Assessing moderated mediation in linear models requires fewer confounding assumptions than assessing mediation.

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Loeys, Tom; Talloen, Wouter; Goubert, Liesbet; Moerkerke, Beatrijs; Vansteelandt, Stijn

2016-11-01

It is well known from the mediation analysis literature that the identification of direct and indirect effects relies on strong no unmeasured confounding assumptions of no unmeasured confounding. Even in randomized studies the mediator may still be correlated with unobserved prognostic variables that affect the outcome, in which case the mediator's role in the causal process may not be inferred without bias. In the behavioural and social science literature very little attention has been given so far to the causal assumptions required for moderated mediation analysis. In this paper we focus on the index for moderated mediation, which measures by how much the mediated effect is larger or smaller for varying levels of the moderator. We show that in linear models this index can be estimated without bias in the presence of unmeasured common causes of the moderator, mediator and outcome under certain conditions. Importantly, one can thus use the test for moderated mediation to support evidence for mediation under less stringent confounding conditions. We illustrate our findings with data from a randomized experiment assessing the impact of being primed with social deception upon observer responses to others' pain, and from an observational study of individuals who ended a romantic relationship assessing the effect of attachment anxiety during the relationship on mental distress 2 years after the break-up. © 2016 The British Psychological Society.

Interpretational confounding is due to misspecification, not to type of indicator: comment on Howell, Breivik, and Wilcox (2007).

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Bollen, Kenneth A

2007-06-01

R. D. Howell, E. Breivik, and J. B. Wilcox (2007) have argued that causal (formative) indicators are inherently subject to interpretational confounding. That is, they have argued that using causal (formative) indicators leads the empirical meaning of a latent variable to be other than that assigned to it by a researcher. Their critique of causal (formative) indicators rests on several claims: (a) A latent variable exists apart from the model when there are effect (reflective) indicators but not when there are causal (formative) indicators, (b) causal (formative) indicators need not have the same consequences, (c) causal (formative) indicators are inherently subject to interpretational confounding, and (d) a researcher cannot detect interpretational confounding when using causal (formative) indicators. This article shows that each claim is false. Rather, interpretational confounding is more a problem of structural misspecification of a model combined with an underidentified model that leaves these misspecifications undetected. Interpretational confounding does not occur if the model is correctly specified whether a researcher has causal (formative) or effect (reflective) indicators. It is the validity of a model not the type of indicator that determines the potential for interpretational confounding. Copyright 2007 APA, all rights reserved.

Sensitivity analysis for direct and indirect effects in the presence of exposure-induced mediator-outcome confounders

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Chiba, Yasutaka

2014-01-01

Questions of mediation are often of interest in reasoning about mechanisms, and methods have been developed to address these questions. However, these methods make strong assumptions about the absence of confounding. Even if exposure is randomized, there may be mediator-outcome confounding variables. Inference about direct and indirect effects is particularly challenging if these mediator-outcome confounders are affected by the exposure because in this case these effects are not identified irrespective of whether data is available on these exposure-induced mediator-outcome confounders. In this paper, we provide a sensitivity analysis technique for natural direct and indirect effects that is applicable even if there are mediator-outcome confounders affected by the exposure. We give techniques for both the difference and risk ratio scales and compare the technique to other possible approaches. PMID:25580387

Sensitivity analysis for the effects of multiple unmeasured confounders.

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Groenwold, Rolf H H; Sterne, Jonathan A C; Lawlor, Debbie A; Moons, Karel G M; Hoes, Arno W; Tilling, Kate

2016-09-01

Observational studies are prone to (unmeasured) confounding. Sensitivity analysis of unmeasured confounding typically focuses on a single unmeasured confounder. The purpose of this study was to assess the impact of multiple (possibly weak) unmeasured confounders. Simulation studies were performed based on parameters estimated from the British Women's Heart and Health Study, including 28 measured confounders and assuming no effect of ascorbic acid intake on mortality. In addition, 25, 50, or 100 unmeasured confounders were simulated, with various mutual correlations and correlations with measured confounders. The correlated unmeasured confounders did not need to be strongly associated with exposure and outcome to substantially bias the exposure-outcome association at interest, provided that there are sufficiently many unmeasured confounders. Correlations between unmeasured confounders, in addition to the strength of their relationship with exposure and outcome, are key drivers of the magnitude of unmeasured confounding and should be considered in sensitivity analyses. However, if the unmeasured confounders are correlated with measured confounders, the bias yielded by unmeasured confounders is partly removed through adjustment for the measured confounders. Discussions of the potential impact of unmeasured confounding in observational studies, and sensitivity analyses to examine this, should focus on the potential for the joint effect of multiple unmeasured confounders to bias results. Copyright © 2016 Elsevier Inc. All rights reserved.

The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model.

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Fritz, Matthew S; Kenny, David A; MacKinnon, David P

2016-01-01

Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator-to-outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. To explore the combined effect of measurement error and omitted confounders in the same model, the effect of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect.

The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model

Science.gov (United States)

Fritz, Matthew S.; Kenny, David A.; MacKinnon, David P.

2016-01-01

Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator to outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. In order to explore the combined effect of measurement error and omitted confounders in the same model, the impact of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect. PMID:27739903

Assessment of Confounding in Studies of Delay and Survival

DEFF Research Database (Denmark)

Tørring, Marie Louise; Vedsted, Peter; Frydenberg, Morten

BACKGROUND: Whether longer time to diagnosis (diagnostic delay) in patients with cancer symptoms is directly and independently associated with poor prognosis cannot be determined in randomised controlled trials. Analysis of observational data is therefore necessary. Many previous studies of the i......BACKGROUND: Whether longer time to diagnosis (diagnostic delay) in patients with cancer symptoms is directly and independently associated with poor prognosis cannot be determined in randomised controlled trials. Analysis of observational data is therefore necessary. Many previous studies......) Clarify which factors are considered confounders or intermediate variables in the literature. 2) Assess how and to what extent these factors bias survival estimates. CONSIDERATIONS: As illustrated in Figure 1, symptoms of cancer may alert patients, GP's, and hospital doctors differently and influence both...... delay and survival time in different ways. We therefore assume that the impact of confounding factors depends on the type of delay studied (e.g., patient delay, GP delay, referral delay, or treatment delay). MATERIALS & METHODS: The project includes systematic review and methodological developments...

Consequences of exposure measurement error for confounder identification in environmental epidemiology

DEFF Research Database (Denmark)

Budtz-Jørgensen, Esben; Keiding, Niels; Grandjean, Philippe

2003-01-01

Non-differential measurement error in the exposure variable is known to attenuate the dose-response relationship. The amount of attenuation introduced in a given situation is not only a function of the precision of the exposure measurement but also depends on the conditional variance of the true...... exposure given the other independent variables. In addition, confounder effects may also be affected by the exposure measurement error. These difficulties in statistical model development are illustrated by examples from a epidemiological study performed in the Faroe Islands to investigate the adverse...

Confounding and exposure measurement error in air pollution epidemiology.

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Sheppard, Lianne; Burnett, Richard T; Szpiro, Adam A; Kim, Sun-Young; Jerrett, Michael; Pope, C Arden; Brunekreef, Bert

2012-06-01

Studies in air pollution epidemiology may suffer from some specific forms of confounding and exposure measurement error. This contribution discusses these, mostly in the framework of cohort studies. Evaluation of potential confounding is critical in studies of the health effects of air pollution. The association between long-term exposure to ambient air pollution and mortality has been investigated using cohort studies in which subjects are followed over time with respect to their vital status. In such studies, control for individual-level confounders such as smoking is important, as is control for area-level confounders such as neighborhood socio-economic status. In addition, there may be spatial dependencies in the survival data that need to be addressed. These issues are illustrated using the American Cancer Society Cancer Prevention II cohort. Exposure measurement error is a challenge in epidemiology because inference about health effects can be incorrect when the measured or predicted exposure used in the analysis is different from the underlying true exposure. Air pollution epidemiology rarely if ever uses personal measurements of exposure for reasons of cost and feasibility. Exposure measurement error in air pollution epidemiology comes in various dominant forms, which are different for time-series and cohort studies. The challenges are reviewed and a number of suggested solutions are discussed for both study domains.

Effect decomposition in the presence of an exposure-induced mediator-outcome confounder

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VanderWeele, Tyler J.; Vansteelandt, Stijn; Robins, James M.

2014-01-01

Methods from causal mediation analysis have generalized the traditional approach to direct and indirect effects in the epidemiologic and social science literature by allowing for interaction and non-linearities. However, the methods from the causal inference literature have themselves been subject to a major limitation in that the so-called natural direct and indirect effects that are employed are not identified from data whenever there is a variable that is affected by the exposure, which also confounds the relationship between the mediator and the outcome. In this paper we describe three alternative approaches to effect decomposition that give quantities that can be interpreted as direct and indirect effects, and that can be identified from data even in the presence of an exposure-induced mediator-outcome confounder. We describe a simple weighting-based estimation method for each of these three approaches, illustrated with data from perinatal epidemiology. The methods described here can shed insight into pathways and questions of mediation even when an exposure-induced mediator-outcome confounder is present. PMID:24487213

Correction of confounding bias in non-randomized studies by appropriate weighting.

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Schmoor, Claudia; Gall, Christine; Stampf, Susanne; Graf, Erika

2011-03-01

In non-randomized studies, the assessment of a causal effect of treatment or exposure on outcome is hampered by possible confounding. Applying multiple regression models including the effects of treatment and covariates on outcome is the well-known classical approach to adjust for confounding. In recent years other approaches have been promoted. One of them is based on the propensity score and considers the effect of possible confounders on treatment as a relevant criterion for adjustment. Another proposal is based on using an instrumental variable. Here inference relies on a factor, the instrument, which affects treatment but is thought to be otherwise unrelated to outcome, so that it mimics randomization. Each of these approaches can basically be interpreted as a simple reweighting scheme, designed to address confounding. The procedures will be compared with respect to their fundamental properties, namely, which bias they aim to eliminate, which effect they aim to estimate, and which parameter is modelled. We will expand our overview of methods for analysis of non-randomized studies to methods for analysis of randomized controlled trials and show that analyses of both study types may target different effects and different parameters. The considerations will be illustrated using a breast cancer study with a so-called Comprehensive Cohort Study design, including a randomized controlled trial and a non-randomized study in the same patient population as sub-cohorts. This design offers ideal opportunities to discuss and illustrate the properties of the different approaches. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multisample adjusted U-statistics that account for confounding covariates.

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Satten, Glen A; Kong, Maiying; Datta, Somnath

2018-06-19

Multisample U-statistics encompass a wide class of test statistics that allow the comparison of 2 or more distributions. U-statistics are especially powerful because they can be applied to both numeric and nonnumeric data, eg, ordinal and categorical data where a pairwise similarity or distance-like measure between categories is available. However, when comparing the distribution of a variable across 2 or more groups, observed differences may be due to confounding covariates. For example, in a case-control study, the distribution of exposure in cases may differ from that in controls entirely because of variables that are related to both exposure and case status and are distributed differently among case and control participants. We propose to use individually reweighted data (ie, using the stratification score for retrospective data or the propensity score for prospective data) to construct adjusted U-statistics that can test the equality of distributions across 2 (or more) groups in the presence of confounding covariates. Asymptotic normality of our adjusted U-statistics is established and a closed form expression of their asymptotic variance is presented. The utility of our approach is demonstrated through simulation studies, as well as in an analysis of data from a case-control study conducted among African-Americans, comparing whether the similarity in haplotypes (ie, sets of adjacent genetic loci inherited from the same parent) occurring in a case and a control participant differs from the similarity in haplotypes occurring in 2 control participants. Copyright © 2018 John Wiley & Sons, Ltd.

Some confounding factors in the study of mortality and occupational exposures

International Nuclear Information System (INIS)

Gilbert, E.S.

1982-01-01

With the recent interest in the study of occupational exposures, the impact of certain selective biases in the groups studied is a matter of some concern. In this paper, data from the Hanford nuclear facility population (southeastern Washington State, 1947-1976), which includes many radiation workers, are used to illustrate a method for examining the effect on mortality of such potentially confounding variables as calendar year, length of time since entering the industry, employment status, length of employment, job category, and initial employment year. The analysis, which is based on the Mantel-Haenszel procedure as adapted for a prospective study, differs from most previous studies of occupational variables which have relied primarily on comparing standardized mortality ratios (utilizing an external control) for various subgroups of the population. Results of this analysis confirm other studies in that reduced death rates are observed for early years of follow-up and for those with higher socioeconomic status (as indicated by job category). In addition, workers employed less than two years and especially terminated workers are found to have elevated death rates as compared with the remainder of the study population. It is important that such correlations be taken into account in planning and interpreting analyses of the effects of occupational exposure

Confounding Underlies the Apparent Month of Birth Effect in Multiple Sclerosis

OpenAIRE

Fiddes, Barnaby; Wason, James; Kemppinen, Anu; Ban, Maria; Compston, Alastair; Sawcer, Stephen

2013-01-01

Objective Several groups have reported apparent association between month of birth and multiple sclerosis. We sought to test the extent to which such studies might be confounded by extraneous variables such as year and place of birth. Methods Using national birth statistics from 2 continents, we assessed the evidence for seasonal variations in birth rate and tested the extent to which these are subject to regional and temporal variation. We then established the age and regional origin distrib...

On Estimation of the Survivor Average Causal Effect in Observational Studies when Important Confounders are Missing Due to Death

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Egleston, Brian L.; Scharfstein, Daniel O.; MacKenzie, Ellen

2008-01-01

We focus on estimation of the causal effect of treatment on the functional status of individuals at a fixed point in time t* after they have experienced a catastrophic event, from observational data with the following features: (1) treatment is imposed shortly after the event and is non-randomized, (2) individuals who survive to t* are scheduled to be interviewed, (3) there is interview non-response, (4) individuals who die prior to t* are missing information on pre-event confounders, (5) medical records are abstracted on all individuals to obtain information on post-event, pre-treatment confounding factors. To address the issue of survivor bias, we seek to estimate the survivor average causal effect (SACE), the effect of treatment on functional status among the cohort of individuals who would survive to t* regardless of whether or not assigned to treatment. To estimate this effect from observational data, we need to impose untestable assumptions, which depend on the collection of all confounding factors. Since pre-event information is missing on those who die prior to t*, it is unlikely that these data are missing at random (MAR). We introduce a sensitivity analysis methodology to evaluate the robustness of SACE inferences to deviations from the MAR assumption. We apply our methodology to the evaluation of the effect of trauma center care on vitality outcomes using data from the National Study on Costs and Outcomes of Trauma Care. PMID:18759833

Indoor biofuel air pollution and respiratory health: the role of confounding factors among women in highland Guatemala.

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Bruce, N; Neufeld, L; Boy, E; West, C

1998-06-01

A number of studies have reported associations between indoor biofuel air pollution in developing countries and chronic obstructive lung disease (COLD) in adults and acute lower respiratory infection (ALRI) in children. Most of these studies have used indirect measures of exposure and generally dealt inadequately with confounding. More reliable, quantified information about this presumed effect is an important pre-requisite for prevention, not least because of the technical, economic and cultural barriers to achieving substantial exposure reductions in the world's poorest households, where ambient pollution levels are typically between ten and a hundred times higher than recommended standards. This study was carried out as part of a programme of research designed to inform the development of intervention studies capable of providing quantified estimates of health benefits. The association between respiratory symptoms and the use of open fires and chimney woodstoves ('planchas'), and the distribution of confounding factors, were examined in a cross-sectional study of 340 women aged 15-45 years, living in a poor rural area in the western highlands of Guatemala. The prevalence of reported cough and phlegm was significantly higher for three of six symptom measures among women using open fires. Although this finding is consistent with a number of other studies, none has systematically examined the extent to which strong associations with confounding variables in these settings limit the ability of observational studies to define the effect of indoor air pollution adequately. Very strong associations (P air pollution and health, although there is a reasonable case for believing that the observed association is causal. Intervention studies are required for stronger evidence of this association, and more importantly, to determine the size of health benefit achievable through feasible exposure reductions.

