low conscientious inhibition/consci...

  3. Impact of HIV-related stigma on treatment adherence: systematic review and meta-synthesis

    Science.gov (United States)

    Katz, Ingrid T; Ryu, Annemarie E; Onuegbu, Afiachukwu G; Psaros, Christina; Weiser, Sheri D; Bangsberg, David R; Tsai, Alexander C

    2013-01-01

    Introduction Adherence to HIV antiretroviral therapy (ART) is a critical determinant of HIV-1 RNA viral suppression and health outcomes. It is generally accepted that HIV-related stigma is correlated with factors that may undermine ART adherence, but its relationship with ART adherence itself is not well established. We therefore undertook this review to systematically assess the relationship between HIV-related stigma and ART adherence. Methods We searched nine electronic databases for published and unpublished literature, with no language restrictions. First we screened the titles and abstracts for studies that potentially contained data on ART adherence. Then we reviewed the full text of these studies to identify articles that reported data on the relationship between ART adherence and either HIV-related stigma or serostatus disclosure. We used the method of meta-synthesis to summarize the findings from the qualitative studies. Results Our search protocol yielded 14,854 initial records. After eliminating duplicates and screening the titles and abstracts, we retrieved the full text of 960 journal articles, dissertations and unpublished conference abstracts for review. We included 75 studies conducted among 26,715 HIV-positive persons living in 32 countries worldwide, with less representation of work from Eastern Europe and Central Asia. Among the 34 qualitative studies, our meta-synthesis identified five distinct third-order labels through an inductive process that we categorized as themes and organized in a conceptual model spanning intrapersonal, interpersonal and structural levels. HIV-related stigma undermined ART adherence by compromising general psychological processes, such as adaptive coping and social support. We also identified psychological processes specific to HIV-positive persons driven by predominant stigmatizing attitudes and which undermined adherence, such as internalized stigma and concealment. Adaptive coping and social support were critical

  4. Development of a combined database for meta-epidemiological research

    DEFF Research Database (Denmark)

    Savović, Jelena; Harris, Ross J; Wood, Lesley

    2010-01-01

    or review. Unique identifiers were assigned to each reference and used to identify duplicate trials. Sets of meta-analyses with overlapping trials were identified and duplicates removed. Overlapping trials were used to examine agreement between assessments of trial characteristics. The combined database...... database will be used to examine the combined evidence on sources of bias in randomized controlled trials. The strategy used to remove overlap between meta-analyses may be of use for future empirical research. Copyright © 2010 John Wiley & Sons, Ltd.......Collections of meta-analyses assembled in meta-epidemiological studies are used to study associations of trial characteristics with intervention effect estimates. However, methods and findings are not consistent across studies. To combine data from 10 meta-epidemiological studies into a single...

  5. Application of a virtual coordinate measuring machine for measurement uncertainty estimation of aspherical lens parameters

    International Nuclear Information System (INIS)

    Küng, Alain; Meli, Felix; Nicolet, Anaïs; Thalmann, Rudolf

    2014-01-01

    Tactile ultra-precise coordinate measuring machines (CMMs) are very attractive for accurately measuring optical components with high slopes, such as aspheres. The METAS µ-CMM, which exhibits a single point measurement repeatability of a few nanometres, is routinely used for measurement services of microparts, including optical lenses. However, estimating the measurement uncertainty is very demanding. Because of the many combined influencing factors, an analytic determination of the uncertainty of parameters that are obtained by numerical fitting of the measured surface points is almost impossible. The application of numerical simulation (Monte Carlo methods) using a parametric fitting algorithm coupled with a virtual CMM based on a realistic model of the machine errors offers an ideal solution to this complex problem: to each measurement data point, a simulated measurement variation calculated from the numerical model of the METAS µ-CMM is added. Repeated several hundred times, these virtual measurements deliver the statistical data for calculating the probability density function, and thus the measurement uncertainty for each parameter. Additionally, the eventual cross-correlation between parameters can be analyzed. This method can be applied for the calibration and uncertainty estimation of any parameter of the equation representing a geometric element. In this article, we present the numerical simulation model of the METAS µ-CMM and the application of a Monte Carlo method for the uncertainty estimation of measured asphere parameters. (paper)

  6. PepArML: A Meta-Search Peptide Identification Platform for Tandem Mass Spectra.

    Science.gov (United States)

    Edwards, Nathan J

    2013-12-01

    The PepArML meta-search peptide identification platform for tandem mass spectra provides a unified search interface to seven search engines; a robust cluster, grid, and cloud computing scheduler for large-scale searches; and an unsupervised, model-free, machine-learning-based result combiner, which selects the best peptide identification for each spectrum, estimates false-discovery rates, and outputs pepXML format identifications. The meta-search platform supports Mascot; Tandem with native, k-score and s-score scoring; OMSSA; MyriMatch; and InsPecT with MS-GF spectral probability scores—reformatting spectral data and constructing search configurations for each search engine on the fly. The combiner selects the best peptide identification for each spectrum based on search engine results and features that model enzymatic digestion, retention time, precursor isotope clusters, mass accuracy, and proteotypic peptide properties, requiring no prior knowledge of feature utility or weighting. The PepArML meta-search peptide identification platform often identifies two to three times more spectra than individual search engines at 10% FDR.

  7. High-dimensional model estimation and model selection

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

  8. Bias-Corrected Estimation of Noncentrality Parameters of Covariance Structure Models

    Science.gov (United States)

    Raykov, Tenko

    2005-01-01

    A bias-corrected estimator of noncentrality parameters of covariance structure models is discussed. The approach represents an application of the bootstrap methodology for purposes of bias correction, and utilizes the relation between average of resample conventional noncentrality parameter estimates and their sample counterpart. The…

  9. A SQL-Database Based Meta-CASE System and its Query Subsystem

    Science.gov (United States)

    Eessaar, Erki; Sgirka, Rünno

    Meta-CASE systems simplify the creation of CASE (Computer Aided System Engineering) systems. In this paper, we present a meta-CASE system that provides a web-based user interface and uses an object-relational database system (ORDBMS) as its basis. The use of ORDBMSs allows us to integrate different parts of the system and simplify the creation of meta-CASE and CASE systems. ORDBMSs provide powerful query mechanism. The proposed system allows developers to use queries to evaluate and gradually improve artifacts and calculate values of software measures. We illustrate the use of the systems by using SimpleM modeling language and discuss the use of SQL in the context of queries about artifacts. We have created a prototype of the meta-CASE system by using PostgreSQL™ ORDBMS and PHP scripting language.

  10. Formalizing the definition of meta-analysis in Molecular Ecology.

    Science.gov (United States)

    ArchMiller, Althea A; Bauer, Eric F; Koch, Rebecca E; Wijayawardena, Bhagya K; Anil, Ammu; Kottwitz, Jack J; Munsterman, Amelia S; Wilson, Alan E

    2015-08-01

    Meta-analysis, the statistical synthesis of pertinent literature to develop evidence-based conclusions, is relatively new to the field of molecular ecology, with the first meta-analysis published in the journal Molecular Ecology in 2003 (Slate & Phua 2003). The goal of this article is to formalize the definition of meta-analysis for the authors, editors, reviewers and readers of Molecular Ecology by completing a review of the meta-analyses previously published in this journal. We also provide a brief overview of the many components required for meta-analysis with a more specific discussion of the issues related to the field of molecular ecology, including the use and statistical considerations of Wright's FST and its related analogues as effect sizes in meta-analysis. We performed a literature review to identify articles published as 'meta-analyses' in Molecular Ecology, which were then evaluated by at least two reviewers. We specifically targeted Molecular Ecology publications because as a flagship journal in this field, meta-analyses published in Molecular Ecology have the potential to set the standard for meta-analyses in other journals. We found that while many of these reviewed articles were strong meta-analyses, others failed to follow standard meta-analytical techniques. One of these unsatisfactory meta-analyses was in fact a secondary analysis. Other studies attempted meta-analyses but lacked the fundamental statistics that are considered necessary for an effective and powerful meta-analysis. By drawing attention to the inconsistency of studies labelled as meta-analyses, we emphasize the importance of understanding the components of traditional meta-analyses to fully embrace the strengths of quantitative data synthesis in the field of molecular ecology. © 2015 John Wiley & Sons Ltd.