Role of environmental confounding in the association between FKBP5 and first-episode psychosis

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Olesya eAjnakina

2014-07-01

Full Text Available Background: Failure to account for the etiological diversity that typically occurs in psychiatric cohorts may increase the potential for confounding, as a proportion of genetic variance will be specific to exposures that have variable distribution in cases. This study investigated whether minimizing the potential for such confounding strengthened the evidence for a genetic candidate currently unsupported at the genome-wide level.Methods: 291 first-episode psychosis cases from South London UK, and 218 unaffected controls were evaluated for a functional polymorphism at the rs1360780 locus in FKBP5. The relationship between FKBP5 and psychosis was modelled using logistic regression. Cannabis use (Cannabis Experiences Questionnaire and parental separation (Childhood Experience of Care and Abuse Questionnaire were modelled as confounders in the analysis.Results: Association at rs1360780 was not detected until the effects of the two environmental factors had been adjusted for in the model (OR=2.81, 95% CI 1.23-6.43, p=0.02. A statistical interaction between rs1360780 and parental separation was confirmed by stratified tests (OR=2.8, p=0.02 vs. OR=0.89, p=0.80. The genetic main effect was directionally-consistent with findings in other (stress-related clinical phenotypes. Moreover, the variation in effect magnitude was explained by the level of power associated with different cannabis constructs used in the model (r=0.95.Conclusions: Our results suggest that the extent to which genetic variants in FKBP5 can influence susceptibility to psychosis may depend on the other etiological factors involved. This finding requires further validation in other large independent cohorts. Potentially this work could have translational implications, as the ability to discriminate between genetic etiologies, based on a case-by-case understanding of exposure history would confer an important clinical advantage that would benefit the delivery of personalizable treatment

Purposeful selection of variables in logistic regression

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Williams David Keith

2008-12-01

Full Text Available Abstract Background The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process. Methods In this paper we introduce an algorithm which automates that process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE. Results We show that the advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction. In addition to significant covariates, this variable selection procedure has the capability of retaining important confounding variables, resulting potentially in a slightly richer model. Application of the macro is further illustrated with the Hosmer and Lemeshow Worchester Heart Attack Study (WHAS data. Conclusion If an analyst is in need of an algorithm that will help guide the retention of significant covariates as well as confounding ones they should consider this macro as an alternative tool.

Quantifying the potential role of unmeasured confounders : the example of influenza vaccination

NARCIS (Netherlands)

Groenwold, R H H; Hoes, A W; Nichol, K L; Hak, E

2008-01-01

BACKGROUND: The validity of non-randomized studies using healthcare databases is often challenged because they lack information on potentially important confounders, such as functional health status and socioeconomic status. In a study quantifying the effects of influenza vaccination among

Importance analysis for models with correlated variables and its sparse grid solution

International Nuclear Information System (INIS)

Li, Luyi; Lu, Zhenzhou

2013-01-01

For structural models involving correlated input variables, a novel interpretation for variance-based importance measures is proposed based on the contribution of the correlated input variables to the variance of the model output. After the novel interpretation of the variance-based importance measures is compared with the existing ones, two solutions of the variance-based importance measures of the correlated input variables are built on the sparse grid numerical integration (SGI): double-loop nested sparse grid integration (DSGI) method and single loop sparse grid integration (SSGI) method. The DSGI method solves the importance measure by decreasing the dimensionality of the input variables procedurally, while SSGI method performs importance analysis through extending the dimensionality of the inputs. Both of them can make full use of the advantages of the SGI, and are well tailored for different situations. By analyzing the results of several numerical and engineering examples, it is found that the novel proposed interpretation about the importance measures of the correlated input variables is reasonable, and the proposed methods for solving importance measures are efficient and accurate. -- Highlights: •The contribution of correlated variables to the variance of the output is analyzed. •A novel interpretation for variance-based indices of correlated variables is proposed. •Two solutions for variance-based importance measures of correlated variables are built

An introduction to sensitivity analysis for unobserved confounding in nonexperimental prevention research.

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Liu, Weiwei; Kuramoto, S Janet; Stuart, Elizabeth A

2013-12-01

Despite the fact that randomization is the gold standard for estimating causal relationships, many questions in prevention science are often left to be answered through nonexperimental studies because randomization is either infeasible or unethical. While methods such as propensity score matching can adjust for observed confounding, unobserved confounding is the Achilles heel of most nonexperimental studies. This paper describes and illustrates seven sensitivity analysis techniques that assess the sensitivity of study results to an unobserved confounder. These methods were categorized into two groups to reflect differences in their conceptualization of sensitivity analysis, as well as their targets of interest. As a motivating example, we examine the sensitivity of the association between maternal suicide and offspring's risk for suicide attempt hospitalization. While inferences differed slightly depending on the type of sensitivity analysis conducted, overall, the association between maternal suicide and offspring's hospitalization for suicide attempt was found to be relatively robust to an unobserved confounder. The ease of implementation and the insight these analyses provide underscores sensitivity analysis techniques as an important tool for nonexperimental studies. The implementation of sensitivity analysis can help increase confidence in results from nonexperimental studies and better inform prevention researchers and policy makers regarding potential intervention targets.

Controlling confounding by frailty when estimating influenza vaccine effectiveness using predictors of dependency in activities of daily living.

Science.gov (United States)

Zhang, Henry T; McGrath, Leah J; Wyss, Richard; Ellis, Alan R; Stürmer, Til

2017-12-01

To improve control of confounding by frailty when estimating the effect of influenza vaccination on all-cause mortality by controlling for a published set of claims-based predictors of dependency in activities of daily living (ADL). Using Medicare claims data, a cohort of beneficiaries >65 years of age was followed from September 1, 2007, to April 12, 2008, with covariates assessed in the 6 months before follow-up. We estimated Cox proportional hazards models of all-cause mortality, with influenza vaccination as a time-varying exposure. We controlled for common demographics, comorbidities, and health care utilization variables and then added 20 ADL dependency predictors. To gauge residual confounding, we estimated pre-influenza season hazard ratios (HRs) between September 1, 2007 and January 5, 2008, which should be 1.0 in the absence of bias. A cohort of 2 235 140 beneficiaries was created, with a median follow-up of 224 days. Overall, 52% were vaccinated and 4% died during follow-up. During the pre-influenza season period, controlling for demographics, comorbidities, and health care use resulted in a HR of 0.66 (0.64, 0.67). Adding the ADL dependency predictors moved the HR to 0.68 (0.67, 0.70). Controlling for demographics and ADL dependency predictors alone resulted in a HR of 0.68 (0.66, 0.70). Results were consistent with those in the literature, with significant uncontrolled confounding after adjustment for demographics, comorbidities, and health care use. Adding ADL dependency predictors moved HRs slightly closer to the null. Of the comorbidities, health care use variables, and ADL dependency predictors, the last set reduced confounding most. However, substantial uncontrolled confounding remained. Copyright © 2017 John Wiley & Sons, Ltd.

Using ecological propensity score to adjust for missing confounders in small area studies.

Science.gov (United States)

Wang, Yingbo; Pirani, Monica; Hansell, Anna L; Richardson, Sylvia; Blangiardo, Marta

2017-11-09

Small area ecological studies are commonly used in epidemiology to assess the impact of area level risk factors on health outcomes when data are only available in an aggregated form. However, the resulting estimates are often biased due to unmeasured confounders, which typically are not available from the standard administrative registries used for these studies. Extra information on confounders can be provided through external data sets such as surveys or cohorts, where the data are available at the individual level rather than at the area level; however, such data typically lack the geographical coverage of administrative registries. We develop a framework of analysis which combines ecological and individual level data from different sources to provide an adjusted estimate of area level risk factors which is less biased. Our method (i) summarizes all available individual level confounders into an area level scalar variable, which we call ecological propensity score (EPS), (ii) implements a hierarchical structured approach to impute the values of EPS whenever they are missing, and (iii) includes the estimated and imputed EPS into the ecological regression linking the risk factors to the health outcome. Through a simulation study, we show that integrating individual level data into small area analyses via EPS is a promising method to reduce the bias intrinsic in ecological studies due to unmeasured confounders; we also apply the method to a real case study to evaluate the effect of air pollution on coronary heart disease hospital admissions in Greater London. © The Author 2017. Published by Oxford University Press.

Bias in random forest variable importance measures: Illustrations, sources and a solution

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Hothorn Torsten

2007-01-01

Full Text Available Abstract Background Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and related scientific fields, for instance to select a subset of genetic markers relevant for the prediction of a certain disease. We show that random forest variable importance measures are a sensible means for variable selection in many applications, but are not reliable in situations where potential predictor variables vary in their scale of measurement or their number of categories. This is particularly important in genomics and computational biology, where predictors often include variables of different types, for example when predictors include both sequence data and continuous variables such as folding energy, or when amino acid sequence data show different numbers of categories. Results Simulation studies are presented illustrating that, when random forest variable importance measures are used with data of varying types, the results are misleading because suboptimal predictor variables may be artificially preferred in variable selection. The two mechanisms underlying this deficiency are biased variable selection in the individual classification trees used to build the random forest on one hand, and effects induced by bootstrap sampling with replacement on the other hand. Conclusion We propose to employ an alternative implementation of random forests, that provides unbiased variable selection in the individual classification trees. When this method is applied using subsampling without replacement, the resulting variable importance measures can be used reliably for variable selection even in situations where the potential predictor variables vary in their scale of measurement or their number of categories. The usage of both random forest algorithms and their variable importance measures in the R system for statistical computing is illustrated and

Variable importance and prediction methods for longitudinal problems with missing variables.

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Iván Díaz

Full Text Available We present prediction and variable importance (VIM methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patients, a field in which current medical practice involves rules of thumb and scoring methods that only use a few variables and ignore the dynamic and high-dimensional nature of trauma recovery. Well-principled prediction and VIM methods can provide a tool to make care decisions informed by the high-dimensional patient's physiological and clinical history. Our VIM parameters are analogous to slope coefficients in adjusted regressions, but are not dependent on a specific statistical model, nor require a certain functional form of the prediction regression to be estimated. In addition, they can be causally interpreted under causal and statistical assumptions as the expected outcome under time-specific clinical interventions, related to changes in the mean of the outcome if each individual experiences a specified change in the variable (keeping other variables in the model fixed. Better yet, the targeted MLE used is doubly robust and locally efficient. Because the proposed VIM does not constrain the prediction model fit, we use a very flexible ensemble learner (the SuperLearner, which returns a linear combination of a list of user-given algorithms. Not only is such a prediction algorithm intuitive appealing, it has theoretical justification as being asymptotically equivalent to the oracle selector. The results of the analysis show effects whose size and significance would have been not been found using a parametric approach (such as stepwise regression or LASSO. In addition, the procedure is even more compelling as the predictor on which it is based showed significant improvements in cross-validated fit, for instance area under the curve (AUC for a receiver-operator curve (ROC. Thus, given that 1 our VIM

An Introduction to Sensitivity Analysis for Unobserved Confounding in Non-Experimental Prevention Research

Science.gov (United States)

Kuramoto, S. Janet; Stuart, Elizabeth A.

2013-01-01

Despite that randomization is the gold standard for estimating causal relationships, many questions in prevention science are left to be answered through non-experimental studies often because randomization is either infeasible or unethical. While methods such as propensity score matching can adjust for observed confounding, unobserved confounding is the Achilles heel of most non-experimental studies. This paper describes and illustrates seven sensitivity analysis techniques that assess the sensitivity of study results to an unobserved confounder. These methods were categorized into two groups to reflect differences in their conceptualization of sensitivity analysis, as well as their targets of interest. As a motivating example we examine the sensitivity of the association between maternal suicide and offspring’s risk for suicide attempt hospitalization. While inferences differed slightly depending on the type of sensitivity analysis conducted, overall the association between maternal suicide and offspring’s hospitalization for suicide attempt was found to be relatively robust to an unobserved confounder. The ease of implementation and the insight these analyses provide underscores sensitivity analysis techniques as an important tool for non-experimental studies. The implementation of sensitivity analysis can help increase confidence in results from non-experimental studies and better inform prevention researchers and policymakers regarding potential intervention targets. PMID:23408282

Variable importance in latent variable regression models

NARCIS (Netherlands)

Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.

2014-01-01

The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable

Methods to quantify variable importance: implications for theanalysis of noisy ecological data

OpenAIRE

Murray, Kim; Conner, Mary M.

2009-01-01

Determining the importance of independent variables is of practical relevance to ecologists and managers concerned with allocating limited resources to the management of natural systems. Although techniques that identify explanatory variables having the largest influence on the response variable are needed to design management actions effectively, the use of various indices to evaluate variable importance is poorly understood. Using Monte Carlo simulations, we compared six different indices c...

Which Propensity Score Method Best Reduces Confounder Imbalance? An Example From a Retrospective Evaluation of a Childhood Obesity Intervention.

Science.gov (United States)

Schroeder, Krista; Jia, Haomiao; Smaldone, Arlene

Propensity score (PS) methods are increasingly being employed by researchers to reduce bias arising from confounder imbalance when using observational data to examine intervention effects. The purpose of this study was to examine PS theory and methodology and compare application of three PS methods (matching, stratification, weighting) to determine which best improves confounder balance. Baseline characteristics of a sample of 20,518 school-aged children with severe obesity (of whom 1,054 received an obesity intervention) were assessed prior to PS application. Three PS methods were then applied to the data to determine which showed the greatest improvement in confounder balance between the intervention and control group. The effect of each PS method on the outcome variable-body mass index percentile change at one year-was also examined. SAS 9.4 and Comprehensive Meta-analysis statistical software were used for analyses. Prior to PS adjustment, the intervention and control groups differed significantly on seven of 11 potential confounders. PS matching removed all differences. PS stratification and weighting both removed one difference but created two new differences. Sensitivity analyses did not change these results. Body mass index percentile at 1 year decreased in both groups. The size of the decrease was smaller in the intervention group, and the estimate of the decrease varied by PS method. Selection of a PS method should be guided by insight from statistical theory and simulation experiments, in addition to observed improvement in confounder balance. For this data set, PS matching worked best to correct confounder imbalance. Because each method varied in correcting confounder imbalance, we recommend that multiple PS methods be compared for ability to improve confounder balance before implementation in evaluating treatment effects in observational data.

Resting-state FMRI confounds and cleanup

Science.gov (United States)

Murphy, Kevin; Birn, Rasmus M.; Bandettini, Peter A.

2013-01-01

The goal of resting-state functional magnetic resonance imaging (FMRI) is to investigate the brain’s functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain “at rest” as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of FMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state FMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state FMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state FMRI comparisons and results, noise cleanup is an often over-looked but essential step in the analysis pipeline. PMID:23571418

Confounding and exposure measurement error in air pollution epidemiology

NARCIS (Netherlands)

Sheppard, L.; Burnett, R.T.; Szpiro, A.A.; Kim, J.Y.; Jerrett, M.; Pope, C.; Brunekreef, B.|info:eu-repo/dai/nl/067548180

2012-01-01

Studies in air pollution epidemiology may suffer from some specific forms of confounding and exposure measurement error. This contribution discusses these, mostly in the framework of cohort studies. Evaluation of potential confounding is critical in studies of the health effects of air pollution.

Development of a localized probabilistic sensitivity method to determine random variable regional importance

International Nuclear Information System (INIS)

Millwater, Harry; Singh, Gulshan; Cortina, Miguel

2012-01-01

There are many methods to identify the important variable out of a set of random variables, i.e., “inter-variable” importance; however, to date there are no comparable methods to identify the “region” of importance within a random variable, i.e., “intra-variable” importance. Knowledge of the critical region of an input random variable (tail, near-tail, and central region) can provide valuable information towards characterizing, understanding, and improving a model through additional modeling or testing. As a result, an intra-variable probabilistic sensitivity method was developed and demonstrated for independent random variables that computes the partial derivative of a probabilistic response with respect to a localized perturbation in the CDF values of each random variable. These sensitivities are then normalized in absolute value with respect to the largest sensitivity within a distribution to indicate the region of importance. The methodology is implemented using the Score Function kernel-based method such that existing samples can be used to compute sensitivities for negligible cost. Numerical examples demonstrate the accuracy of the method through comparisons with finite difference and numerical integration quadrature estimates. - Highlights: ► Probabilistic sensitivity methodology. ► Determines the “region” of importance within random variables such as left tail, near tail, center, right tail, etc. ► Uses the Score Function approach to reuse the samples, hence, negligible cost. ► No restrictions on the random variable types or limit states.

The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams.

Science.gov (United States)

Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong

2017-12-28

Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which

The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams

Directory of Open Access Journals (Sweden)

Yuanyuan Yu

2017-12-01

Full Text Available Abstract Background Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Methods Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM were compared. The “do-calculus” was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Results Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal

Pre-Analytical Parameters Affecting Vascular Endothelial Growth Factor Measurement in Plasma: Identifying Confounders.

Science.gov (United States)

Walz, Johanna M; Boehringer, Daniel; Deissler, Heidrun L; Faerber, Lothar; Goepfert, Jens C; Heiduschka, Peter; Kleeberger, Susannah M; Klettner, Alexa; Krohne, Tim U; Schneiderhan-Marra, Nicole; Ziemssen, Focke; Stahl, Andreas

2016-01-01

Vascular endothelial growth factor-A (VEGF-A) is intensively investigated in various medical fields. However, comparing VEGF-A measurements is difficult because sample acquisition and pre-analytic procedures differ between studies. We therefore investigated which variables act as confounders of VEGF-A measurements. Following a standardized protocol, blood was taken at three clinical sites from six healthy participants (one male and one female participant at each center) twice one week apart. The following pre-analytical parameters were varied in order to analyze their impact on VEGF-A measurements: analyzing center, anticoagulant (EDTA vs. PECT / CTAD), cannula (butterfly vs. neonatal), type of centrifuge (swing-out vs. fixed-angle), time before and after centrifugation, filling level (completely filled vs. half-filled tubes) and analyzing method (ELISA vs. multiplex bead array). Additionally, intrapersonal variations over time and sex differences were explored. Statistical analysis was performed using a linear regression model. The following parameters were identified as statistically significant independent confounders of VEGF-A measurements: analyzing center, anticoagulant, centrifuge, analyzing method and sex of the proband. The following parameters were no significant confounders in our data set: intrapersonal variation over one week, cannula, time before and after centrifugation and filling level of collection tubes. VEGF-A measurement results can be affected significantly by the identified pre-analytical parameters. We recommend the use of CTAD anticoagulant, a standardized type of centrifuge and one central laboratory using the same analyzing method for all samples.

Pre-Analytical Parameters Affecting Vascular Endothelial Growth Factor Measurement in Plasma: Identifying Confounders.

Directory of Open Access Journals (Sweden)

Johanna M Walz

Full Text Available Vascular endothelial growth factor-A (VEGF-A is intensively investigated in various medical fields. However, comparing VEGF-A measurements is difficult because sample acquisition and pre-analytic procedures differ between studies. We therefore investigated which variables act as confounders of VEGF-A measurements.Following a standardized protocol, blood was taken at three clinical sites from six healthy participants (one male and one female participant at each center twice one week apart. The following pre-analytical parameters were varied in order to analyze their impact on VEGF-A measurements: analyzing center, anticoagulant (EDTA vs. PECT / CTAD, cannula (butterfly vs. neonatal, type of centrifuge (swing-out vs. fixed-angle, time before and after centrifugation, filling level (completely filled vs. half-filled tubes and analyzing method (ELISA vs. multiplex bead array. Additionally, intrapersonal variations over time and sex differences were explored. Statistical analysis was performed using a linear regression model.The following parameters were identified as statistically significant independent confounders of VEGF-A measurements: analyzing center, anticoagulant, centrifuge, analyzing method and sex of the proband. The following parameters were no significant confounders in our data set: intrapersonal variation over one week, cannula, time before and after centrifugation and filling level of collection tubes.VEGF-A measurement results can be affected significantly by the identified pre-analytical parameters. We recommend the use of CTAD anticoagulant, a standardized type of centrifuge and one central laboratory using the same analyzing method for all samples.

'Mechanical restraint-confounders, risk, alliance score'

DEFF Research Database (Denmark)

Deichmann Nielsen, Lea; Bech, Per; Hounsgaard, Lise

2017-01-01

. AIM: To clinically validate a new, structured short-term risk assessment instrument called the Mechanical Restraint-Confounders, Risk, Alliance Score (MR-CRAS), with the intended purpose of supporting the clinicians' observation and assessment of the patient's readiness to be released from mechanical...... restraint. METHODS: The content and layout of MR-CRAS and its user manual were evaluated using face validation by forensic mental health clinicians, content validation by an expert panel, and pilot testing within two, closed forensic mental health inpatient units. RESULTS: The three sub-scales (Confounders......, Risk, and a parameter of Alliance) showed excellent content validity. The clinical validations also showed that MR-CRAS was perceived and experienced as a comprehensible, relevant, comprehensive, and useable risk assessment instrument. CONCLUSIONS: MR-CRAS contains 18 clinically valid items...

Interpretational Confounding Is Due to Misspecification, Not to Type of Indicator: Comment on Howell, Breivik, and Wilcox (2007)

Science.gov (United States)

Bollen, Kenneth A.

2007-01-01

R. D. Howell, E. Breivik, and J. B. Wilcox (2007) have argued that causal (formative) indicators are inherently subject to interpretational confounding. That is, they have argued that using causal (formative) indicators leads the empirical meaning of a latent variable to be other than that assigned to it by a researcher. Their critique of causal…

Adolescent sleep disturbance and school performance: the confounding variable of socioeconomics.

Science.gov (United States)

Pagel, James F; Forister, Natalie; Kwiatkowki, Carol

2007-02-15

To assess how selected socioeconomic variables known to affect school performance alter the association between reported sleep disturbance and poor school performance in a contiguous middle school/high school population. A school district/college IRB approved questionnaire was distributed in science and health classes in middle school and high school. This questionnaire included a frequency scaled pediatric sleep disturbance questionnaire for completion by students and a permission and demographic questionnaire for completion by parents (completed questionnaires n = 238 with 69.3% including GPA). Sleep complaints occur at high frequency in this sample (sleep onset insomnia 60% > 1 x /wk.; 21.2% every night; sleepiness during the day (45.7% > 1 x /wk.; 15.2 % every night), and difficulty concentrating (54.6% > 1 x /wk.; 12.9% always). Students with lower grade point averages (GPAs) were more likely to have restless/aching legs when trying to fall asleep, difficulty concentrating during the day, snoring every night, difficulty waking in the morning, sleepiness during the day, and falling asleep in class. Lower reported GPAs were significantly associated with lower household incomes. After statistically controlling for income, restless legs, sleepiness during the day, and difficulty with concentration continued to significantly affect school performance. This study provides additional evidence indicating that sleep disturbances occur at high frequencies in adolescents and significantly affect daytime performance, as measured by GPA. The socioeconomic variable of household income also significantly affects GPA. After statistically controlling for age and household income, the number and type of sleep variables noted to significantly affect GPA are altered but persistent in demonstrating significant effects on school performance.

[COMPUTER TECHNOLOGY FOR ACCOUNTING OF CONFOUNDERS IN THE RISK ASSESSMENT IN COMPARATIVE STUDIES ON THE BASE OF THE METHOD OF STANDARDIZATION].

Science.gov (United States)

Shalaumova, Yu V; Varaksin, A N; Panov, V G

2016-01-01

There was performed an analysis of the accounting of the impact of concomitant variables (confounders), introducing a systematic error in the assessment of the impact of risk factors on the resulting variable. The analysis showed that standardization is an effective method for the reduction of the shift of risk assessment. In the work there is suggested an algorithm implementing the method of standardization based on stratification, providing for the minimization of the difference of distributions of confounders in groups on risk factors. To automate the standardization procedures there was developed a software available on the website of the Institute of Industrial Ecology, UB RAS. With the help of the developed software by numerically modeling there were determined conditions of the applicability of the method of standardization on the basis of stratification for the case of the normal distribution on the response and confounder and linear relationship between them. Comparison ofresults obtained with the help of the standardization with statistical methods (logistic regression and analysis of covariance) in solving the problem of human ecology, has shown that obtaining close results is possible if there will be met exactly conditions for the applicability of statistical methods. Standardization is less sensitive to violations of conditions of applicability.

Methods to control for unmeasured confounding in pharmacoepidemiology : an overview

NARCIS (Netherlands)

Uddin, Md Jamal; Groenwold, Rolf H H; Ali, Mohammed Sanni; de Boer, Anthonius; Roes, Kit C B; Chowdhury, Muhammad A B; Klungel, Olaf H.

2016-01-01

Background Unmeasured confounding is one of the principal problems in pharmacoepidemiologic studies. Several methods have been proposed to detect or control for unmeasured confounding either at the study design phase or the data analysis phase. Aim of the Review To provide an overview of commonly

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

Climatological variability in regional air pollution

International Nuclear Information System (INIS)

Shannon, J.D.; Trexler, E.C. Jr.

1995-01-01

Although some air pollution modeling studies examine events that have already occurred (e.g., the Chernobyl plume) with relevant meteorological conditions largely known, most pollution modeling studies address expected or potential scenarios for the future. Future meteorological conditions, the major pollutant forcing function other than emissions, are inherently uncertain although much relevant information is contained in past observational data. For convenience in our discussions of regional pollutant variability unrelated to emission changes, we define meteorological variability as short-term (within-season) pollutant variability and climatological variability as year-to-year changes in seasonal averages and accumulations of pollutant variables. In observations and in some of our simulations the effects are confounded because for seasons of two different years both the mean and the within-season character of a pollutant variable may change. Effects of climatological and meteorological variability on means and distributions of air pollution parameters, particularly those related to regional visibility, are illustrated. Over periods of up to a decade climatological variability may mask or overstate improvements resulting from emission controls. The importance of including climatological uncertainties in assessing potential policies, particularly when based partly on calculated source-receptor relationships, is highlighted

Sensitivity analysis for unobserved confounding of direct and indirect effects using uncertainty intervals.

Science.gov (United States)

Lindmark, Anita; de Luna, Xavier; Eriksson, Marie

2018-05-10

To estimate direct and indirect effects of an exposure on an outcome from observed data, strong assumptions about unconfoundedness are required. Since these assumptions cannot be tested using the observed data, a mediation analysis should always be accompanied by a sensitivity analysis of the resulting estimates. In this article, we propose a sensitivity analysis method for parametric estimation of direct and indirect effects when the exposure, mediator, and outcome are all binary. The sensitivity parameters consist of the correlations between the error terms of the exposure, mediator, and outcome models. These correlations are incorporated into the estimation of the model parameters and identification sets are then obtained for the direct and indirect effects for a range of plausible correlation values. We take the sampling variability into account through the construction of uncertainty intervals. The proposed method is able to assess sensitivity to both mediator-outcome confounding and confounding involving the exposure. To illustrate the method, we apply it to a mediation study based on the data from the Swedish Stroke Register (Riksstroke). An R package that implements the proposed method is available. Copyright © 2018 John Wiley & Sons, Ltd.

Examining the role of unmeasured confounding in mediation analysis with genetic and genomic applications.

Science.gov (United States)

Lutz, Sharon M; Thwing, Annie; Schmiege, Sarah; Kroehl, Miranda; Baker, Christopher D; Starling, Anne P; Hokanson, John E; Ghosh, Debashis

2017-07-19

In mediation analysis if unmeasured confounding is present, the estimates for the direct and mediated effects may be over or under estimated. Most methods for the sensitivity analysis of unmeasured confounding in mediation have focused on the mediator-outcome relationship. The Umediation R package enables the user to simulate unmeasured confounding of the exposure-mediator, exposure-outcome, and mediator-outcome relationships in order to see how the results of the mediation analysis would change in the presence of unmeasured confounding. We apply the Umediation package to the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study to examine the role of unmeasured confounding due to population stratification on the effect of a single nucleotide polymorphism (SNP) in the CHRNA5/3/B4 locus on pulmonary function decline as mediated by cigarette smoking. Umediation is a flexible R package that examines the role of unmeasured confounding in mediation analysis allowing for normally distributed or Bernoulli distributed exposures, outcomes, mediators, measured confounders, and unmeasured confounders. Umediation also accommodates multiple measured confounders, multiple unmeasured confounders, and allows for a mediator-exposure interaction on the outcome. Umediation is available as an R package at https://github.com/SharonLutz/Umediation A tutorial on how to install and use the Umediation package is available in the Additional file 1.

Quantitative assessment of unobserved confounding is mandatory in nonrandomized intervention studies

NARCIS (Netherlands)

Groenwold, R H H; Hak, E; Hoes, A W

OBJECTIVE: In nonrandomized intervention studies unequal distribution of patient characteristics in the groups under study may hinder comparability of prognosis and therefore lead to confounding bias. Our objective was to review methods to control for observed confounding, as well as unobserved

Overview of potential procedural and participant-related confounds for neuroimaging of the resting state

Science.gov (United States)

Duncan, Niall W.; Northoff, Georg

2013-01-01

Studies of intrinsic brain activity in the resting state have become increasingly common. A productive discussion of what analysis methods are appropriate, of the importance of physiologic correction and of the potential interpretations of results has been ongoing. However, less attention has been paid to factors other than physiologic noise that may confound resting-state experiments. These range from straightforward factors, such as ensuring that participants are all instructed in the same manner, to more obscure participant-related factors, such as body weight. We provide an overview of such potentially confounding factors, along with some suggested approaches for minimizing their impact. A particular theme that emerges from the overview is the range of systematic differences between types of study groups (e.g., between patients and controls) that may influence resting-state study results. PMID:22964258

Interpreting Multiple Linear Regression: A Guidebook of Variable Importance

Science.gov (United States)

Nathans, Laura L.; Oswald, Frederick L.; Nimon, Kim

2012-01-01

Multiple regression (MR) analyses are commonly employed in social science fields. It is also common for interpretation of results to typically reflect overreliance on beta weights, often resulting in very limited interpretations of variable importance. It appears that few researchers employ other methods to obtain a fuller understanding of what…

CONFOUNDING STRUCTURE OF TWO-LEVEL NONREGULAR FACTORIAL DESIGNS

Institute of Scientific and Technical Information of China (English)

Ren Junbai

2012-01-01

In design theory,the alias structure of regular fractional factorial designs is elegantly described with group theory.However,this approach cannot be applied to nonregular designs directly. For an arbitrary nonregular design,a natural question is how to describe the confounding relations between its effects,is there any inner structure similar to regular designs? The aim of this article is to answer this basic question.Using coefficients of indicator function,confounding structure of nonregular fractional factorial designs is obtained as linear constrains on the values of effects.A method to estimate the sparse significant effects in an arbitrary nonregular design is given through an example.

The performance of random coefficient regression in accounting for residual confounding.

Science.gov (United States)

Gustafson, Paul; Greenland, Sander

2006-09-01

Greenland (2000, Biometrics 56, 915-921) describes the use of random coefficient regression to adjust for residual confounding in a particular setting. We examine this setting further, giving theoretical and empirical results concerning the frequentist and Bayesian performance of random coefficient regression. Particularly, we compare estimators based on this adjustment for residual confounding to estimators based on the assumption of no residual confounding. This devolves to comparing an estimator from a nonidentified but more realistic model to an estimator from a less realistic but identified model. The approach described by Gustafson (2005, Statistical Science 20, 111-140) is used to quantify the performance of a Bayesian estimator arising from a nonidentified model. From both theoretical calculations and simulations we find support for the idea that superior performance can be obtained by replacing unrealistic identifying constraints with priors that allow modest departures from those constraints. In terms of point-estimator bias this superiority arises when the extent of residual confounding is substantial, but the advantage is much broader in terms of interval estimation. The benefit from modeling residual confounding is maintained when the prior distributions employed only roughly correspond to reality, for the standard identifying constraints are equivalent to priors that typically correspond much worse.

Sensitivity analysis and power for instrumental variable studies.