  11. Estimation of Environment-Related Properties of Chemicals for Design of Sustainable Processes: Development of Group-Contribution+ (GC+) Property Models and Uncertainty Analysis

    Science.gov (United States)

    The aim of this work is to develop group-contribution+ (GC+) method (combined group-contribution (GC) method and atom connectivity index (CI) method) based property models to provide reliable estimations of environment-related properties of organic chemicals together with uncert...

  12. Prevalence of Depression among University Students: A Systematic Review and Meta-Analysis Study

    Directory of Open Access Journals (Sweden)

    Diana Sarokhani

    2013-01-01

    Full Text Available Introduction. Depression is one of the four major diseases in the world and is the most common cause of disability from diseases. The aim of this study is to estimate the prevalence of depression among Iranian university students using meta-analysis method. Materials and Methods. Keyword depression was searched in electronic databases such as PubMed, Scopus, MAGIran, Medlib, and SID. Data was analyzed using meta-analysis (random-effects model. Heterogeneity of studies was assessed using the I2 index. Data was analyzed using STATA software Ver.10. Results. In 35 studies conducted in Iran from 1995 to 2012 with sample size of 9743, prevalence of depression in the university students was estimated to be 33% (95% CI: 32–34. The prevalence of depression among boys was estimated to be 28% (95% CI: 26–30, among girls 23% (95% CI: 22–24, single students 39% (95% CI: 37–41, and married students 20% (95% CI: 17–24. Metaregression model showed that the trend of depression among Iranian students was flat. Conclusions. On the whole, depression is common in university students with no preponderance between males and females and in single students is higher than married ones.

  13. Should in-line filters be used in peripheral intravenous catheters to prevent infusion-related phlebitis? A systematic review of randomized controlled trials.

    Science.gov (United States)

    Niël-Weise, Barbara S; Stijnen, Theo; van den Broek, Peterhans J

    2010-06-01

    In this systematic review, we assessed the effect of in-line filters on infusion-related phlebitis associated with peripheral IV catheters. The study was designed as a systematic review and meta-analysis of randomized controlled trials. We used MEDLINE and the Cochrane Controlled Trial Register up to August 10, 2009. Two reviewers independently assessed trial quality and extracted data. Data on phlebitis were combined when appropriate, using a random-effects model. The impact of the risk of phlebitis in the control group (baseline risk) on the effect of in-line filters was studied by using meta-regression based on the bivariate meta-analysis model. The quality of the evidence was determined by using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) method. Eleven trials (1633 peripheral catheters) were included in this review to compare the effect of in-line filters on the incidence of phlebitis in hospitalized patients. Baseline risks across trials ranged from 23% to 96%. Meta-analysis of all trials showed that in-line filters reduced the risk of infusion-related phlebitis (relative risk, 0.66; 95% confidence interval, 0.43-1.00). This benefit, however, is very uncertain, because the trials had serious methodological shortcomings and meta-analysis revealed marked unexplained statistical heterogeneity (P < 0.0000, I(2) = 90.4%). The estimated benefit did not depend on baseline risk. In-line filters in peripheral IV catheters cannot be recommended routinely, because evidence of their benefit is uncertain.

  14. Likelihood ratio meta-analysis: New motivation and approach for an old method.

    Science.gov (United States)

    Dormuth, Colin R; Filion, Kristian B; Platt, Robert W

    2016-03-01

    A 95% confidence interval (CI) in an updated meta-analysis may not have the expected 95% coverage. If a meta-analysis is simply updated with additional data, then the resulting 95% CI will be wrong because it will not have accounted for the fact that the earlier meta-analysis failed or succeeded to exclude the null. This situation can be avoided by using the likelihood ratio (LR) as a measure of evidence that does not depend on type-1 error. We show how an LR-based approach, first advanced by Goodman, can be used in a meta-analysis to pool data from separate studies to quantitatively assess where the total evidence points. The method works by estimating the log-likelihood ratio (LogLR) function from each study. Those functions are then summed to obtain a combined function, which is then used to retrieve the total effect estimate, and a corresponding 'intrinsic' confidence interval. Using as illustrations the CAPRIE trial of clopidogrel versus aspirin in the prevention of ischemic events, and our own meta-analysis of higher potency statins and the risk of acute kidney injury, we show that the LR-based method yields the same point estimate as the traditional analysis, but with an intrinsic confidence interval that is appropriately wider than the traditional 95% CI. The LR-based method can be used to conduct both fixed effect and random effects meta-analyses, it can be applied to old and new meta-analyses alike, and results can be presented in a format that is familiar to a meta-analytic audience. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Child Wasting in Emergency Pockets: A Meta-Analysis of Small-Scale Surveys from Ethiopia

    Directory of Open Access Journals (Sweden)

    Chiara Altare

    2016-01-01

    Full Text Available Child undernutrition is a major public health concern in Ethiopia (stunting national prevalence: 44%; wasting: 10%, despite the overall improvement in child health status during the last decade. Hundreds of small-scale surveys are conducted in Ethiopia’s emergency pockets under ENCU’s supervision. We reviewed the evidence from small-scale surveys conducted between 2008 and 2013 with two objectives: to provide a summary estimate of wasting prevalence from emergency pockets and to examine reasons for variation in prevalence estimates. We created a dataset by combining data from the Complex Emergency Database, the Famine Early Warning System Network and the Armed Conflict Location Event Data. We conducted a meta-analysis of small-scale surveys using a random effects model with known within-study heterogeneity. The influence of survey covariates on estimated prevalence was investigated with meta-regression techniques. We included 158 surveys in the analysis. A high degree of heterogeneity among surveys was observed. The overall estimate of wasting prevalence was 10.6% (95% CI 9.8–11.4, with differences among regions and between residents and refugees. Meta-regression results showed that vaccination coverage, child mortality, diarrhea prevalence and food insecurity are significantly associated with wasting prevalence. Child care and displacement status were not. Aggregated analysis of small-scale surveys provides insights into the prevalence of wasting and factors explaining its variation. It can also guide survey planning towards areas with limited data availability.