Science.gov (United States)

Wang, Xuran; Jiang, Yang; Zhang, Nancy R; Small, Dylan S

2018-03-31

In observational studies to estimate treatment effects, unmeasured confounding is often a concern. The instrumental variable (IV) method can control for unmeasured confounding when there is a valid IV. To be a valid IV, a variable needs to be independent of unmeasured confounders and only affect the outcome through affecting the treatment. When applying the IV method, there is often concern that a putative IV is invalid to some degree. We present an approach to sensitivity analysis for the IV method which examines the sensitivity of inferences to violations of IV validity. Specifically, we consider sensitivity when the magnitude of association between the putative IV and the unmeasured confounders and the direct effect of the IV on the outcome are limited in magnitude by a sensitivity parameter. Our approach is based on extending the Anderson-Rubin test and is valid regardless of the strength of the instrument. A power formula for this sensitivity analysis is presented. We illustrate its usage via examples about Mendelian randomization studies and its implications via a comparison of using rare versus common genetic variants as instruments. © 2018, The International Biometric Society.

Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

Science.gov (United States)

Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

2016-03-10

Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

Spectral Data Captures Important Variability Between and Among Species and Functional Types

Science.gov (United States)

Townsend, P. A.; Serbin, S. P.; Kingdon, C.; Singh, A.; Couture, J. J.; Gamon, J. A.

2013-12-01

Narrowband spectral data in the visible, near and shortwave infrared (400-2500 nm) are being used increasingly in plant ecology to characterize the biochemical, physiological and water status of vegetation, as well as community composition. In particular, spectroscopic data have recently received considerable attention for their capacity to discriminate plants according to functional properties or 'optical types.' Such measurements can be acquired from airborne/satellite remote sensing imagery or field spectrometers and are commonly used to directly estimate or infer properties important to photosynthesis, carbon and water fluxes, nutrient dynamics, phenology, and disturbance. Spectral data therefore represent proxies for measurements that are otherwise time consuming or expensive to make, and - more importantly - provide the opportunity to characterize the spatial and temporal variability of taxonomic or functional groups. We have found that spectral variation within species and functional types can in fact exceed the variation between types. As such, we recommend that the traditional quantification of characteristics defining species and/or functional types must be modified to include the range of variability in those properties. We provide four examples of the importance of spectral data for describing within-species/functional type variation. First, within temperate forests, the spectral properties of foliage vary considerably with canopy position. This variability is strongly related to differences in specific leaf area between shade- and sun-lit leaves, and the resulting differences among leaves in strategies for light harvesting, photosynthesis, and leaf longevity. These results point to the need to better characterize leaf optical properties throughout a canopy, rather than basing the characterization of ecosystem functioning on only the sunlit portion of the canopy crown. Second, we show considerable differences in optical properties of foliage from

Propensity score methodology for confounding control in health care utilization databases

Directory of Open Access Journals (Sweden)

Elisabetta Patorno

2013-06-01

Full Text Available Propensity score (PS methodology is a common approach to control for confounding in nonexperimental studies of treatment effects using health care utilization databases. This methodology offers researchers many advantages compared with conventional multivariate models: it directly focuses on the determinants of treatment choice, facilitating the understanding of the clinical decision-making process by the researcher; it allows for graphical comparisons of the distribution of propensity scores and truncation of subjects without overlapping PS indicating a lack of equipoise; it allows transparent assessment of the confounder balance achieved by the PS at baseline; and it offers a straightforward approach to reduce the dimensionality of sometimes large arrays of potential confounders in utilization databases, directly addressing the “curse of dimensionality” in the context of rare events. This article provides an overview of the use of propensity score methodology for pharmacoepidemiologic research with large health care utilization databases, covering recent discussions on covariate selection, the role of automated techniques for addressing unmeasurable confounding via proxies, strategies to maximize clinical equipoise at baseline, and the potential of machine-learning algorithms for optimized propensity score estimation. The appendix discusses the available software packages for PS methodology. Propensity scores are a frequently used and versatile tool for transparent and comprehensive adjustment of confounding in pharmacoepidemiology with large health care databases.

Are Attractive Men's Faces Masculine or Feminine? The Importance of Controlling Confounds in Face Stimuli

Science.gov (United States)

Debruine, Lisa M.; Jones, Benedict C.; Smith, Finlay G.; Little, Anthony C.

2010-01-01

Women's preferences for male masculinity are highly variable. Although many researchers explain this variability as reflecting systematic individual differences in how women resolve the tradeoff between the costs and benefits of choosing a masculine partner, others suggest that methodological differences between studies are responsible. A recent…

Important variables in explaining real-time peak price in the independent power market of Ontario

International Nuclear Information System (INIS)

Rueda, I.E.A.; Marathe, A.

2005-01-01

This paper uses support vector machines (SVM) based learning algorithm to select important variables that help explain the real-time peak electricity price in the Ontario market. The Ontario market was opened to competition only in May 2002. Due to the limited number of observations available, finding a set of variables that can explain the independent power market of Ontario (IMO) real-time peak price is a significant challenge for the traders and analysts. The kernel regressions of the explanatory variables on the IMO real-time average peak price show that non-linear dependencies exist between the explanatory variables and the IMO price. This non-linear relationship combined with the low variable-observation ratio rule out conventional statistical analysis. Hence, we use an alternative machine learning technique to find the important explanatory variables for the IMO real-time average peak price. SVM sensitivity analysis based results find that the IMO's predispatch average peak price, the actual import peak volume, the peak load of the Ontario market and the net available supply after accounting for load (energy excess) are some of the most important variables in explaining the real-time average peak price in the Ontario electricity market. (author)

Cross-sectional analysis of food choice frequency, sleep confounding beverages, and psychological distress predictors of sleep quality.

Science.gov (United States)

Knowlden, Adam P; Burns, Maranda; Harcrow, Andy; Shewmake, Meghan E

2016-03-16

Poor sleep quality is a significant public health problem. The role of nutrition in predicting sleep quality is a relatively unexplored area of inquiry. The purpose of this study was to evaluate the capacity of 10 food choice categories, sleep confounding beverages, and psychological distress to predict the sleep quality of college students. A logistic regression model comprising 10 food choice variables (healthy proteins, unhealthy proteins, healthy dairy, unhealthy dairy, healthy grains, unhealthy grains, healthy fruits and vegetables, unhealthy empty calories, healthy beverages, unhealthy beverages), sleep confounding beverages (caffeinated/alcoholic beverages), as well as psychological distress (low, moderate, serious distress) was computed to determine the capacity of the variables to predict sleep quality (good/poor). The odds of poor sleep quality were 32.4% lower for each unit of increased frequency of healthy proteins consumed (pempty calorie food choices consumed (p=0.003; OR=1.131), and 107.3% higher for those classified in the moderate psychological distress (p=0.016; OR=2.073). Collectively, healthy proteins, healthy dairy, unhealthy empty calories, and moderate psychological distress were moderately predictive of sleep quality in the sample (Nagelkerke R2=23.8%). Results of the study suggested higher frequency of consumption of healthy protein and healthy dairy food choices reduced the odds of poor sleep quality, while higher consumption of empty calories and moderate psychological distress increased the odds of poor sleep quality.

Assessing mediation using marginal structural models in the presence of confounding and moderation

OpenAIRE

Coffman, Donna L.; Zhong, Wei

2012-01-01

This paper presents marginal structural models (MSMs) with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW can be used to take confounding into account, but IPW has several advantages. Regression adjustment of even one confounder of the mediator and ou...

Risk of cancer in the vicinity of municipal solid waste incinerators: importance of using a flexible modelling strategy

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Goria Sarah

2009-05-01

Full Text Available Abstract Background We conducted an ecological study in four French administrative departments and highlighted an excess risk in cancer morbidity for residents around municipal solid waste incinerators. The aim of this paper is to show how important are advanced tools and statistical techniques to better assess weak associations between the risk of cancer and past environmental exposures. Methods The steps to evaluate the association between the risk of cancer and the exposure to incinerators, from the assessment of exposure to the definition of the confounding variables and the statistical analysis carried out are detailed and discussed. Dispersion modelling was used to assess exposure to sixteen incinerators. A geographical information system was developed to define an index of exposure at the IRIS level that is the geographical unit we considered. Population density, rural/urban status, socio-economic deprivation, exposure to air pollution from traffic and from other industries were considered as potential confounding factors and defined at the IRIS level. Generalized additive models and Bayesian hierarchical models were used to estimate the association between the risk of cancer and the index of exposure to incinerators accounting for the confounding factors. Results Modelling to assess the exposure to municipal solid waste incinerators allowed accounting for factors known to influence the exposure (meteorological data, point source characteristics, topography. The statistical models defined allowed modelling extra-Poisson variability and also non-linear relationships between the risk of cancer and the exposure to incinerators and the confounders. Conclusion In most epidemiological studies distance is still used as a proxy for exposure. This can lead to significant exposure misclassification. Additionally, in geographical correlation studies the non-linear relationships are usually not accounted for in the statistical analysis. In studies of

Beyond total treatment effects in randomised controlled trials: Baseline measurement of intermediate outcomes needed to reduce confounding in mediation investigations.

Science.gov (United States)

Landau, Sabine; Emsley, Richard; Dunn, Graham

2018-06-01

Random allocation avoids confounding bias when estimating the average treatment effect. For continuous outcomes measured at post-treatment as well as prior to randomisation (baseline), analyses based on (A) post-treatment outcome alone, (B) change scores over the treatment phase or (C) conditioning on baseline values (analysis of covariance) provide unbiased estimators of the average treatment effect. The decision to include baseline values of the clinical outcome in the analysis is based on precision arguments, with analysis of covariance known to be most precise. Investigators increasingly carry out explanatory analyses to decompose total treatment effects into components that are mediated by an intermediate continuous outcome and a non-mediated part. Traditional mediation analysis might be performed based on (A) post-treatment values of the intermediate and clinical outcomes alone, (B) respective change scores or (C) conditioning on baseline measures of both intermediate and clinical outcomes. Using causal diagrams and Monte Carlo simulation, we investigated the performance of the three competing mediation approaches. We considered a data generating model that included three possible confounding processes involving baseline variables: The first two processes modelled baseline measures of the clinical variable or the intermediate variable as common causes of post-treatment measures of these two variables. The third process allowed the two baseline variables themselves to be correlated due to past common causes. We compared the analysis models implied by the competing mediation approaches with this data generating model to hypothesise likely biases in estimators, and tested these in a simulation study. We applied the methods to a randomised trial of pragmatic rehabilitation in patients with chronic fatigue syndrome, which examined the role of limiting activities as a mediator. Estimates of causal mediation effects derived by approach (A) will be biased if one of

Relative Importance of Political Instability and Economic Variables on Perceived Country Creditworthiness

OpenAIRE

Suk Hun Lee

1993-01-01

This paper examines the relative importance of political instability and economic variables on perceived country creditworthiness. Our results indicate that both political instability and economic variables are taken into account in evaluating country creditworthiness; however, it appears that bankers assign larger weight to economic performances, which we except of reflect longer term political stability. In addition, the frequency of changes in the regime and armed conflict, both proxying f...

Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

Science.gov (United States)

Vansteelandt, Stijn; Walter, Stefan; Tchetgen Tchetgen, Eric

2018-07-01

Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.

Cardiovascular health, traffic-related air pollution and noise: are associations mutually confounded? A systematic review.

Science.gov (United States)

Tétreault, Louis-François; Perron, Stéphane; Smargiassi, Audrey

2013-10-01

This review assessed the confounding effect of one traffic-related exposure (noise or air pollutants) on the association between the other exposure and cardiovascular outcomes. A systematic review was conducted with the databases Medline and Embase. The confounding effects in studies were assessed by using change in the estimate with a 10 % cutoff point. The influence on the change in the estimate of the quality of the studies, the exposure assessment methods and the correlation between road noise and air pollutions were also assessed. Nine publications were identified. For most studies, the specified confounders produced changes in estimates noise and pollutants, the quality of the study and of the exposure assessment do not seem to influence the confounding effects. Results from this review suggest that confounding of cardiovascular effects by noise or air pollutants is low, though with further improvements in exposure assessment, the situation may change. More studies using pollution indicators specific to road traffic are needed to properly assess if noise and air pollution are subjected to confounding.

Confounder selection in environmental epidemiology: Assessment of health effects of prenatal mercury exposure

DEFF Research Database (Denmark)

Budtz-Jørgensen, Esben; Keiding, Niels; Grandjean, Philippe

2007-01-01

PURPOSE: The purpose of the study is to compare different approaches to the identification of confounders needed for analyzing observational data. Whereas standard analysis usually is conducted as if the confounders were known a priori, selection uncertainty also must be taken into account. METHO...

Prostate-Specific Antigen Velocity Before and After Elimination of Factors That Can Confound the Prostate-Specific Antigen Level

International Nuclear Information System (INIS)

Park, Jessica J.; Chen, Ming-Hui; Loffredo, Marian; D’Amico, Anthony V.

2012-01-01

Purpose: Prostate-specific antigen (PSA) velocity, like PSA level, can be confounded. In this study, we estimated the impact that confounding factors could have on correctly identifying a patient with a PSA velocity >2 ng/ml/y. Methods and Materials: Between 2006 and 2010, a total of 50 men with newly diagnosed PC comprised the study cohort. We calculated and compared the false-positive and false-negative PSA velocity >2 ng/ml/y rates for all men and those with low-risk disease using two approaches to calculate PSA velocity. First, we used PSA values obtained within 18 months of diagnosis; second, we used values within 18 months of diagnosis, substituting the prebiopsy PSA for a repeat, nonconfounded PSA that was obtained using the same assay and without confounders. Results: Using PSA levels pre-biopsy, 46% of all men had a PSA velocity >2 ng/ml/y; whereas this value declined to 32% when substituting the last prebiopsy PSA for a repeat, nonconfounded PSA using the same assay and without confounders. The false-positive rate for PSA velocity >2 ng/ml/y was 43% as compared with a false-negative rate of PSA velocity >2 ng/ml/y of 11% (p = 0.0008) in the overall cohort. These respective values in the low-risk subgroup were 60% and 16.7% (p = 0.09). Conclusion: This study provides evidence to explain the discordance in cancer-specific outcomes among groups investigating the prognostic significance of PSA velocity >2 ng/ml/y, and highlights the importance of patient education on potential confounders of the PSA test before obtaining PSA levels.

Comparison of statistical approaches dealing with time-dependent confounding in drug effectiveness studies.

Science.gov (United States)

Karim, Mohammad Ehsanul; Petkau, John; Gustafson, Paul; Platt, Robert W; Tremlett, Helen

2018-06-01

In longitudinal studies, if the time-dependent covariates are affected by the past treatment, time-dependent confounding may be present. For a time-to-event response, marginal structural Cox models are frequently used to deal with such confounding. To avoid some of the problems of fitting marginal structural Cox model, the sequential Cox approach has been suggested as an alternative. Although the estimation mechanisms are different, both approaches claim to estimate the causal effect of treatment by appropriately adjusting for time-dependent confounding. We carry out simulation studies to assess the suitability of the sequential Cox approach for analyzing time-to-event data in the presence of a time-dependent covariate that may or may not be a time-dependent confounder. Results from these simulations revealed that the sequential Cox approach is not as effective as marginal structural Cox model in addressing the time-dependent confounding. The sequential Cox approach was also found to be inadequate in the presence of a time-dependent covariate. We propose a modified version of the sequential Cox approach that correctly estimates the treatment effect in both of the above scenarios. All approaches are applied to investigate the impact of beta-interferon treatment in delaying disability progression in the British Columbia Multiple Sclerosis cohort (1995-2008).

Neuropsychological functioning in older people with type 2 diabetes: the effect of controlling for confounding factors.

Science.gov (United States)

Asimakopoulou, K G; Hampson, S E; Morrish, N J

2002-04-01

Neuropsychological functioning was examined in a group of 33 older (mean age 62.40 +/- 9.62 years) people with Type 2 diabetes (Group 1) and 33 non-diabetic participants matched with Group 1 on age, sex, premorbid intelligence and presence of hypertension and cardio/cerebrovascular conditions (Group 2). Data statistically corrected for confounding factors obtained from the diabetic group were compared with the matched control group. The results suggested small cognitive deficits in diabetic people's verbal memory and mental flexibility (Logical Memory A and SS7). No differences were seen between the two samples in simple and complex visuomotor attention, sustained complex visual attention, attention efficiency, mental double tracking, implicit memory, and self-reported memory problems. These findings indicate minimal cognitive impairment in relatively uncomplicated Type 2 diabetes and demonstrate the importance of control and matching for confounding factors.

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

Science.gov (United States)

Cleophas, Ton J

2016-01-01

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

A Framework for Categorizing Important Project Variables

Science.gov (United States)

Parsons, Vickie S.

2003-01-01

While substantial research has led to theories concerning the variables that affect project success, no universal set of such variables has been acknowledged as the standard. The identification of a specific set of controllable variables is needed to minimize project failure. Much has been hypothesized about the need to match project controls and management processes to individual projects in order to increase the chance for success. However, an accepted taxonomy for facilitating this matching process does not exist. This paper surveyed existing literature on classification of project variables. After an analysis of those proposals, a simplified categorization is offered to encourage further research.

Wide Variability in Emergency Physician Admission Rates: A Target to Reduce Costs Without Compromising Quality

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Jeffrey J. Guterman

2016-09-01

Full Text Available Introduction: Attending physician judgment is the traditional standard of care for emergency department (ED admission decisions. The extent to which variability in admission decisions affect cost and quality is not well understood. We sought to determine the impact of variability in admission decisions on cost and quality. Methods: We performed a retrospective observational study of patients presenting to a university-affiliated, urban ED from October 1, 2007, through September 30, 2008. The main outcome measures were admission rate, fiscal indicators (Medicaid-denied payment days, and quality indicators (15- and 30-day ED returns; delayed hospital admissions. We asked each Attending to estimate their inpatient admission rate and correlated their personal assessment with actual admission rates. Results: Admission rates, even after adjusting for known confounders, were highly variable (15.2%-32.0% and correlated with Medicaid denied-payment day rates (p=0.038. There was no correlation with quality outcome measures (30-day ED return or delayed hospital admission. There was no significant correlation between actual and self-described admission rate; the range of mis-estimation was 0% to 117%. Conclusion: Emergency medicine attending admission rates at this institution are highly variable, unexplained by known confounding variables, and unrelated to quality of care, as measured by 30-day ED return or delayed hospital admission. Admission optimization represents an important untapped potential for cost reduction through avoidable hospitalizations, with no apparent adverse effects on quality.

Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments

DEFF Research Database (Denmark)

Pedersen, Kristine B.; Lejon, Tore; Ottosen, Lisbeth M.

2015-01-01

Using multivariate design and modelling, the optimal conditions for electrodialytic remediation (EDR) of heavy metals were determined for polluted harbour sediments from Hammerfest harbour located in the geographic Arctic region of Norway. The comparative importance of the variables, current......) was computed and variable importance in the projection was used to assess the influence of the experimental variables. Current density and remediation time proved to have the highest influence on the remediation of the heavy metals Cr, Cu, Ni, Pb and Zn in the studied experimental domain. In addition......, it was shown that excluding the acidification time improved the PLS model, indicating the importance of applying a limited experimental domain that covers the removal phases of each heavy metal in the specific sediment. Based on PLS modelling, the optimal conditions for remediating the Hammerfest sediment were...

Quantification of the impact of a confounding variable on functional connectivity confirms anti-correlated networks in the resting-state.

Science.gov (United States)

Carbonell, F; Bellec, P; Shmuel, A

2014-02-01

The effect of regressing out the global average signal (GAS) in resting state fMRI data has become a concern for interpreting functional connectivity analyses. It is not clear whether the reported anti-correlations between the Default Mode and the Dorsal Attention Networks are intrinsic to the brain, or are artificially created by regressing out the GAS. Here we introduce a concept, Impact of the Global Average on Functional Connectivity (IGAFC), for quantifying the sensitivity of seed-based correlation analyses to the regression of the GAS. This voxel-wise IGAFC index is defined as the product of two correlation coefficients: the correlation between the GAS and the fMRI time course of a voxel, times the correlation between the GAS and the seed time course. This definition enables the calculation of a threshold at which the impact of regressing-out the GAS would be large enough to introduce spurious negative correlations. It also yields a post-hoc impact correction procedure via thresholding, which eliminates spurious correlations introduced by regressing out the GAS. In addition, we introduce an Artificial Negative Correlation Index (ANCI), defined as the absolute difference between the IGAFC index and the impact threshold. The ANCI allows a graded confidence scale for ranking voxels according to their likelihood of showing artificial correlations. By applying this method, we observed regions in the Default Mode and Dorsal Attention Networks that were anti-correlated. These findings confirm that the previously reported negative correlations between the Dorsal Attention and Default Mode Networks are intrinsic to the brain and not the result of statistical manipulations. Our proposed quantification of the impact that a confound may have on functional connectivity can be generalized to global effect estimators other than the GAS. It can be readily applied to other confounds, such as systemic physiological or head movement interferences, in order to quantify their

ASSOCIATION BETWEEN EMOTIONAL VARIABLES AND SCHOOL ACHIEVEMENT

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Christoph Randler

2009-07-01

Full Text Available Recent psychological studies highlight emotional aspects, and they show an important role within individual learning processes. Hereby, positive emotions were supposed to positively influence learning and achievement processes and negative ones do the contrary. In this study, an educational unit “ecosystem lake” was used during which achievement (three tests and emotional variables (interest, well-being, anxiety and boredom; measured at the end of three pre-selected lessons were monitored. The research question was to explore correlations between emotional variables and the learning outcome of the teaching unit. Prior knowledge was regressed against the subsequent tests to account for its confounding effect. Regressions showed a highly significant influence of prior knowledge on the subsequent measurements of achievement. However, after accounting for prior knowledge, a positive correlation between interest/well-being and achievement and a negative correlation between anxiety/boredom and achievement was found. Further research and interventions should try to enhance positive emotions in biology lessons to positively influence achievement.

Measuring the surgical 'learning curve': methods, variables and competency.

Science.gov (United States)

Khan, Nuzhath; Abboudi, Hamid; Khan, Mohammed Shamim; Dasgupta, Prokar; Ahmed, Kamran

2014-03-01

To describe how learning curves are measured and what procedural variables are used to establish a 'learning curve' (LC). To assess whether LCs are a valuable measure of competency. A review of the surgical literature pertaining to LCs was conducted using the Medline and OVID databases. Variables should be fully defined and when possible, patient-specific variables should be used. Trainee's prior experience and level of supervision should be quantified; the case mix and complexity should ideally be constant. Logistic regression may be used to control for confounding variables. Ideally, a learning plateau should reach a predefined/expert-derived competency level, which should be fully defined. When the group splitting method is used, smaller cohorts should be used in order to narrow the range of the LC. Simulation technology and competence-based objective assessments may be used in training and assessment in LC studies. Measuring the surgical LC has potential benefits for patient safety and surgical education. However, standardisation in the methods and variables used to measure LCs is required. Confounding variables, such as participant's prior experience, case mix, difficulty of procedures and level of supervision, should be controlled. Competency and expert performance should be fully defined. © 2013 The Authors. BJU International © 2013 BJU International.

The importance of immune gene variability (MHC in evolutionary ecology and conservation

Directory of Open Access Journals (Sweden)

Sommer Simone

2005-10-01

Full Text Available Abstract Genetic studies have typically inferred the effects of human impact by documenting patterns of genetic differentiation and levels of genetic diversity among potentially isolated populations using selective neutral markers such as mitochondrial control region sequences, microsatellites or single nucleotide polymorphism (SNPs. However, evolutionary relevant and adaptive processes within and between populations can only be reflected by coding genes. In vertebrates, growing evidence suggests that genetic diversity is particularly important at the level of the major histocompatibility complex (MHC. MHC variants influence many important biological traits, including immune recognition, susceptibility to infectious and autoimmune diseases, individual odours, mating preferences, kin recognition, cooperation and pregnancy outcome. These diverse functions and characteristics place genes of the MHC among the best candidates for studies of mechanisms and significance of molecular adaptation in vertebrates. MHC variability is believed to be maintained by pathogen-driven selection, mediated either through heterozygote advantage or frequency-dependent selection. Up to now, most of our knowledge has derived from studies in humans or from model organisms under experimental, laboratory conditions. Empirical support for selective mechanisms in free-ranging animal populations in their natural environment is rare. In this review, I first introduce general information about the structure and function of MHC genes, as well as current hypotheses and concepts concerning the role of selection in the maintenance of MHC polymorphism. The evolutionary forces acting on the genetic diversity in coding and non-coding markers are compared. Then, I summarise empirical support for the functional importance of MHC variability in parasite resistance with emphasis on the evidence derived from free-ranging animal populations investigated in their natural habitat. Finally, I

R Package multiPIM: A Causal Inference Approach to Variable Importance Analysis

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Stephan J Ritter

2014-04-01

Full Text Available We describe the R package multiPIM, including statistical background, functionality and user options. The package is for variable importance analysis, and is meant primarily for analyzing data from exploratory epidemiological studies, though it could certainly be applied in other areas as well. The approach taken to variable importance comes from the causal inference field, and is different from approaches taken in other R packages. By default, multiPIM uses a double robust targeted maximum likelihood estimator (TMLE of a parameter akin to the attributable risk. Several regression methods/machine learning algorithms are available for estimating the nuisance parameters of the models, including super learner, a meta-learner which combines several different algorithms into one. We describe a simulation in which the double robust TMLE is compared to the graphical computation estimator. We also provide example analyses using two data sets which are included with the package.

Prenatal Paracetamol Exposure and Wheezing in Childhood: Causation or Confounding?

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Enrica Migliore

Full Text Available Several studies have reported an increased risk of wheezing in the children of mothers who used paracetamol during pregnancy. We evaluated to what extent this association is explained by confounding.We investigated the association between maternal paracetamol use in the first and third trimester of pregnancy and ever wheezing or recurrent wheezing/asthma in infants in the NINFEA cohort study. Risks ratios (RR and 95% confidence intervals (CI were estimated after adjustment for confounders, including maternal infections and antibiotic use during pregnancy.The prevalence of maternal paracetamol use was 30.6% during the first and 36.7% during the third trimester of pregnancy. The prevalence of ever wheezing and recurrent wheezing/asthma was 16.9% and 5.6%, respectively. After full adjustment, the RR for ever wheezing decreased from 1.25 [1.07-1.47] to 1.10 [0.94-1.30] in the first, and from 1.26 [1.08-1.47] to 1.10 [0.93-1.29] in the third trimester. A similar pattern was observed for recurrent wheezing/asthma. Duration of maternal paracetamol use was not associated with either outcome. Further analyses on paracetamol use for three non-infectious disorders (sciatica, migraine, and headache revealed no increased risk of wheezing in children.The association between maternal paracetamol use during pregnancy and infant wheezing is mainly, if not completely explained by confounding.

Investigating the Idoho oil spillage into Lagos: Some confounding ...

African Journals Online (AJOL)

... caused by these spillages must consider the socio-economic characteristics of the population as this may reveal a true picture of the event and facilitate proper interpretation of the result. Keywords: Toxicity, Idoho Oil Spillage, Confounders, Socio economic factors. Nigerian Journal of Health and Biomedical Sciences Vol.

Hypnotics and mortality – confounding by disease and socioeconomic position

DEFF Research Database (Denmark)

Kriegbaum, Margit; Hendriksen, Carsten; Vass, Mikkel

2015-01-01

Purpose The aim of this Cohort study of 10 527 Danish men was to investigate the extent to which the association between hypnotics and mortality is confounded by several markers of disease and living conditions. Methods Exposure was purchases of hypnotics 1995–1999 (“low users” (150 or less defined......% confidence intervals (CI). Results When covariates were entered one at a time, the changes in HR estimates showed that psychiatric disease, socioeconomic position and substance abuse reduced the excess risk by 17–36% in the low user group and by 45–52% in the high user group. Somatic disease, intelligence...... point at psychiatric disease, substance abuse and socioeconomic position as potential confounding factors partly explaining the association between use of hypnotics and all-cause mortality....

Variation in faecal water content may confound estimates of gastro-intestinal parasite intensity in wild African herbivores.

Science.gov (United States)

Turner, W C; Cizauskas, C A; Getz, W M

2010-03-01

Estimates of parasite intensity within host populations are essential for many studies of host-parasite relationships. Here we evaluated the seasonal, age- and sex-related variability in faecal water content for two wild ungulate species, springbok (Antidorcas marsupialis) and plains zebra (Equus quagga). We then assessed whether or not faecal water content biased conclusions regarding differences in strongyle infection rates by season, age or sex. There was evidence of significant variation in faecal water content by season and age for both species, and by sex in springbok. Analyses of faecal egg counts demonstrated that sex was a near-significant factor in explaining variation in strongyle parasite infection rates in zebra (P = 0.055) and springbok (P = 0.052) using wet-weight faecal samples. However, once these intensity estimates were re-scaled by the percent of dry matter in the faeces, sex was no longer a significant factor (zebra, P = 0.268; springbok, P = 0.234). These results demonstrate that variation in faecal water content may confound analyses and could produce spurious conclusions, as was the case with host sex as a factor in the analysis. We thus recommend that researchers assess whether water variation could be a confounding factor when designing and performing research using faecal indices of parasite intensity.

Dietary supplement use and smoking are important correlates of biomarkers of water-soluble vitamin status after adjusting for sociodemographic and lifestyle variables in a representative sample of U.S. adults.

Science.gov (United States)

Pfeiffer, Christine M; Sternberg, Maya R; Schleicher, Rosemary L; Rybak, Michael E

2013-06-01

Biochemical indicators of water-soluble vitamin (WSV) status were measured in a nationally representative sample of the U.S. population in NHANES 2003-2006. To examine whether demographic differentials in nutritional status were related to and confounded by certain variables, we assessed the association of sociodemographic (age, sex, race-ethnicity, education, income) and lifestyle (dietary supplement use, smoking, alcohol consumption, BMI, physical activity) variables with biomarkers of WSV status in adults (aged ≥ 20 y): serum and RBC folate, serum pyridoxal-5'-phosphate (PLP), serum 4-pyridoxic acid, serum total cobalamin (vitamin B-12), plasma total homocysteine (tHcy), plasma methylmalonic acid (MMA), and serum ascorbic acid. Age (except for PLP) and smoking (except for MMA) were generally the strongest significant correlates of these biomarkers (|r| ≤ 0.43) and together with supplement use explained more of the variability compared with the other covariates in bivariate analysis. In multiple regression models, sociodemographic and lifestyle variables together explained from 7 (vitamin B-12) to 29% (tHcy) of the biomarker variability. We observed significant associations for most biomarkers (≥ 6 of 8) with age, sex, race-ethnicity, supplement use, smoking, and BMI and for some biomarkers with PIR (5 of 8), education (1 of 8), alcohol consumption (4 of 8), and physical activity (5 of 8). We noted large estimated percentage changes in biomarker concentrations between race-ethnic groups (from -24 to 20%), between supplement users and nonusers (from -12 to 104%), and between smokers and nonsmokers (from -28 to 8%). In summary, age, sex, and race-ethnic differentials in biomarker concentrations remained significant after adjusting for sociodemographic and lifestyle variables. Supplement use and smoking were important correlates of biomarkers of WSV status.

Increasing importance of precipitation variability on global livestock grazing lands

Science.gov (United States)

Sloat, Lindsey L.; Gerber, James S.; Samberg, Leah H.; Smith, William K.; Herrero, Mario; Ferreira, Laerte G.; Godde, Cécile M.; West, Paul C.