  16. Network meta-analyses performed by contracting companies and commissioned by industry

    NARCIS (Netherlands)

    Schuit, Ewoud; Ioannidis, John P A

    2016-01-01

    Background: Industry commissions contracting companies to perform network meta-analysis for health technology assessment (HTA) and reimbursement submissions. Our objective was to estimate the number of network meta-analyses performed by consulting companies contracted by industry, to assess whether

  17. A framework for the meta-analysis of Bland-Altman studies based on a limits of agreement approach.

    Science.gov (United States)

    Tipton, Elizabeth; Shuster, Jonathan

    2017-10-15

    Bland-Altman method comparison studies are common in the medical sciences and are used to compare a new measure to a gold-standard (often costlier or more invasive) measure. The distribution of these differences is summarized by two statistics, the 'bias' and standard deviation, and these measures are combined to provide estimates of the limits of agreement (LoA). When these LoA are within the bounds of clinically insignificant differences, the new non-invasive measure is preferred. Very often, multiple Bland-Altman studies have been conducted comparing the same two measures, and random-effects meta-analysis provides a means to pool these estimates. We provide a framework for the meta-analysis of Bland-Altman studies, including methods for estimating the LoA and measures of uncertainty (i.e., confidence intervals). Importantly, these LoA are likely to be wider than those typically reported in Bland-Altman meta-analyses. Frequently, Bland-Altman studies report results based on repeated measures designs but do not properly adjust for this design in the analysis. Meta-analyses of Bland-Altman studies frequently exclude these studies for this reason. We provide a meta-analytic approach that allows inclusion of estimates from these studies. This includes adjustments to the estimate of the standard deviation and a method for pooling the estimates based upon robust variance estimation. An example is included based on a previously published meta-analysis. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  18. Lower estimated glomerular filtration rate and higher albuminuria are associated with mortality and end-stage renal disease. A collaborative meta-analysis of kidney disease population cohorts

    DEFF Research Database (Denmark)

    Astor, Brad C; Matsushita, Kunihiro; Gansevoort, Ron T

    2011-01-01

    We studied here the independent associations of estimated glomerular filtration rate (eGFR) and albuminuria with mortality and end-stage renal disease (ESRD) in individuals with chronic kidney disease (CKD). We performed a collaborative meta-analysis of 13 studies totaling 21,688 patients selected...

  19. Prevalence of suicidal ideation in Chinese college students: a meta-analysis.

    Science.gov (United States)

    Li, Zhan-Zhan; Li, Ya-Ming; Lei, Xian-Yang; Zhang, Dan; Liu, Li; Tang, Si-Yuan; Chen, Lizhang

    2014-01-01

    About 1 million people worldwide commit suicide each year, and college students with suicidal ideation are at high risk of suicide. The prevalence of suicidal ideation in college students has been estimated extensively, but quantitative syntheses of overall prevalence are scarce, especially in China. Accurate estimates of prevalence are important for making public policy. In this paper, we aimed to determine the prevalence of suicidal ideation in Chinese college students. Databases including PubMed, Web of Knowledge, Chinese Web of Knowledge, Wangfang (Chinese database) and Weipu (Chinese database) were systematically reviewed to identify articles published between 2004 to July 2013, in either English or Chinese, reporting prevalence estimates of suicidal ideation among Chinese college students. The strategy also included a secondary search of reference lists of records retrieved from databases. Then the prevalence estimates were summarized using a random effects model. The effects of moderator variables on the prevalence estimates were assessed using a meta-regression model. A total of 41 studies involving 160339 college students were identified, and the prevalence ranged from 1.24% to 26.00%. The overall pooled prevalence of suicidal ideation among Chinese college students was 10.72% (95%CI: 8.41% to 13.28%). We noted substantial heterogeneity in prevalence estimates. Subgroup analyses showed that prevalence of suicidal ideation in females is higher than in males. The prevalence of suicidal ideation in Chinese college students is relatively high, although the suicide rate is lower compared with the entire society, suggesting the need for local surveys to inform the development of health services for college students.

  20. Loneliness among people with HIV in relation to locus of control and negative meta-stereotyping

    NARCIS (Netherlands)

    Gordijn, E.H.; Boven, G.

    2009-01-01

    The aim of this research was to examine the relation between locus of control, meta-stereotyping (expectancies about how one's group is stereotyped by another group), and loneliness among people who are HIV-positive. In line with expectations, a survey in the Netherlands among 122 people living with

  1. The role of pre-existing diabetes mellitus on hepatocellular carcinoma occurrence and prognosis: a meta-analysis of prospective cohort studies.

    Directory of Open Access Journals (Sweden)

    Wan-Shui Yang

    Full Text Available The impact of pre-existing diabetes mellitus (DM on hepatocellular carcinoma (HCC occurrence and prognosis is complex and unclear. The aim of this meta-analysis is to evaluate the association between pre-existing diabetes mellitus and hepatocellular carcinoma occurrence and prognosis.We searched PubMed, Embase and the Cochrane Library from their inception to January, 2011 for prospective epidemiological studies assessing the effect of pre-existing diabetes mellitus on hepatocellular carcinoma occurrence, mortality outcomes, cancer recurrence, and treatment-related complications. Study-specific risk estimates were combined by using fixed effect or random effect models.The database search generated a total of 28 prospective studies that met the inclusion criteria. Among these studies, 14 reported the risk of HCC incidence and 6 studies reported risk of HCC specific mortality. Six studies provided a total of 8 results for all-cause mortality in HCC patients. Four studies documented HCC recurrence risks and 2 studies reported risks for hepatic decomposition occurrence in HCC patients. Meta-analysis indicated that pre-existing diabetes mellitus (DM was significantly associated with increased risk of HCC incidence [meta-relative risk (RR = 1.87, 95% confidence interval (CI: 1.15-2.27] and HCC-specific mortality (meta-RR = 1.88, 95%CI: 1.39-2.55 compared with their non-DM counterparts. HCC patients with pre-existing DM had a 38% increased (95% CI: 1.13-1.48 risk of death from all-causes and 91% increased (95%CI: 1.41-2.57 risk of hepatic decomposition occurrence compared to those without DM. In DM patients, the meta-RR for HCC recurrence-free survival was 1.93(95%CI: 1.12-3.33 compared with non-diabetic patients.The findings from the current meta-analysis suggest that DM may be both associated with elevated risks of both HCC incidence and mortality. Furthermore, HCC patients with pre-existing diabetes have a poorer prognosis relative to their

  2. Contributions in Radio Channel Sounding, Modeling, and Estimation

    DEFF Research Database (Denmark)

    Pedersen, Troels

    2009-01-01

    This thesis spans over three strongly related topics in wireless communication: channel-sounding, -modeling, and -estimation. Three main problems are addressed: optimization of spatio-temporal apertures for channel sounding; estimation of per-path power spectral densities (psds); and modeling...... relies on a ``propagation graph'' where vertices  represent scatterers and edges represent the wave propagation conditions between scatterers.  The graph has a recursive structure, which permits modeling of the transfer function of the graph. We derive a closed-form expression of the infinite......-bounce impulse response. This expression is used for simulation of the impulse response of randomly generated propagation graphs. The obtained realizations exhibit the well-observed  exponential power decay versus delay and specular-to-diffuse transition....

  3. Hypothyroidism and carpal tunnel syndrome: a meta-analysis.

    Science.gov (United States)

    Shiri, Rahman

    2014-12-01

    This study aimed to assess the magnitude of the association between hypothyroidism and carpal tunnel syndrome (CTS). Eighteen studies were included in a random-effects meta-analysis. A meta-analysis of the studies that did not control their estimates for any confounder showed an association between a thyroid disease (hypo- or hyperthyroidism) and CTS (N = 9,573, effect size [ES] = 1.32 (95% confidence interval [CI], 1.04-1.68) and between hypothyroidism and CTS (N = 64,531, ES = 2.15 [95% CI, 1.64-2.83]). When a meta-analysis limited to the studies that controlled their estimates for some potential confounders, the association between a thyroid disease and CTS disappeared (N = 4,799, ES = 1.17 [95% CI, 0.71-1.92], I(2) = 0%), and the effect size for hypothyroidism largely attenuated (N = 71,133, ES = 1.44 [95% CI, 1.27-1.63], I(2) = 0%). Moreover, there was evidence of publication bias. This meta-analysis found only a modest association between hypothyroidism and CTS. Confounding and publication bias may still account for part of the remaining excess risk. © 2014 Wiley Periodicals, Inc.