2018-03-01

Pastures and rangelands underpin global meat and milk production and are a critical resource for millions of people dependent on livestock for food security1,2. Forage growth, which is highly climate dependent3,4, is potentially vulnerable to climate change, although precisely where and to what extent remains relatively unexplored. In this study, we assess climate-based threats to global pastures, with a specific focus on changes in within- and between-year precipitation variability (precipitation concentration index (PCI) and coefficient of variation of precipitation (CVP), respectively). Relating global satellite measures of vegetation greenness (such as the Normalized Difference Vegetation Index; NDVI) to key climatic factors reveals that CVP is a significant, yet often overlooked, constraint on vegetation productivity across global pastures. Using independent stocking data, we found that areas with high CVP support lower livestock densities than less-variable regions. Globally, pastures experience about a 25% greater year-to-year precipitation variation (CVP = 0.27) than the average global land surface area (0.21). Over the past century, CVP has generally increased across pasture areas, although both positive (49% of pasture area) and negative (31% of pasture area) trends exist. We identify regions in which livestock grazing is important for local food access and economies, and discuss the potential for pasture intensification in the context of long-term regional trends in precipitation variability.

Carotta: Revealing Hidden Confounder Markers in Metabolic Breath Profiles

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Anne-Christin Hauschild

2015-06-01

Full Text Available Computational breath analysis is a growing research area aiming at identifying volatile organic compounds (VOCs in human breath to assist medical diagnostics of the next generation. While inexpensive and non-invasive bioanalytical technologies for metabolite detection in exhaled air and bacterial/fungal vapor exist and the first studies on the power of supervised machine learning methods for profiling of the resulting data were conducted, we lack methods to extract hidden data features emerging from confounding factors. Here, we present Carotta, a new cluster analysis framework dedicated to uncovering such hidden substructures by sophisticated unsupervised statistical learning methods. We study the power of transitivity clustering and hierarchical clustering to identify groups of VOCs with similar expression behavior over most patient breath samples and/or groups of patients with a similar VOC intensity pattern. This enables the discovery of dependencies between metabolites. On the one hand, this allows us to eliminate the effect of potential confounding factors hindering disease classification, such as smoking. On the other hand, we may also identify VOCs associated with disease subtypes or concomitant diseases. Carotta is an open source software with an intuitive graphical user interface promoting data handling, analysis and visualization. The back-end is designed to be modular, allowing for easy extensions with plugins in the future, such as new clustering methods and statistics. It does not require much prior knowledge or technical skills to operate. We demonstrate its power and applicability by means of one artificial dataset. We also apply Carotta exemplarily to a real-world example dataset on chronic obstructive pulmonary disease (COPD. While the artificial data are utilized as a proof of concept, we will demonstrate how Carotta finds candidate markers in our real dataset associated with confounders rather than the primary disease (COPD

The ad-libitum alcohol 'taste test': secondary analyses of potential confounds and construct validity.

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Jones, Andrew; Button, Emily; Rose, Abigail K; Robinson, Eric; Christiansen, Paul; Di Lemma, Lisa; Field, Matt

2016-03-01

Motivation to drink alcohol can be measured in the laboratory using an ad-libitum 'taste test', in which participants rate the taste of alcoholic drinks whilst their intake is covertly monitored. Little is known about the construct validity of this paradigm. The objective of this study was to investigate variables that may compromise the validity of this paradigm and its construct validity. We re-analysed data from 12 studies from our laboratory that incorporated an ad-libitum taste test. We considered time of day and participants' awareness of the purpose of the taste test as potential confounding variables. We examined whether gender, typical alcohol consumption, subjective craving, scores on the Alcohol Use Disorders Identification Test and perceived pleasantness of the drinks predicted ad-libitum consumption (construct validity). We included 762 participants (462 female). Participant awareness and time of day were not related to ad-libitum alcohol consumption. Males drank significantly more alcohol than females (p alcohol consumption (p = 0.04), craving (p alcohol consumption. The construct validity of the taste test was supported by relationships between ad-libitum consumption and typical alcohol consumption, craving and pleasantness ratings of the drinks. The ad-libitum taste test is a valid method for the assessment of alcohol intake in the laboratory.

Confounding by dietary patterns of the inverse association between alcohol consumption and type 2 diabetes risk

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Epidemiology of dietary components and disease risk limits interpretability due to potential residual confounding by correlated dietary components. Dietary pattern analyses by factor analysis or partial least squares may overcome this limitation. To examine confounding by dietary pattern as well as ...

Confounding by dietary pattern of the inverse association between alcohol consumption and type 2 diabetes risk

Science.gov (United States)

Epidemiology of dietary components and disease risk limits interpretability due to potential residual confounding by correlated dietary components. Dietary pattern analyses by factor analysis or partial least squares may overcome the limitation. To examine confounding by dietary pattern as well as ...

Chasing the effects of Pre-analytical Confounders - a Multicentre Study on CSF-AD biomarkers

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Maria Joao Leitao

2015-07-01

Full Text Available Core cerebrospinal fluid (CSF biomarkers-Aβ42, Tau and pTau–have been recently incorporated in the revised criteria for Alzheimer’s disease (AD. However, their widespread clinical application lacks standardization. Pre-analytical sample handling and storage play an important role in the reliable measurement of these biomarkers across laboratories. In this study, we aim to surpass the efforts from previous studies, by employing a multicentre approach to assess the impact of less studied CSF pre-analytical confounders in AD-biomarkers quantification. Four different centres participated in this study and followed the same established protocol. CSF samples were analysed for three biomarkers (Aβ42, Tau and pTau and tested for different spinning conditions (temperature: Room temperature (RT vs. 4oC; speed: 500g vs. 2000g vs. 3000g, storage volume variations (25%, 50% and 75% of tube total volume as well as freezing-thaw cycles (up to 5 cyles. The influence of sample routine parameters, inter-centre variability and relative value of each biomarker (reported as normal/abnormal, was analysed. Centrifugation conditions did not influence biomarkers levels, except for samples with a high CSF total protein content, where either non centrifugation or centrifugation at RT, compared to 4ºC, led to higher Aβ42 levels. Reducing CSF storage volume from 75% to 50% of total tube capacity, decreased Aβ42 concentration (within analytical CV of the assay, whereas no change in Tau or pTau was observed. Moreover, the concentration of Tau and pTau appears to be stable up to 5 freeze-thaw cycles, whereas Aβ42 levels decrease if CSF is freeze-thawed more than 3 times. This systematic study reinforces the need for CSF centrifugation at 4ºC prior to storage and highlights the influence of storage conditions in Aβ42 levels. This study contributes to the establishment of harmonized standard operating procedures that will help reducing inter-lab variability of CSF

Complex analyses of inverted repeats in mitochondrial genomes revealed their importance and variability.

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Cechová, Jana; Lýsek, Jirí; Bartas, Martin; Brázda, Václav

2018-04-01

The NCBI database contains mitochondrial DNA (mtDNA) genomes from numerous species. We investigated the presence and locations of inverted repeat sequences (IRs) in these mtDNA sequences, which are known to be important for regulating nuclear genomes. IRs were identified in mtDNA in all species. IR lengths and frequencies correlate with evolutionary age and the greatest variability was detected in subgroups of plants and fungi and the lowest variability in mammals. IR presence is non-random and evolutionary favoured. The frequency of IRs generally decreased with IR length, but not for IRs 24 or 30 bp long, which are 1.5 times more abundant. IRs are enriched in sequences from the replication origin, followed by D-loop, stem-loop and miscellaneous sequences, pointing to the importance of IRs in regulatory regions of mitochondrial DNA. Data were produced using Palindrome analyser, freely available on the web at http://bioinformatics.ibp.cz. vaclav@ibp.cz. Supplementary data are available at Bioinformatics online.

THE RELATIVE IMPORTANCE OF FINANCIAL RATIOS AND NONFINANCIAL VARIABLES IN PREDICTING OF INSOLVENCY

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Ivica Pervan

2013-02-01

Full Text Available One of the most important decisions in every bank is approving loans to firms, which is based on evaluated credit risk and collateral. Namely, it is necessary to evaluate the risk that client will be unable to repay the obligations according to the contract. After Beaver's (1967 and Altman's (1968 seminal papers many authors extended the initial research by changing the methodology, samples, countries, etc. But majority of business failure papers as predictors use financial ratios, while in the real life banks combine financial and nonfinancial variables. In order to test predictive power of nonfinancial variables authors in the paper compare two insolvency prediction models. The first model that used financial rations resulted with classification accuracy of 82.8%, while the combined model with financial and nonfinancial variables resulted with classification accuracy of 88.1%.

Dietary supplement use and smoking are important correlates of biomarkers of water-soluble vitamin status after adjusting for sociodemographic and lifestyle variables in a representative sample of US adults1,2,3

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Pfeiffer, Christine M.; Sternberg, Maya R.; Schleicher, Rosemary L.; Rybak, Michael E.

2016-01-01

Biochemical indicators of water-soluble vitamin (WSV) status have been measured in a nationally representative sample of the US population in NHANES 2003–2006. To examine whether demographic differentials in nutritional status were related to and confounded by certain variables, we assessed the association of sociodemographic (age, sex, race-ethnicity, education, income) and lifestyle variables (dietary supplement use, smoking, alcohol consumption, BMI, physical activity) with biomarkers of WSV status in adults (≥20 y): serum and RBC folate, serum pyridoxal-5′-phosphate (PLP), serum 4-pyridoxic acid, serum total cobalamin (B-12), plasma total homocysteine (tHcy), plasma methylmalonic acid (MMA), and serum ascorbic acid. Age (except for PLP) and smoking (except for MMA) were generally the strongest significant correlates of these biomarkers (|r| ≤0.43) and together with supplement use explained more of the variability as compared to the other covariates in bivariate analysis. In multiple regression models, sociodemographic and lifestyle variables together explained from 7% (B-12) to 29% (tHcy) of the biomarker variability. We observed significant associations for most biomarkers (≥6 out of 8) with age, sex, race-ethnicity, supplement use, smoking, and BMI; and for some biomarkers with PIR (5/8), education (1/8), alcohol consumption (4/8), and physical activity (5/8). We noted large estimated percent changes in biomarker concentrations between race-ethnic groups (from −24% to 20%), between supplement users and nonusers (from −12% to 104%), and between smokers and nonsmokers (from −28% to 8%). In summary, age, sex, and race-ethnic differentials in biomarker concentrations remained significant after adjusting for sociodemographic and lifestyle variables. Supplement use and smoking were important correlates of biomarkers of WSV status. PMID:23576641

The Association Between Headaches and Temporomandibular Disorders is Confounded by Bruxism and Somatic Symptoms.

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van der Meer, Hedwig A; Speksnijder, Caroline M; Engelbert, Raoul H H; Lobbezoo, Frank; Nijhuis-van der Sanden, Maria W G; Visscher, Corine M

2017-09-01

The objective of this observational study was to establish the possible presence of confounders on the association between temporomandibular disorders (TMD) and headaches in a patient population from a TMD and Orofacial Pain Clinic. Several subtypes of headaches have been diagnosed: self-reported headache, (probable) migraine, (probable) tension-type headache, and secondary headache attributed to TMD. The presence of TMD was subdivided into 2 subtypes: painful TMD and function-related TMD. The associations between the subtypes of TMD and headaches were evaluated by single regression models. To study the influence of possible confounding factors on this association, the regression models were extended with age, sex, bruxism, stress, depression, and somatic symptoms. Of the included patients (n=203), 67.5% experienced headaches. In the subsample of patients with a painful TMD (n=58), the prevalence of self-reported headaches increased to 82.8%. The associations found between self-reported headache and (1) painful TMD and (2) function-related TMD were confounded by the presence of somatic symptoms. For probable migraine, both somatic symptoms and bruxism confounded the initial association found with painful TMD. The findings of this study imply that there is a central working mechanism overlapping TMD and headache. Health care providers should not regard these disorders separately, but rather look at the bigger picture to appreciate the complex nature of the diagnostic and therapeutic process.

PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances.

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Tang, Zheng-Zheng; Chen, Guanhua; Alekseyenko, Alexander V

2016-09-01

Recent advances in sequencing technology have made it possible to obtain high-throughput data on the composition of microbial communities and to study the effects of dysbiosis on the human host. Analysis of pairwise intersample distances quantifies the association between the microbiome diversity and covariates of interest (e.g. environmental factors, clinical outcomes, treatment groups). In the design of these analyses, multiple choices for distance metrics are available. Most distance-based methods, however, use a single distance and are underpowered if the distance is poorly chosen. In addition, distance-based tests cannot flexibly handle confounding variables, which can result in excessive false-positive findings. We derive presence-weighted UniFrac to complement the existing UniFrac distances for more powerful detection of the variation in species richness. We develop PERMANOVA-S, a new distance-based method that tests the association of microbiome composition with any covariates of interest. PERMANOVA-S improves the commonly-used Permutation Multivariate Analysis of Variance (PERMANOVA) test by allowing flexible confounder adjustments and ensembling multiple distances. We conducted extensive simulation studies to evaluate the performance of different distances under various patterns of association. Our simulation studies demonstrate that the power of the test relies on how well the selected distance captures the nature of the association. The PERMANOVA-S unified test combines multiple distances and achieves good power regardless of the patterns of the underlying association. We demonstrate the usefulness of our approach by reanalyzing several real microbiome datasets. miProfile software is freely available at https://medschool.vanderbilt.edu/tang-lab/software/miProfile z.tang@vanderbilt.edu or g.chen@vanderbilt.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Studies and research concerning BNFP. Identification and simplified modeling of economically important radwaste variables

International Nuclear Information System (INIS)

Ebel, P.E.; Godfrey, W.L.; Henry, J.L.; Postles, R.L.

1983-09-01

An extensive computer model describing the mass balance and economic characteristics of radioactive waste disposal systems was exercised in a series of runs designed using linear statistical methods. The most economically important variables were identified, their behavior characterized, and a simplified computer model prepared which runs on desk-top minicomputers. This simplified model allows the investigation of the effects of the seven most significant variables in each of four waste areas: Liquid Waste Storage, Liquid Waste Solidification, General Process Trash Handling, and Hulls Handling. 8 references, 1 figure, 12 tables

[The intelligence quotient and malnutrition. Iron deficiency and the lead concentration as confusing variables].

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Vega-Franco, L; Mejía, A M; Robles, B; Moreno, L; Pérez, Y

1991-11-01

This study gave us the opportunity to know the roles iron deficiency and the presence of lead in blood play, as confounding variables, in relation to the state of malnutrition and the intellect of those children. A sample of 169 school children were classified according to their state of nutrition, their condition in reference to serum iron and lead concentrations. In addition, their intelligence was evaluated. The results confirmed that those children with lower weights and heights registered lesser points of intelligence; in fact, iron deficiency cancels out the difference in favor of those taller and weighing more. Lead did not contribute as a confounding variable, but more than half of the children showed possible toxic levels of this metal.

Variable selection for confounder control, flexible modeling and Collaborative Targeted Minimum Loss-based Estimation in causal inference

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Schnitzer, Mireille E.; Lok, Judith J.; Gruber, Susan

2015-01-01

This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low-and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios. PMID:26226129

Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability.

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Shaowei Sang

Full Text Available Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF, a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose.Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8% imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags.Imported DF cases and mosquito

Accounting for Time-Varying Confounding in the Relationship Between Obesity and Coronary Heart Disease: Analysis With G-Estimation: The ARIC Study.

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Shakiba, Maryam; Mansournia, Mohammad Ali; Salari, Arsalan; Soori, Hamid; Mansournia, Nasrin; Kaufman, Jay S

2018-06-01

In longitudinal studies, standard analysis may yield biased estimates of exposure effect in the presence of time-varying confounders that are also intermediate variables. We aimed to quantify the relationship between obesity and coronary heart disease (CHD) by appropriately adjusting for time-varying confounders. This study was performed in a subset of participants from the Atherosclerosis Risk in Communities (ARIC) Study (1987-2010), a US study designed to investigate risk factors for atherosclerosis. General obesity was defined as body mass index (weight (kg)/height (m)2) ≥30, and abdominal obesity (AOB) was defined according to either waist circumference (≥102 cm in men and ≥88 cm in women) or waist:hip ratio (≥0.9 in men and ≥0.85 in women). The association of obesity with CHD was estimated by G-estimation and compared with results from accelerated failure-time models using 3 specifications. The first model, which adjusted for baseline covariates, excluding metabolic mediators of obesity, showed increased risk of CHD for all obesity measures. Further adjustment for metabolic mediators in the second model and time-varying variables in the third model produced negligible changes in the hazard ratios. The hazard ratios estimated by G-estimation were 1.15 (95% confidence interval (CI): 0.83, 1.47) for general obesity, 1.65 (95% CI: 1.35, 1.92) for AOB based on waist circumference, and 1.38 (95% CI: 1.13, 1.99) for AOB based on waist:hip ratio, suggesting that AOB increased the risk of CHD. The G-estimated hazard ratios for both measures were further from the null than those derived from standard models.

A two-stage model in a Bayesian framework to estimate a survival endpoint in the presence of confounding by indication.

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Bellera, Carine; Proust-Lima, Cécile; Joseph, Lawrence; Richaud, Pierre; Taylor, Jeremy; Sandler, Howard; Hanley, James; Mathoulin-Pélissier, Simone

2018-04-01

Background Biomarker series can indicate disease progression and predict clinical endpoints. When a treatment is prescribed depending on the biomarker, confounding by indication might be introduced if the treatment modifies the marker profile and risk of failure. Objective Our aim was to highlight the flexibility of a two-stage model fitted within a Bayesian Markov Chain Monte Carlo framework. For this purpose, we monitored the prostate-specific antigens in prostate cancer patients treated with external beam radiation therapy. In the presence of rising prostate-specific antigens after external beam radiation therapy, salvage hormone therapy can be prescribed to reduce both the prostate-specific antigens concentration and the risk of clinical failure, an illustration of confounding by indication. We focused on the assessment of the prognostic value of hormone therapy and prostate-specific antigens trajectory on the risk of failure. Methods We used a two-stage model within a Bayesian framework to assess the role of the prostate-specific antigens profile on clinical failure while accounting for a secondary treatment prescribed by indication. We modeled prostate-specific antigens using a hierarchical piecewise linear trajectory with a random changepoint. Residual prostate-specific antigens variability was expressed as a function of prostate-specific antigens concentration. Covariates in the survival model included hormone therapy, baseline characteristics, and individual predictions of the prostate-specific antigens nadir and timing and prostate-specific antigens slopes before and after the nadir as provided by the longitudinal process. Results We showed positive associations between an increased prostate-specific antigens nadir, an earlier changepoint and a steeper post-nadir slope with an increased risk of failure. Importantly, we highlighted a significant benefit of hormone therapy, an effect that was not observed when the prostate-specific antigens trajectory was

LD Score regression distinguishes confounding from polygenicity in genome-wide association studies

DEFF Research Database (Denmark)

Bulik-Sullivan, Brendan K.; Loh, Po-Ru; Finucane, Hilary K.

2015-01-01

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from...

Marine oils: Complex, confusing, confounded?

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Benjamin B. Albert

2016-09-01

Full Text Available Marine oils gained prominence following the report that Greenland Inuits who consumed a high-fat diet rich in long-chain n-3 polyunsaturated fatty acids (PUFAs also had low rates of cardiovascular disease. Marine n-3 PUFAs have since become a billion dollar industry, which will continue to grow based on current trends. However, recent systematic reviews question the health benefits of marine oil supplements, particularly in the prevention of cardiovascular disease. Marine oils constitute an extremely complex dietary intervention for a number of reasons: i the many chemical compounds they contain; ii the many biological processes affected by n-3 PUFAs; iii their tendency to deteriorate and form potentially toxic primary and secondary oxidation products; and iv inaccuracy in the labelling of consumer products. These complexities may confound the clinical literature, limiting the ability to make substantive conclusions for some key health outcomes. Thus, there is a pressing need for clinical trials using marine oils whose composition has been independently verified and demonstrated to be minimally oxidised. Without such data, it is premature to conclude that n-3 PUFA rich supplements are ineffective.

Is the association between general cognitive ability and violent crime caused by family-level confounders?

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Frisell, Thomas; Pawitan, Yudi; Långström, Niklas

2012-01-01

Research has consistently found lower cognitive ability to be related to increased risk for violent and other antisocial behaviour. Since this association has remained when adjusting for childhood socioeconomic position, ethnicity, and parental characteristics, it is often assumed to be causal, potentially mediated through school adjustment problems and conduct disorder. Socioeconomic differences are notoriously difficult to quantify, however, and it is possible that the association between intelligence and delinquency suffer substantial residual confounding. We linked longitudinal Swedish total population registers to study the association of general cognitive ability (intelligence) at age 18 (the Conscript Register, 1980-1993) with the incidence proportion of violent criminal convictions (the Crime Register, 1973-2009), among all men born in Sweden 1961-1975 (N = 700,514). Using probit regression, we controlled for measured childhood socioeconomic variables, and further employed sibling comparisons (family pedigree data from the Multi-Generation Register) to adjust for shared familial characteristics. Cognitive ability in early adulthood was inversely associated to having been convicted of a violent crime (β = -0.19, 95% CI: -0.19; -0.18), the association remained when adjusting for childhood socioeconomic factors (β = -0.18, 95% CI: -0.18; -0.17). The association was somewhat lower within half-brothers raised apart (β = -0.16, 95% CI: -0.18; -0.14), within half-brothers raised together (β = -0.13, 95% CI: (-0.15; -0.11), and lower still in full-brother pairs (β = -0.10, 95% CI: -0.11; -0.09). The attenuation among half-brothers raised together and full brothers was too strong to be attributed solely to attenuation from measurement error. Our results suggest that the association between general cognitive ability and violent criminality is confounded partly by factors shared by brothers. However, most of the association remains even

External adjustment of unmeasured confounders in a case-control study of benzodiazepine use and cancer risk

DEFF Research Database (Denmark)

Thygesen, Lau Caspar; Pottegård, Anton; Ersbøll, Annette Kjaer

2017-01-01

AIMS: Previous studies have reported diverging results on the association between benzodiazepine use and cancer risk. METHODS: We investigated this association in a matched case-control study including incident cancer cases during 2002-2009 in the Danish Cancer Registry (n = 94 923) and age......% confidence interval 1.00-1.19) and for smoking-related cancers from 1.20 to 1.10 (95% confidence interval 1.00-1.21). CONCLUSION: We conclude that the increased risk observed in the solely register-based study could partly be attributed to unmeasured confounding....... PSs were used: The error-prone PS using register-based confounders and the calibrated PS based on both register- and survey-based confounders, retrieved from the Health Interview Survey. RESULTS: Register-based data showed that cancer cases had more diagnoses, higher comorbidity score and more co...

Learner Variables Important for Success in L2 Listening Comprehension in French Immersion Classrooms

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Vandergrift, Larry; Baker, Susan C.

2018-01-01

Listening comprehension, which is relatively straightforward for native language (L1) speakers, is often frustrating for second language (L2) learners. Listening comprehension is important to L2 acquisition, but little is known about the variables that influence the development of L2 listening skills. The goal of this study was to determine which…

The relationship between urinary tract infection during pregnancy and preeclampsia: causal, confounded or spurious?

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Karmon, Anatte; Sheiner, Eyal

2008-06-01

Preeclampsia is a major cause of maternal morbidity, although its precise etiology remains elusive. A number of studies suggest that urinary tract infection (UTI) during the course of gestation is associated with elevated risk for preeclampsia, while others have failed to prove such an association. In our medical center, pregnant women who were exposed to at least one UTI episode during pregnancy were 1.3 times more likely to have mild preeclampsia and 1.8 times more likely to have severe preeclampsia as compared to unexposed women. Our results are based on univariate analyses and are not adjusted for potential confounders. This editorial aims to discuss the relationship between urinary tract infection and preeclampsia, as well as examine the current problems regarding the interpretation of this association. Although the relationship between UTI and preeclampsia has been demonstrated in studies with various designs, carried-out in a variety of settings, the nature of this association is unclear. By taking into account timeline, dose-response effects, treatment influences, and potential confounders, as well as by neutralizing potential biases, future studies may be able to clarify the relationship between UTI and preeclampsia by determining if it is causal, confounded, or spurious.

Do patient and practice characteristics confound age-group differences in preferences for general practice care? A quantitative study

Science.gov (United States)

2013-01-01

Background Previous research showed inconsistent results regarding the relationship between the age of patients and preference statements regarding GP care. This study investigates whether elderly patients have different preference scores and ranking orders concerning 58 preference statements for GP care than younger patients. Moreover, this study examines whether patient characteristics and practice location may confound the relationship between age and the categorisation of a preference score as very important. Methods Data of the Consumer Quality Index GP Care were used, which were collected in 32 general practices in the Netherlands. The rank order and preference score were calculated for 58 preference statements for four age groups (0–30, 31–50, 51–74, 75 years and older). Using chi-square tests and logistic regression analyses, it was investigated whether a significant relationship between age and preference score was confounded by patient characteristics and practice location. Results Elderly patients did not have a significant different ranking order for the preference statements than the other three age groups (r = 0.0193; p = 0.41). However, in 53% of the statements significant differences were found in preference score between the four age groups. Elderly patients categorized significantly less preference statements as ‘very important’. In most cases, the significant relationships were not confounded by gender, education, perceived health, the number of GP contacts and location of the GP practice. Conclusion The preferences of elderly patients for GP care concern the same items as younger patients. However, their preferences are less strong, which cannot be ascribed to gender, education, perceived health, the number of GP contacts and practice location. PMID:23800156

Translational Rodent Models for Research on Parasitic Protozoa-A Review of Confounders and Possibilities.

Science.gov (United States)

Ehret, Totta; Torelli, Francesca; Klotz, Christian; Pedersen, Amy B; Seeber, Frank

2017-01-01

Rodents, in particular Mus musculus , have a long and invaluable history as models for human diseases in biomedical research, although their translational value has been challenged in a number of cases. We provide some examples in which rodents have been suboptimal as models for human biology and discuss confounders which influence experiments and may explain some of the misleading results. Infections of rodents with protozoan parasites are no exception in requiring close consideration upon model choice. We focus on the significant differences between inbred, outbred and wild animals, and the importance of factors such as microbiota, which are gaining attention as crucial variables in infection experiments. Frequently, mouse or rat models are chosen for convenience, e.g., availability in the institution rather than on an unbiased evaluation of whether they provide the answer to a given question. Apart from a general discussion on translational success or failure, we provide examples where infections with single-celled parasites in a chosen lab rodent gave contradictory or misleading results, and when possible discuss the reason for this. We present emerging alternatives to traditional rodent models, such as humanized mice and organoid primary cell cultures. So-called recombinant inbred strains such as the Collaborative Cross collection are also a potential solution for certain challenges. In addition, we emphasize the advantages of using wild rodents for certain immunological, ecological, and/or behavioral questions. The experimental challenges (e.g., availability of species-specific reagents) that come with the use of such non-model systems are also discussed. Our intention is to foster critical judgment of both traditional and newly available translational rodent models for research on parasitic protozoa that can complement the existing mouse and rat models.

Translational Rodent Models for Research on Parasitic Protozoa—A Review of Confounders and Possibilities

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Totta Ehret

2017-06-01

Full Text Available Rodents, in particular Mus musculus, have a long and invaluable history as models for human diseases in biomedical research, although their translational value has been challenged in a number of cases. We provide some examples in which rodents have been suboptimal as models for human biology and discuss confounders which influence experiments and may explain some of the misleading results. Infections of rodents with protozoan parasites are no exception in requiring close consideration upon model choice. We focus on the significant differences between inbred, outbred and wild animals, and the importance of factors such as microbiota, which are gaining attention as crucial variables in infection experiments. Frequently, mouse or rat models are chosen for convenience, e.g., availability in the institution rather than on an unbiased evaluation of whether they provide the answer to a given question. Apart from a general discussion on translational success or failure, we provide examples where infections with single-celled parasites in a chosen lab rodent gave contradictory or misleading results, and when possible discuss the reason for this. We present emerging alternatives to traditional rodent models, such as humanized mice and organoid primary cell cultures. So-called recombinant inbred strains such as the Collaborative Cross collection are also a potential solution for certain challenges. In addition, we emphasize the advantages of using wild rodents for certain immunological, ecological, and/or behavioral questions. The experimental challenges (e.g., availability of species-specific reagents that come with the use of such non-model systems are also discussed. Our intention is to foster critical judgment of both traditional and newly available translational rodent models for research on parasitic protozoa that can complement the existing mouse and rat models.

What variables are important in predicting bovine viral diarrhea virus? A random forest approach.

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Machado, Gustavo; Mendoza, Mariana Recamonde; Corbellini, Luis Gustavo

2015-07-24

Bovine viral diarrhea virus (BVDV) causes one of the most economically important diseases in cattle, and the virus is found worldwide. A better understanding of the disease associated factors is a crucial step towards the definition of strategies for control and eradication. In this study we trained a random forest (RF) prediction model and performed variable importance analysis to identify factors associated with BVDV occurrence. In addition, we assessed the influence of features selection on RF performance and evaluated its predictive power relative to other popular classifiers and to logistic regression. We found that RF classification model resulted in an average error rate of 32.03% for the negative class (negative for BVDV) and 36.78% for the positive class (positive for BVDV).The RF model presented area under the ROC curve equal to 0.702. Variable importance analysis revealed that important predictors of BVDV occurrence were: a) who inseminates the animals, b) number of neighboring farms that have cattle and c) rectal palpation performed routinely. Our results suggest that the use of machine learning algorithms, especially RF, is a promising methodology for the analysis of cross-sectional studies, presenting a satisfactory predictive power and the ability to identify predictors that represent potential risk factors for BVDV investigation. We examined classical predictors and found some new and hard to control practices that may lead to the spread of this disease within and among farms, mainly regarding poor or neglected reproduction management, which should be considered for disease control and eradication.

Environmental lead exposure is associated with visit-to-visit systolic blood pressure variability in the US adults.

Science.gov (United States)

Faramawi, Mohammed F; Delongchamp, Robert; Lin, Yu-Sheng; Liu, Youcheng; Abouelenien, Saly; Fischbach, Lori; Jadhav, Supriya

2015-04-01

The association between environmental lead exposure and blood pressure variability, an important risk factor for cardiovascular disease, is unexplored and unknown. The objective of the study was to test the hypothesis that lead exposure is associated with blood pressure variability. American participants 17 years of age or older from National Health and Nutrition Examination Survey III were included in the analysis. Participants' blood lead concentrations expressed as micrograms per deciliter were determined. The standard deviations of visit-to-visit systolic and diastolic blood pressure were calculated to determine blood pressure variability. Multivariable regression analyses adjusted for age, gender, race, smoking and socioeconomic status were employed. The participants' mean age and mean blood lead concentration were 42.72 years and 3.44 mcg/dl, respectively. Systolic blood pressure variability was significantly associated with environmental lead exposure after adjusting for the effect of the confounders. The unadjusted and adjusted means of visit-to-visit systolic blood pressure variability and the β coefficient of lead exposure were 3.44, 3.33 mcg/dl, β coefficient = 0.07, P variability. Screening adults with fluctuating blood pressure for lead exposure could be warranted.

Wind turbines and idiopathic symptoms: The confounding effect of concurrent environmental exposures.

Science.gov (United States)

Blanes-Vidal, Victoria; Schwartz, Joel

2016-01-01

Whether or not wind turbines pose a risk to human health is a matter of heated debate. Personal reactions to other environmental exposures occurring in the same settings as wind turbines may be responsible of the reported symptoms. However, these have not been accounted for in previous studies. We investigated whether there is an association between residential proximity to wind turbines and idiopathic symptoms, after controlling for personal reactions to other environmental co-exposures. We assessed wind turbine exposures in 454 residences as the distance to the closest wind turbine (Dw) and number of wind turbines turbines and agricultural odor exposure, we did not observe a significant relationship between residential proximity to wind turbines and symptoms and the parameter estimates were attenuated toward zero. Wind turbines-health associations can be confounded by personal reactions to other environmental co-exposures. Isolated associations reported in the literature may be due to confounding bias. Copyright © 2016 Elsevier Inc. All rights reserved.

Permutation importance: a corrected feature importance measure.