  4. An evaluation of the relations between flow regime components, stream characteristics, species traits and meta-demographic rates of warmwater stream fishes: Implications for aquatic resource management

    Science.gov (United States)

    Peterson, James T.; Shea, C.P.

    2015-01-01

    Fishery biologists are increasingly recognizing the importance of considering the dynamic nature of streams when developing streamflow policies. Such approaches require information on how flow regimes influence the physical environment and how those factors, in turn, affect species-specific demographic rates. A more cost-effective alternative could be the use of dynamic occupancy models to predict how species are likely to respond to changes in flow. To appraise the efficacy of this approach, we evaluated relative support for hypothesized effects of seasonal streamflow components, stream channel characteristics, and fish species traits on local extinction, colonization, and recruitment (meta-demographic rates) of stream fishes. We used 4 years of seasonal fish collection data from 23 streams to fit multistate, multiseason occupancy models for 42 fish species in the lower Flint River Basin, Georgia. Modelling results suggested that meta-demographic rates were influenced by streamflows, particularly short-term (10-day) flows. Flow effects on meta-demographic rates also varied with stream size, channel morphology, and fish species traits. Small-bodied species with generalized life-history characteristics were more resilient to flow variability than large-bodied species with specialized life-history characteristics. Using this approach, we simplified the modelling framework, thereby facilitating the development of dynamic, spatially explicit evaluations of the ecological consequences of water resource development activities over broad geographic areas. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

  5. Values of natural and human-made wetlands: A meta-analysis

    NARCIS (Netherlands)

    Ghermandi, A.; van den Bergh, J.C.J.M.; Brander, L.M.; de Groot, H.L.F.; Nunes, P.A.L.D.

    2010-01-01

    The values of goods and services provided by wetland ecosystems are examined through a meta-analysis of an expanded database of wetland value estimates and with a focus on human-made wetlands. This study extends and improves upon previous meta-analyses of the wetland valuation literature in terms of

  6. Association between type 1 diabetes mellitus and risk of epilepsy: A meta-analysis of observational studies.

    Science.gov (United States)

    Yan, Dandan; Zhao, Enfa; Zhang, Hong; Luo, Xiaohui; Du, Yajuan

    2017-01-01

    A potential association between type 1 diabetes mellitus and subsequent epilepsy emerged in recent studies. This study aimed to evaluate the possible relationship between type 1 diabetes mellitus and epilepsy using meta-analysis. Pubmed, ISI Web of Knowledge, Embase and Cochrane Library were searched for potential studies of the association between type 1 diabetes mellitus and epilepsy from inception to February 1, 2017. Two investigators independently screened studies for inclusion and extracted related data; discrepancies were solved by consensus. Random effects model of Hazard Ratio (HR) was used to estimate the strength of association. We identified 13 papers from potentially relevant articles of which 3 cohort studies met the inclusion criteria. Random effects meta-analysis showed that type 1 diabetes mellitus was associated with an increased risk of epilepsy with HR = 3.29 (95% CI: 2.61-4.14; I 2 = 0, p = 0.689). Similar results were observed in type 1 diabetes mellitus patents younger than 18-years-old with HR = 2.96 (95% CI: 2.28-3.84; I 2 = 0, p = 0.571). Meta-analysis of 2 studies that adjusted for potential confounders yielded an increased risk of epilepsy with HR = 2.89 (95% CI: 2.26-3.70; I 2 = 0, p = 0.831). The meta-analysis indicates that type 1 diabetes mellitus is associated with a statistically significant increased risk for epilepsy compared to those without type 1 diabetes mellitus.

  7. Comparison of the effect between pioglitazone and metformin in treating patients with PCOS:a meta-analysis.

    Science.gov (United States)

    Xu, Yifeng; Wu, Yanxiang; Huang, Qin

    2017-10-01

    Pioglitazone was used to treat patients of PCOS in many researches, but the treatment has not been recognized by public or recommended by all the guidelines. We conducted a meta-analysis of the related literatures to objectively evaluate the clinical effectiveness and safety by comparing pioglitazone with metformin administrated by PCOS patients. Searches were performed in Cochrane Library, EMBASE and PubMed (last updated December 2016). Eleven studies among 486 related articles were identified through searches. Fixed effects and random effects models were used to calculate the overall risk estimates. The results of the meta-analysis suggest that improvement of the menstrual cycle and ovulation in pioglitazone treatment group was better than metformin group [OR = 2.31, 95% CI (1.37, 3.91), P treatment group was better than pioglitazone group [SMD = 0.29, 95% CI (0.0, 0.59), P = 0.048, I 2  = 0.0%]. BMI was more elevated in pioglitazone group than in metformin group [SMD = 0.83, 95% CI (0.24, 1.41), P = 0.006, I 2  = 82.8%]. There were no significant differences of the other data between the two groups. This meta-analysis indicated that pioglitazone ameliorated menstrual cycle and ovulation better than metformin and metformin ameliorated BMI and F-G scores better than pioglitazone in treating patients with PCOS. Pioglitazone might be a good choice for the patients with PCOS who were intolerant or invalid to metformin for the treatment.

  8. A Two-Stage Approach to Synthesizing Covariance Matrices in Meta-Analytic Structural Equation Modeling

    Science.gov (United States)

    Cheung, Mike W. L.; Chan, Wai

    2009-01-01

    Structural equation modeling (SEM) is widely used as a statistical framework to test complex models in behavioral and social sciences. When the number of publications increases, there is a need to systematically synthesize them. Methodology of synthesizing findings in the context of SEM is known as meta-analytic SEM (MASEM). Although correlation…

  9. Cancer risk of low dose/low dose rate radiation: a meta-analysis of cancer data of mammals exposed to low doses of radiation

    International Nuclear Information System (INIS)

    Ogata, Hiromitsu; Magae, Junji

    2008-01-01

    Full text: Linear No Threshold (LNT) model is a basic theory for radioprotection, but the adaptability of this hypothesis to biological responses at low doses or at low dose rates is not sufficiently investigated. Simultaneous consideration of the cumulative dose and the dose rate is necessary for evaluating the risk of long-term exposure to ionizing radiation at low dose. This study intends to examine several numerical relationships between doses and dose rates in biological responses to gamma radiation. Collected datasets on the relationship between dose and the incidence of cancer in mammals exposed to low doses of radiation were analysed using meta-regression models and modified exponential (MOE) model, which we previously published, that predicts irradiation time-dependent biological response at low dose rate ionizing radiation. Minimum doses of observable risk and effective doses with a variety of dose rates were calculated using parameters estimated by fitting meta-regression models to the data and compared them with other statistical models that find values corresponding to 'threshold limits'. By fitting a weighted regression model (fixed-effects meta-regression model) to the data on risk of all cancers, it was found that the log relative risk [log(RR)] increased as the total exposure dose increased. The intersection of this regression line with the x-axis denotes the minimum dose of observable risk. These estimated minimum doses and effective doses increased with decrease of dose rate. The goodness of fits of MOE-model depended on cancer types, but the total cancer risk is reduced when dose rates are very low. The results suggest that dose response curve for cancer risk is remarkably affected by dose rate and that dose rate effect changes as a function of dose rate. For scientific discussion on the low dose exposure risk and its uncertainty, the term 'threshold' should be statistically defined, and dose rate effects should be included in the risk

  10. A Meta-Analysis of the Relations among Training Criteria

    National Research Council Canada - National Science Library

    Alliger, George

    1998-01-01

    .... Meta-analysis results among criteria using this framework include the finding of substantial reliabilities across training criteria and reasonable convergence among subdivisions of criteria within a larger level...

  11. The Trans-Contextual Model of Autonomous Motivation in Education: Conceptual and Empirical Issues and Meta-Analysis.

    Science.gov (United States)

    Hagger, Martin S; Chatzisarantis, Nikos L D

    2016-06-01

    The trans-contextual model outlines the processes by which autonomous motivation toward activities in a physical education context predicts autonomous motivation toward physical activity outside of school, and beliefs about, intentions toward, and actual engagement in, out-of-school physical activity. In the present article, we clarify the fundamental propositions of the model and resolve some outstanding conceptual issues, including its generalizability across multiple educational domains, criteria for its rejection or failed replication, the role of belief-based antecedents of intentions, and the causal ordering of its constructs. We also evaluate the consistency of model relationships in previous tests of the model using path-analytic meta-analysis. The analysis supported model hypotheses but identified substantial heterogeneity in the hypothesized relationships across studies unattributed to sampling and measurement error. Based on our meta-analysis, future research needs to provide further replications of the model in diverse educational settings beyond physical education and test model hypotheses using experimental methods.

  12. Group-Contribution based Property Estimation and Uncertainty analysis for Flammability-related Properties

    DEFF Research Database (Denmark)

    Frutiger, Jerome; Marcarie, Camille; Abildskov, Jens

    2016-01-01

    regression and outlier treatment have been applied to achieve high accuracy. Furthermore, linear error propagation based on covariance matrix of estimated parameters was performed. Therefore, every estimated property value of the flammability-related properties is reported together with its corresponding 95......%-confidence interval of the prediction. Compared to existing models the developed ones have a higher accuracy, are simple to apply and provide uncertainty information on the calculated prediction. The average relative error and correlation coefficient are 11.5% and 0.99 for LFL, 15.9% and 0.91 for UFL, 2...

  13. Meta-Theoretical Contributions to the Constitution of a Model-Based Didactics of Science

    Science.gov (United States)

    Ariza, Yefrin; Lorenzano, Pablo; Adúriz-Bravo, Agustín

    2016-10-01

    There is nowadays consensus in the community of didactics of science (i.e. science education understood as an academic discipline) regarding the need to include the philosophy of science in didactical research, science teacher education, curriculum design, and the practice of science education in all educational levels. Some authors have identified an ever-increasing use of the concept of `theoretical model', stemming from the so-called semantic view of scientific theories. However, it can be recognised that, in didactics of science, there are over-simplified transpositions of the idea of model (and of other meta-theoretical ideas). In this sense, contemporary philosophy of science is often blurred or distorted in the science education literature. In this paper, we address the discussion around some meta-theoretical concepts that are introduced into didactics of science due to their perceived educational value. We argue for the existence of a `semantic family', and we characterise four different versions of semantic views existing within the family. In particular, we seek to contribute to establishing a model-based didactics of science mainly supported in this semantic family.

  14. Limitations and risks of meta-analyses of longevity studies

    DEFF Research Database (Denmark)

    Sebastiani, Paola; Bae, Harold; Gurinovich, Anastasia

    2017-01-01

    Searching for genetic determinants of human longevity has been challenged by the rarity of data sets with large numbers of individuals who have reached extreme old age, inconsistent definitions of the phenotype, and the difficulty of defining appropriate controls. Meta-analysis - a statistical...... method to summarize results from different studies - has become a common tool in genetic epidemiology to accrue large sample sizes for powerful genetic association studies. In conducting a meta-analysis of studies of human longevity however, particular attention must be made to the definition of cases...... and controls (including their health status) and on the effect of possible confounders such as sex and ethnicity upon the genetic effect to be estimated. We will show examples of how a meta-analysis can inflate the false negative rates of genetic association studies or it can bias estimates of the association...

  15. The impact of childbirth-related post-traumatic stress on a couple's relationship: a systematic review and meta-synthesis.

    Science.gov (United States)

    Delicate, A; Ayers, S; Easter, A; McMullen, S

    2018-02-01

    This review aimed to identify the impact of childbirth-related post-traumatic stress disorder (PTSD) or symptoms (PTSS) on a couple's relationship. Childbirth can be psychologically traumatic and can lead to PTSD. There is emerging evidence that experiencing a traumatic birth can affect the quality of the couple's relationship. This is an important issue because poor-quality relationships can impact on the well-being of partners, their parenting and the welfare of the infant. A systematic search was conducted of Amed, CENTRAL, Cinahl, Embase, Maternity and Infant Care, Medline, MITCognet, POPLINE, PsycARTICLES, PsycBITE, PsycINFO, Pubmed and Science Direct. Additionally, grey literature, citation and reference searches were conducted. Papers were eligible for inclusion if they reported qualitative data about parents who had experienced childbirth and measures of PTSD or PTSS and the relationship were taken. Analysis was conducted using meta-ethnography. Seven studies were included in the meta-synthesis. Results showed that childbirth-related PTSD or PTSS can have a perceived impact on the couple's relationship and five themes were identified: negative emotions; lack of understanding and support; loss of intimacy; strain on the relationship; and strengthened relationships. A model of proposed interaction between these themes is presented. The impact of childbirth-related PTSD or PTSS on the couple's relationships is complex. As the quality of the couple relationship is important to family well-being, it is important that healthcare professionals are aware of the impact of experiencing psychologically traumatic childbirth as impetus for prevention and support.

  16. Network meta-analysis: a technique to gather evidence from direct and indirect comparisons

    Science.gov (United States)

    2017-01-01

    Systematic reviews and pairwise meta-analyses of randomized controlled trials, at the intersection of clinical medicine, epidemiology and statistics, are positioned at the top of evidence-based practice hierarchy. These are important tools to base drugs approval, clinical protocols and guidelines formulation and for decision-making. However, this traditional technique only partially yield information that clinicians, patients and policy-makers need to make informed decisions, since it usually compares only two interventions at the time. In the market, regardless the clinical condition under evaluation, usually many interventions are available and few of them have been studied in head-to-head studies. This scenario precludes conclusions to be drawn from comparisons of all interventions profile (e.g. efficacy and safety). The recent development and introduction of a new technique – usually referred as network meta-analysis, indirect meta-analysis, multiple or mixed treatment comparisons – has allowed the estimation of metrics for all possible comparisons in the same model, simultaneously gathering direct and indirect evidence. Over the last years this statistical tool has matured as technique with models available for all types of raw data, producing different pooled effect measures, using both Frequentist and Bayesian frameworks, with different software packages. However, the conduction, report and interpretation of network meta-analysis still poses multiple challenges that should be carefully considered, especially because this technique inherits all assumptions from pairwise meta-analysis but with increased complexity. Thus, we aim to provide a basic explanation of network meta-analysis conduction, highlighting its risks and benefits for evidence-based practice, including information on statistical methods evolution, assumptions and steps for performing the analysis. PMID:28503228

  17. Meta-analytic approaches to determine gender differences in the age-incidence characteristics of schizophrenia and related psychoses.

    Science.gov (United States)

    Jackson, Dan; Kirkbride, James; Croudace, Tim; Morgan, Craig; Boydell, Jane; Errazuriz, Antonia; Murray, Robin M; Jones, Peter B

    2013-03-01

    A recent systematic review and meta-analysis of the incidence and prevalence of schizophrenia and other psychoses in England investigated the variation in the rates of psychotic disorders. However, some of the questions of interest, and the data collected to answer these, could not be adequately addressed using established meta-analysis techniques. We developed a novel statistical method, which makes combined use of fractional polynomials and meta-regression. This was used to quantify the evidence of gender differences and a secondary peak onset in women, where the outcome of interest is the incidence of schizophrenia. Statistically significant and epidemiologically important effects were obtained using our methods. Our analysis is based on data from four studies that provide 50 incidence rates, stratified by age and gender. We describe several variations of our method, in particular those that might be used where more data is available, and provide guidance for assessing the model fit. Copyright © 2013 John Wiley & Sons, Ltd.

  18. Meta-analysis for heritability of estimates development and production traits of Coffea canephora PierreMeta-análise para estimativas de herdabilidade de características do desenvolvimento e produção do Coffea canephora Pierre

    Directory of Open Access Journals (Sweden)

    Telde Natel Custódio

    2012-12-01

    Full Text Available Heritability of estimates related to development and production traits of coffee (C. canephora are widely used informations in genetic improvement programs. However, because of the great number of scientific papers published in the recent years, conflicting conclusions are observed. Thus, to summarize such information has become a necessity. In this context, a meta-analysis was conducted with the objective of summarizing the heritability estimates of traits related to the development and production of C. canephora. Heritability estimates were appraised regarding the following traits: plant height, diameter of the canopy, fruit size, maturation cycle, bean production (kg ha-1, maturation uniformity, flat bean percentage, empty bean percentage, peaberry percentage, moisture percentage of the bean at harvest, cherry coffee and coffee coconut ratio, cherry coffee and benefited coffee ratio, coffee coconut and benefited coffee ratio, percentage of medium sieve and yield. The data regarding the heritability estimates are from scientific articles published in national and international journals, congress annals, and post-graduation thesis and dissertations. The most of the appraised traits, except the diameter of the canopy and of the yield, are highly inherited, reflecting the high genetic variety of coffee plants, and possible for satisfactory genetic gains to be reached in improvement programs in which those traits are evaluated. The use of techniques of meta-analysis shows to be efficient to synthesize the results of studies of estimation of heritability obtained in experiments evaluating the characteristics related to development and production C. canephora.Estimativas de herdabilidade de características relacionadas ao desenvolvimento e produção de cafeeiros (C. canephora são informações muito utilizadas em programas de melhoramento genético, no entanto, em virtude do grande número de trabalhos científicos publicados nos últimos anos

  19. Cancer Related-Knowledge - Small Area Estimates

    Science.gov (United States)

    These model-based estimates are produced using statistical models that combine data from the Health Information National Trends Survey, and auxiliary variables obtained from relevant sources and borrow strength from other areas with similar characteristics.

  20. A meta-analysis of the factors influencing development rate variation in Aedes aegypti (Diptera: Culicidae)

    Science.gov (United States)

    2014-01-01

    Background Development rates of Aedes aegypti are known to vary with respect to many abiotic and biotic factors including temperature, resource availability, and intraspecific competition. The relative importance of these factors and their interactions are not well established across populations. We performed meta-analysis on a dataset of development rate estimates from 49 studies. Results Meta-analytic results indicated that the environmental factor of temperature is sufficient to explain development rate variability in Ae. aegypti. While diet and density may greatly impact other developmental phenotypes, these results suggest that for development rate these factors should never be considered to the exclusion of temperature. The effect of temperature on development rate is not homogenous or constant. The sources of heterogeneity of the effect of temperature are difficult to analyze due to lack of consistent reporting of larval rearing methods. Conclusions Temperature is the most important ecological determinant of development rate in Ae. aegypti, but its effect is heterogeneous. Ignoring this heterogeneity is problematic for models of vector population and vector-borne disease transmission. PMID:24495345

  1. Meta-analysis in plant pathology: synthesizing research results.

    Science.gov (United States)

    Rosenberg, M S; Garrett, K A; Su, Z; Bowden, R L

    2004-09-01

    ABSTRACT Meta-analysis is a set of statistical procedures for synthesizing research results from a number of different studies. An estimate of a statistical effect, such as the difference in disease severity for plants with or without a management treatment, is collected from each study along with a measure of the variance of the estimate of the effect. Combining results from different studies will generally result in increased statistical power so that it is easier to detect small effects. Combining results from different studies may also make it possible to compare the size of the effect as a function of other predictor variables such as geographic region or pathogen species. We present a review of the basic methodology for meta-analysis. We also present an example of meta-analysis of the relationship between disease severity and yield loss for foliar wheat diseases, based on data collected from a decade of fungicide and nematicide test results.

  2. Testing moderation in network meta-analysis with individual participant data

    Science.gov (United States)

    Dagne, Getachew A.; Brown, C. Hendricks; Howe, George; Kellam, Sheppard G.; Liu, Lei

    2016-01-01

    Summary Meta-analytic methods for combining data from multiple intervention trials are commonly used to estimate the effectiveness of an intervention. They can also be extended to study comparative effectiveness, testing which of several alternative interventions is expected to have the strongest effect. This often requires network meta-analysis (NMA), which combines trials involving direct comparison of two interventions within the same trial and indirect comparisons across trials. In this paper, we extend existing network methods for main effects to examining moderator effects, allowing for tests of whether intervention effects vary for different populations or when employed in different contexts. In addition, we study how the use of individual participant data (IPD) may increase the sensitivity of NMA for detecting moderator effects, as compared to aggregate data NMA that employs study-level effect sizes in a meta-regression framework. A new network meta-analysis diagram is proposed. We also develop a generalized multilevel model for NMA that takes into account within- and between-trial heterogeneity, and can include participant-level covariates. Within this framework we present definitions of homogeneity and consistency across trials. A simulation study based on this model is used to assess effects on power to detect both main and moderator effects. Results show that power to detect moderation is substantially greater when applied to IPD as compared to study-level effects. We illustrate the use of this method by applying it to data from a classroom-based randomized study that involved two sub-trials, each comparing interventions that were contrasted with separate control groups. PMID:26841367

  3. Advances in meta-analysis: examples from internal medicine to neurology.

    Science.gov (United States)

    Copetti, Massimiliano; Fontana, Andrea; Graziano, Giusi; Veneziani, Federica; Siena, Federica; Scardapane, Marco; Lucisano, Giuseppe; Pellegrini, Fabio

    2014-01-01

    We review the state of the art in meta-analysis and data pooling following the evolution of the statistical models employed. Starting from a classic definition of meta-analysis of published data, a set of apparent antinomies which characterized the development of the meta-analytic tools are reconciled in dichotomies where the second term represents a possible generalization of the first one. Particular attention is given to the generalized linear mixed models as an overall framework for meta-analysis. Bayesian meta-analysis is discussed as a further possibility of generalization for sensitivity analysis and the use of priors as a data augmentation approach. We provide relevant examples to underline how the need for adequate methods to solve practical issues in specific areas of research have guided the development of advanced methods in meta-analysis. We show how all the advances in meta-analysis naturally merge into the unified framework of generalized linear mixed models and reconcile apparently conflicting approaches. All these complex models can be easily implemented with the standard commercial software available. © 2013 S. Karger AG, Basel.

  4. Comparing interval estimates for small sample ordinal CFA models.

    Science.gov (United States)

    Natesan, Prathiba

    2015-01-01

    Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading

  5. PARAMETER ESTIMATION AND MODEL SELECTION FOR INDOOR ENVIRONMENTS BASED ON SPARSE OBSERVATIONS

    Directory of Open Access Journals (Sweden)

    Y. Dehbi

    2017-09-01

    Full Text Available This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

  6. Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations

    Science.gov (United States)

    Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.

    2017-09-01

    This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

  7. Management of Listeria monocytogenes in fermented sausages using the Food Safety Objective concept underpinned by stochastic modeling and meta-analysis.

    Science.gov (United States)

    Mataragas, M; Alessandria, V; Rantsiou, K; Cocolin, L

    2015-08-01

    In the present work, a demonstration is made on how the risk from the presence of Listeria monocytogenes in fermented sausages can be managed using the concept of Food Safety Objective (FSO) aided by stochastic modeling (Bayesian analysis and Monte Carlo simulation) and meta-analysis. For this purpose, the ICMSF equation was used, which combines the initial level (H0) of the hazard and its subsequent reduction (ΣR) and/or increase (ΣI) along the production chain. Each element of the equation was described by a distribution to investigate the effect not only of the level of the hazard, but also the effect of the accompanying variability. The distribution of each element was determined by Bayesian modeling (H0) and meta-analysis (ΣR and ΣI). The output was a normal distribution N(-5.36, 2.56) (log cfu/g) from which the percentage of the non-conforming products, i.e. the fraction above the FSO of 2 log cfu/g, was estimated at 0.202%. Different control measures were examined such as lowering initial L. monocytogenes level and inclusion of an additional killing step along the process resulting in reduction of the non-conforming products from 0.195% to 0.003% based on the mean and/or square-root change of the normal distribution, and 0.001%, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. Sensitivity Analysis of Simulation Models

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2009-01-01

    This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial two-level designs for first-order polynomial

  9. The prevalence of chronic fatigue syndrome/ myalgic encephalomyelitis: a meta-analysis

    Directory of Open Access Journals (Sweden)

    Johnston S

    2013-03-01

    Full Text Available Samantha Johnston,1 Ekua W Brenu,1 Donald Staines,1,2 Sonya Marshall-Gradisnik1 1Griffith Health Institute, School of Medical Sciences, National Centre for Neuroimmunology and Emerging Diseases, Griffith University, Parklands, QLD, Australia; 2Gold Coast Public Health Unit, Queensland Health, Robina, QLD, Australia Purpose: To perform a meta-analysis to examine variability among prevalence estimates for CFS/ME, according to the method of assessment used. Methods: Databases were systematically searched for studies on CFS/ME prevalence in adults that applied the 1994 Centers for Disease Control (CDC case definition.1 Estimates were categorized into two methods of assessment: self-reporting of symptoms versus clinical assessment of symptoms. Meta-analysis was performed to pool prevalences by assessment using random effects modeling. This was stratified by sample setting (community or primary care and heterogeneity was examined using the I2 statistic. Results: Of 216 records found, 14 studies were considered suitable for inclusion. The pooled prevalence for self-reporting assessment was 3.28% (95% CI: 2.24–4.33 and 0.76% (95% CI: 0.23–1.29 for clinical assessment. High variability was observed among self-reported estimates, while clinically assessed estimates showed greater consistency. Conclusion: The observed heterogeneity in CFS/ME prevalence may be due to differences in method of assessment. Stakeholders should be cautious of prevalence determined by the self-reporting of symptoms alone. The 1994 CDC case definition appeared to be the most reliable clinical assessment tool available at the time of these studies. Improving clinical case definitions and their adoption internationally will enable better comparisons of findings and inform health systems about the true burden of CFS/ME. Keywords: chronic fatigue syndrome, myalgic encephalomyelitis, prevalence, meta-analysis

  10. Capital-Energy Substitution and Shifts in Factor Demand. A Meta-Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Koetse, M.J. [Department of Spatial Economics, Vrije Universiteit Amsterdam (Netherlands); De Groot, Henri L.F. [Tinbergen Institute, Amsterdam (Netherlands); Florax, R.J.G.M. [Department of Agricultural Economics, Purdue University, West Lafayette (United States)

    2006-07-01

    This paper presents results of a meta-regression analysis on empirical estimates of capital-energy substitution. Theoretically it is clear that a distinction should be made between Morishima substitution elasticities and cross-price elasticities. The former represent purely technical substitution possibilities while the latter include an income effect and therefore represent economic substitution potential. We estimate a meta-regression model with separate coefficients for the two elasticity samples. Our findings suggest that primary model assumptions on returns to scale, technological change and separability of input factors matter for the outcome of a primary study. Aggregation of variables and the type of data used in empirical research are also relevant sources of systematic effect-size variation. Taking these factors into consideration, we compute ideal-typical elasticities for the short, medium and long run. The resulting figures clearly show that substitution elasticities are substantially higher than cross price elasticities. Therefore, despite considerable technical opportunities for capital-energy substitution, they are almost entirely outweighed by the negative income effect brought about by energy price increases; the short and medium run cross price elasticities are not statistically different from zero. In the long run this pattern does not hold. Our findings therefore suggest that actual changes in the demand for capital due to energy price increases take time.

  11. Eliciting mixed emotions: A meta-analysis comparing models, types and measures.

    Directory of Open Access Journals (Sweden)

    Raul eBerrios

    2015-04-01

    Full Text Available The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model – dimensional or discrete – as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative. The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (dIG+ = .77, which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought.

  12. Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review.

    Science.gov (United States)

    Weir, Christopher J; Butcher, Isabella; Assi, Valentina; Lewis, Stephanie C; Murray, Gordon D; Langhorne, Peter; Brady, Marian C

    2018-03-07

    Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis. We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios. For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally

  13. Graph Regularized Meta-path Based Transductive Regression in Heterogeneous Information Network.

    Science.gov (United States)

    Wan, Mengting; Ouyang, Yunbo; Kaplan, Lance; Han, Jiawei

    2015-01-01

    A number of real-world networks are heterogeneous information networks, which are composed of different types of nodes and links. Numerical prediction in heterogeneous information networks is a challenging but significant area because network based information for unlabeled objects is usually limited to make precise estimations. In this paper, we consider a graph regularized meta-path based transductive regression model ( Grempt ), which combines the principal philosophies of typical graph-based transductive classification methods and transductive regression models designed for homogeneous networks. The computation of our method is time and space efficient and the precision of our model can be verified by numerical experiments.

  14. Association between increase in fixed penalties and road safety outcomes: A meta-analysis.

    Science.gov (United States)

    Elvik, Rune

    2016-07-01

    Studies that have evaluated the association between increases in traffic fine amounts (fixed penalties) and changes in compliance with road traffic law or the number of accidents are synthesised by means of meta-analysis. The studies were few and different in many respects. Nine studies were included in the meta-analysis of changes in compliance. Four studies were included in the meta-analysis of changes in accidents. Increasing traffic fines was found to be associated with small changes in the rate of violations. The changes were non-linear. For increases up to about 100%, violations were reduced. For larger increases, no reduction in violations was found. A small reduction in fatal accidents was associated with increased fixed penalties, varying between studies from less than 1-12%. The main pattern of changes in violations was similar in the fixed-effects and random-effects models of meta-analysis, meta-regression and when simple (non-weighted) mean values were computed. The main findings are thus robust, although most of the primary studies did not control very well for potentially confounding factors. Summary estimates of changes in violations or accidents should be treated as provisional and do not necessarily reflect causal relationships. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. A Simple Plasma Retinol Isotope Ratio Method for Estimating β-Carotene Relative Bioefficacy in Humans: Validation with the Use of Model-Based Compartmental Analysis.

    Science.gov (United States)

    Ford, Jennifer Lynn; Green, Joanne Balmer; Lietz, Georg; Oxley, Anthony; Green, Michael H

    2017-09-01

    Background: Provitamin A carotenoids are an important source of dietary vitamin A for many populations. Thus, accurate and simple methods for estimating carotenoid bioefficacy are needed to evaluate the vitamin A value of test solutions and plant sources. β-Carotene bioefficacy is often estimated from the ratio of the areas under plasma isotope response curves after subjects ingest labeled β-carotene and a labeled retinyl acetate reference dose [isotope reference method (IRM)], but to our knowledge, the method has not yet been evaluated for accuracy. Objectives: Our objectives were to develop and test a physiologically based compartmental model that includes both absorptive and postabsorptive β-carotene bioconversion and to use the model to evaluate the accuracy of the IRM and a simple plasma retinol isotope ratio [(RIR), labeled β-carotene-derived retinol/labeled reference-dose-derived retinol in one plasma sample] for estimating relative bioefficacy. Methods: We used model-based compartmental analysis (Simulation, Analysis and Modeling software) to develop and apply a model that provided known values for β-carotene bioefficacy. Theoretical data for 10 subjects were generated by the model and used to determine bioefficacy by RIR and IRM; predictions were compared with known values. We also applied RIR and IRM to previously published data. Results: Plasma RIR accurately predicted β-carotene relative bioefficacy at 14 d or later. IRM also accurately predicted bioefficacy by 14 d, except that, when there was substantial postabsorptive bioconversion, IRM underestimated bioefficacy. Based on our model, 1-d predictions of relative bioefficacy include absorptive plus a portion of early postabsorptive conversion. Conclusion: The plasma RIR is a simple tracer method that accurately predicts β-carotene relative bioefficacy based on analysis of one blood sample obtained at ≥14 d after co-ingestion of labeled β-carotene and retinyl acetate. The method also provides

  16. A distributed approach for parameters estimation in System Biology models

    International Nuclear Information System (INIS)

    Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

    2009-01-01

    Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

  17. Insights into the genetic architecture of early stage age-related macular degeneration: a genome-wide association study meta-analysis.

    Directory of Open Access Journals (Sweden)

    Elizabeth G Holliday

    Full Text Available Genetic factors explain a majority of risk variance for age-related macular degeneration (AMD. While genome-wide association studies (GWAS for late AMD implicate genes in complement, inflammatory and lipid pathways, the genetic architecture of early AMD has been relatively under studied. We conducted a GWAS meta-analysis of early AMD, including 4,089 individuals with prevalent signs of early AMD (soft drusen and/or retinal pigment epithelial changes and 20,453 individuals without these signs. For various published late AMD risk loci, we also compared effect sizes between early and late AMD using an additional 484 individuals with prevalent late AMD. GWAS meta-analysis confirmed previously reported association of variants at the complement factor H (CFH (peak P = 1.5×10(-31 and age-related maculopathy susceptibility 2 (ARMS2 (P = 4.3×10(-24 loci, and suggested Apolipoprotein E (ApoE polymorphisms (rs2075650; P = 1.1×10(-6 associated with early AMD. Other possible loci that did not reach GWAS significance included variants in the zinc finger protein gene GLI3 (rs2049622; P = 8.9×10(-6 and upstream of GLI2 (rs6721654; P = 6.5×10(-6, encoding retinal Sonic hedgehog signalling regulators, and in the tyrosinase (TYR gene (rs621313; P = 3.5×10(-6, involved in melanin biosynthesis. For a range of published, late AMD risk loci, estimated effect sizes were significantly lower for early than late AMD. This study confirms the involvement of multiple established AMD risk variants in early AMD, but suggests weaker genetic effects on the risk of early AMD relative to late AMD. Several biological processes were suggested to be potentially specific for early AMD, including pathways regulating RPE cell melanin content and signalling pathways potentially involved in retinal regeneration, generating hypotheses for further investigation.

  18. Estimating Drilling Cost and Duration Using Copulas Dependencies Models

    Directory of Open Access Journals (Sweden)

    M. Al Kindi

    2017-03-01

    Full Text Available Estimation of drilling budget and duration is a high-level challenge for oil and gas industry. This is due to the many uncertain activities in the drilling procedure such as material prices, overhead cost, inflation, oil prices, well type, and depth of drilling. Therefore, it is essential to consider all these uncertain variables and the nature of relationships between them. This eventually leads into the minimization of the level of uncertainty and yet makes a "good" estimation points for budget and duration given the well type. In this paper, the copula probability theory is used in order to model the dependencies between cost/duration and MRI (mechanical risk index. The MRI is a mathematical computation, which relates various drilling factors such as: water depth, measured depth, true vertical depth in addition to mud weight and horizontal displacement. In general, the value of MRI is utilized as an input for the drilling cost and duration estimations. Therefore, modeling the uncertain dependencies between MRI and both cost and duration using copulas is important. The cost and duration estimates for each well were extracted from the copula dependency model where research study simulate over 10,000 scenarios. These new estimates were later compared to the actual data in order to validate the performance of the procedure. Most of the wells show moderate - weak relationship of MRI dependence, which means that the variation in these wells can be related to MRI but to the extent that it is not the primary source.

  19. Parameter Estimation of a Reliability Model of Demand-Caused and Standby-Related Failures of Safety Components Exposed to Degradation by Demand Stress and Ageing That Undergo Imperfect Maintenance

    Directory of Open Access Journals (Sweden)

    S. Martorell

    2017-01-01

    Full Text Available One can find many reliability, availability, and maintainability (RAM models proposed in the literature. However, such models become more complex day after day, as there is an attempt to capture equipment performance in a more realistic way, such as, explicitly addressing the effect of component ageing and degradation, surveillance activities, and corrective and preventive maintenance policies. Then, there is a need to fit the best model to real data by estimating the model parameters using an appropriate tool. This problem is not easy to solve in some cases since the number of parameters is large and the available data is scarce. This paper considers two main failure models commonly adopted to represent the probability of failure on demand (PFD of safety equipment: (1 by demand-caused and (2 standby-related failures. It proposes a maximum likelihood estimation (MLE approach for parameter estimation of a reliability model of demand-caused and standby-related failures of safety components exposed to degradation by demand stress and ageing that undergo imperfect maintenance. The case study considers real failure, test, and maintenance data for a typical motor-operated valve in a nuclear power plant. The results of the parameters estimation and the adoption of the best model are discussed.

  20. The Relation between Self-Regulated Learning and Academic Achievement across Childhood and Adolescence: A Meta-Analysis

    Science.gov (United States)

    Dent, Amy L.; Koenka, Alison C.

    2016-01-01

    This research synthesis explores how academic achievement relates to two main components of self-regulated learning for students in elementary and secondary school. Two meta-analyses integrated previous findings on (1) the defining metacognitive processes of self-regulated learning and (2) students' use of cognitive strategies. Overall…