Science.gov (United States)

Altmann, André; Toloşi, Laura; Sander, Oliver; Lengauer, Thomas

2010-05-15

In life sciences, interpretability of machine learning models is as important as their prediction accuracy. Linear models are probably the most frequently used methods for assessing feature relevance, despite their relative inflexibility. However, in the past years effective estimators of feature relevance have been derived for highly complex or non-parametric models such as support vector machines and RandomForest (RF) models. Recently, it has been observed that RF models are biased in such a way that categorical variables with a large number of categories are preferred. In this work, we introduce a heuristic for normalizing feature importance measures that can correct the feature importance bias. The method is based on repeated permutations of the outcome vector for estimating the distribution of measured importance for each variable in a non-informative setting. The P-value of the observed importance provides a corrected measure of feature importance. We apply our method to simulated data and demonstrate that (i) non-informative predictors do not receive significant P-values, (ii) informative variables can successfully be recovered among non-informative variables and (iii) P-values computed with permutation importance (PIMP) are very helpful for deciding the significance of variables, and therefore improve model interpretability. Furthermore, PIMP was used to correct RF-based importance measures for two real-world case studies. We propose an improved RF model that uses the significant variables with respect to the PIMP measure and show that its prediction accuracy is superior to that of other existing models. R code for the method presented in this article is available at http://www.mpi-inf.mpg.de/ approximately altmann/download/PIMP.R CONTACT: altmann@mpi-inf.mpg.de, laura.tolosi@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online.

Influence of potentially confounding factors on sea urchin porewater toxicity tests

Science.gov (United States)

Carr, R.S.; Biedenbach, J.M.; Nipper, M.

2006-01-01

The influence of potentially confounding factors has been identified as a concern for interpreting sea urchin porewater toxicity test data. The results from >40 sediment-quality assessment surveys using early-life stages of the sea urchin Arbacia punctulata were compiled and examined to determine acceptable ranges of natural variables such as pH, ammonia, and dissolved organic carbon on the fertilization and embryological development endpoints. In addition, laboratory experiments were also conducted with A. punctulata and compared with information from the literature. Pore water with pH as low as 6.9 is an unlikely contributor to toxicity for the fertilization and embryological development tests with A. punctulata. Other species of sea urchin have narrower pH tolerance ranges. Ammonia is rarely a contributing factor in pore water toxicity tests using the fertilization endpoint, but the embryological development endpoint may be influenced by ammonia concentrations commonly found in porewater samples. Therefore, ammonia needs to be considered when interpreting results for the embryological development test. Humic acid does not affect sea urchin fertilization at saturation concentrations, but it could have an effect on the embryological development endpoint at near-saturation concentrations. There was no correlation between sediment total organic carbon concentrations and porewater dissolved organic carbon concentrations. Because of the potential for many varying substances to activate parthenogenesis in sea urchin eggs, it is recommended that a no-sperm control be included with every fertilization test treatment. ?? 2006 Springer Science+Business Media, Inc.

A comparison of Bayesian and Monte Carlo sensitivity analysis for unmeasured confounding.

Science.gov (United States)

McCandless, Lawrence C; Gustafson, Paul

2017-08-15

Bias from unmeasured confounding is a persistent concern in observational studies, and sensitivity analysis has been proposed as a solution. In the recent years, probabilistic sensitivity analysis using either Monte Carlo sensitivity analysis (MCSA) or Bayesian sensitivity analysis (BSA) has emerged as a practical analytic strategy when there are multiple bias parameters inputs. BSA uses Bayes theorem to formally combine evidence from the prior distribution and the data. In contrast, MCSA samples bias parameters directly from the prior distribution. Intuitively, one would think that BSA and MCSA ought to give similar results. Both methods use similar models and the same (prior) probability distributions for the bias parameters. In this paper, we illustrate the surprising finding that BSA and MCSA can give very different results. Specifically, we demonstrate that MCSA can give inaccurate uncertainty assessments (e.g. 95% intervals) that do not reflect the data's influence on uncertainty about unmeasured confounding. Using a data example from epidemiology and simulation studies, we show that certain combinations of data and prior distributions can result in dramatic prior-to-posterior changes in uncertainty about the bias parameters. This occurs because the application of Bayes theorem in a non-identifiable model can sometimes rule out certain patterns of unmeasured confounding that are not compatible with the data. Consequently, the MCSA approach may give 95% intervals that are either too wide or too narrow and that do not have 95% frequentist coverage probability. Based on our findings, we recommend that analysts use BSA for probabilistic sensitivity analysis. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Predicting Teacher Value-Added Results in Non-Tested Subjects Based on Confounding Variables: A Multinomial Logistic Regression

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Street, Nathan Lee

2017-01-01

Teacher value-added measures (VAM) are designed to provide information regarding teachers' causal impact on the academic growth of students while controlling for exogenous variables. While some researchers contend VAMs successfully and authentically measure teacher causality on learning, others suggest VAMs cannot adequately control for exogenous…

Control selection and confounding factors: A lesson from a Japanese case-control study to examine acellular pertussis vaccine effectiveness.

Science.gov (United States)

Ohfuji, Satoko; Okada, Kenji; Nakano, Takashi; Ito, Hiroaki; Hara, Megumi; Kuroki, Haruo; Hirota, Yoshio

2017-08-24

When using a case-control study design to examine vaccine effectiveness, both the selection of control subjects and the consideration of potential confounders must be the important issues to ensure accurate results. In this report, we described our experience from a case-control study conducted to evaluate the effectiveness of acellular pertussis vaccine combined with diphtheria-tetanus toxoids (DTaP vaccine). Newly diagnosed pertussis cases and age- and sex-matched friend-controls were enrolled, and the history of DTaP vaccination was compared between groups. Logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) of vaccination for development of pertussis. After adjustment for potential confounders, four doses of DTaP vaccination showed a lower OR for pediatrician-diagnosed pertussis (OR=0.11, 95% CI, 0.01-0.99). In addition, the decreasing OR of four doses vaccination was more pronounced for laboratory-confirmed pertussis (OR=0.07, 95%CI, 0.01-0.82). Besides, positive association with pertussis was observed in subjects with a history of steroid treatment (OR=5.67) and those with a recent contact with a lasting cough (OR=4.12). When using a case-control study to evaluate the effectiveness of vaccines, particularly those for uncommon infectious diseases such as pertussis, the use of friend-controls may be optimal due to the fact that they shared a similar experience for exposure to the pathogen as the cases. In addition, to assess vaccine effectiveness as accurately as possible, the effects of confounding should be adequately controlled with a matching or analysis technique. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

An education gradient in health, a health gradient in education, or a confounded gradient in both?

Science.gov (United States)

Lynch, Jamie L; von Hippel, Paul T

2016-04-01

There is a positive gradient associating educational attainment with health, yet the explanation for this gradient is not clear. Does higher education improve health (causation)? Do the healthy become highly educated (selection)? Or do good health and high educational attainment both result from advantages established early in the life course (confounding)? This study evaluates these competing explanations by tracking changes in educational attainment and Self-rated Health (SRH) from age 15 to age 31 in the National Longitudinal Study of Youth, 1997 cohort. Ordinal logistic regression confirms that high-SRH adolescents are more likely to become highly educated. This is partly because adolescent SRH is associated with early advantages including adolescents' academic performance, college plans, and family background (confounding); however, net of these confounders adolescent SRH still predicts adult educational attainment (selection). Fixed-effects longitudinal regression shows that educational attainment has little causal effect on SRH at age 31. Completion of a high school diploma or associate's degree has no effect on SRH, while completion of a bachelor's or graduate degree have effects that, though significant, are quite small (less than 0.1 points on a 5-point scale). While it is possible that educational attainment would have greater effect on health at older ages, at age 31 what we see is a health gradient in education, shaped primarily by selection and confounding rather than by a causal effect of education on health. Copyright © 2016 Elsevier Ltd. All rights reserved.

Observing Two Important Teaching Variables.

Science.gov (United States)

Gustafson, John A.

1986-01-01

Two behaviors essential to good teaching, teacher expectation and teacher flexibility, have been incorporated into the observation system used in the student teacher program at the University of New Mexico. The importance of these behaviors in teaching and in evaluating student teachers is discussed. (MT)

Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

DEFF Research Database (Denmark)

Jackson, D.; White, I.; Kostis, J.B.

2009-01-01

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an...

Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

NARCIS (Netherlands)

Jackson, D.; White, I.; Kostis, J.B.; Wilson, A.C.; Folsom, A.R.; Feskens, E.J.M.

2009-01-01

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an

Parasitism can be a confounding factor in assessing the response of zebra mussels to water contamination

International Nuclear Information System (INIS)

Minguez, Laëtitia; Buronfosse, Thierry; Beisel, Jean-Nicolas; Giambérini, Laure

2012-01-01

Biological responses measured in aquatic organisms to monitor environmental pollution could be also affected by different biotic and abiotic factors. Among these environmental factors, parasitism has often been neglected even if infection by parasites is very frequent. In the present field investigation, the parasite infra-communities and zebra mussel biological responses were studied up- and downstream a waste water treatment plant in northeast France. In both sites, mussels were infected by ciliates and/or intracellular bacteria, but prevalence rates and infection intensities were different according to the habitat. Concerning the biological responses differences were observed related to the site quality and the infection status. Parasitism affects both systems but seemed to depend mainly on environmental conditions. The influence of parasites is not constant, but remains important to consider it as a potential confounding factor in ecotoxicological studies. This study also emphasizes the interesting use of integrative indexes to synthesize data set. Highlights: ► Study of potential bias associated with the use of infected zebra mussels in ecotoxicological studies. ► Presence of infected mussels on banks and channels, up- and downstream a waste water treatment plant. ► Parasitism influence on biological responses dependent of mussel population history. ► Integrative index, an interesting tool to synthesize the set of biological data. - Parasitism influence on the host physiology would be strongly dependent on environmental conditions but remains a potential confounding factor in ecotoxicological studies.

Marital well-being and depression in Chinese marriage: Going beyond satisfaction and ruling out critical confounders.

Science.gov (United States)

Cao, Hongjian; Zhou, Nan; Fang, Xiaoyi; Fine, Mark

2017-09-01

Based on data obtained from 203 Chinese couples during the early years of marriage and utilizing the actor-partner interdependence model, this study examined the prospective associations between different aspects of marital well-being (i.e., marital satisfaction, instability, commitment, and closeness) and depressive symptoms (assessed 2 years later) while controlling for critical intrapersonal (i.e., neuroticism and self-esteem) and contextual (i.e., stressful life events) confounders. Results indicated that (a) when considering different aspects of marital well-being as predictors of depressive symptoms separately, each aspect was significantly associated with spouses' own subsequent depressive symptoms; (b) when examining various aspects of marital well-being simultaneously, only husbands' commitment, husbands' instability, and wives' instability were significantly associated with their own subsequent depressive symptoms above and beyond the other aspects; and (c) the associations between husbands' commitment, husbands' instability, and wives' instability and their own subsequent depressive symptoms remained significant even after controlling for potential major intrapersonal and contextual confounders. Such findings (a) provide evidence that the marital discord model of depression may apply to Chinese couples, (b) highlight the importance of going beyond marital (dis)satisfaction when examining the association between marital well-being and depression, and (c) demonstrate that marital well-being can account for unique variance in depressive symptoms above and beyond an array of intrapersonal and contextual risk factors. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Influence of management history and landscape variables on soil organic carbon and soil redistribution

Science.gov (United States)

Venteris, E.R.; McCarty, G.W.; Ritchie, J.C.; Gish, T.

2004-01-01

Controlled studies to investigate the interaction between crop growth, soil properties, hydrology, and management practices are common in agronomy. These sites (much as with real world farmland) often have complex management histories and topographic variability that must be considered. In 1993 an interdisiplinary study was started for a 20-ha site in Beltsville, MD. Soil cores (271) were collected in 1999 in a 30-m grid (with 5-m nesting) and analyzed as part of the site characterization. Soil organic carbon (SOC) and 137Cesium (137Cs) were measured. Analysis of aerial photography from 1992 and of farm management records revealed that part of the site had been maintained as a swine pasture and the other portion as cropped land. Soil properties, particularly soil redistribution and SOC, show large differences in mean values between the two areas. Mass C is 0.8 kg m -2 greater in the pasture area than in the cropped portion. The pasture area is primarily a deposition site, whereas the crop area is dominated by erosion. Management influence is suggested, but topographic variability confounds interpretation. Soil organic carbon is spatially structured, with a regionalized variable of 120 m. 137Cs activity lacks spatial structure, suggesting disturbance of the profile by animal activity and past structures such as swine shelters and roads. Neither SOC nor 137Cs were strongly correlated to terrain parameters, crop yields, or a seasonal soil moisture index predicted from crop yields. SOC and 137Cs were weakly correlated (r2 ???0.2, F-test P-value 0.001), suggesting that soil transport controls, in part, SOC distribution. The study illustrates the importance of past site history when interpreting the landscape distribution of soil properties, especially those strongly influenced by human activity. Confounding variables, complex soil hydrology, and incomplete documentation of land use history make definitive interpretations of the processes behind the spatial distributions

Syphilis may be a confounding factor, not a causative agent, in syphilitic ALS.

Science.gov (United States)

Tuk, Bert

2016-01-01

Based upon a review of published clinical observations regarding syphilitic amyotrophic lateral sclerosis (ALS), I hypothesize that syphilis is actually a confounding factor, not a causative factor, in syphilitic ALS. Moreover, I propose that the successful treatment of ALS symptoms in patients with syphilitic ALS using penicillin G and hydrocortisone is an indirect consequence of the treatment regimen and is not due to the treatment of syphilis. Specifically, I propose that the observed effect is due to the various pharmacological activities of penicillin G ( e.g ., a GABA receptor antagonist) and/or the multifaceted pharmacological activity of hydrocortisone. The notion that syphilis may be a confounding factor in syphilitic ALS is highly relevant, as it suggests that treating ALS patients with penicillin G and hydrocortisone-regardless of whether they present with syphilitic ALS or non-syphilitic ALS-may be effective at treating this rapidly progressive, highly devastating disease.

Enhancing the estimation of blood pressure using pulse arrival time and two confounding factors

International Nuclear Information System (INIS)

Baek, Hyun Jae; Kim, Ko Keun; Kim, Jung Soo; Lee, Boreom; Park, Kwang Suk

2010-01-01

A new method of blood pressure (BP) estimation using multiple regression with pulse arrival time (PAT) and two confounding factors was evaluated in clinical and unconstrained monitoring situations. For the first analysis with clinical data, electrocardiogram (ECG), photoplethysmogram (PPG) and invasive BP signals were obtained by a conventional patient monitoring device during surgery. In the second analysis, ECG, PPG and non-invasive BP were measured using systems developed to obtain data under conditions in which the subject was not constrained. To enhance the performance of BP estimation methods, heart rate (HR) and arterial stiffness were considered as confounding factors in regression analysis. The PAT and HR were easily extracted from ECG and PPG signals. For arterial stiffness, the duration from the maximum derivative point to the maximum of the dicrotic notch in the PPG signal, a parameter called TDB, was employed. In two experiments that normally cause BP variation, the correlation between measured BP and the estimated BP was investigated. Multiple-regression analysis with the two confounding factors improved correlation coefficients for diastolic blood pressure and systolic blood pressure to acceptable confidence levels, compared to existing methods that consider PAT only. In addition, reproducibility for the proposed method was determined using constructed test sets. Our results demonstrate that non-invasive, non-intrusive BP estimation can be obtained using methods that can be applied in both clinical and daily healthcare situations

Enhancing the estimation of blood pressure using pulse arrival time and two confounding factors.

Science.gov (United States)

Baek, Hyun Jae; Kim, Ko Keun; Kim, Jung Soo; Lee, Boreom; Park, Kwang Suk

2010-02-01

A new method of blood pressure (BP) estimation using multiple regression with pulse arrival time (PAT) and two confounding factors was evaluated in clinical and unconstrained monitoring situations. For the first analysis with clinical data, electrocardiogram (ECG), photoplethysmogram (PPG) and invasive BP signals were obtained by a conventional patient monitoring device during surgery. In the second analysis, ECG, PPG and non-invasive BP were measured using systems developed to obtain data under conditions in which the subject was not constrained. To enhance the performance of BP estimation methods, heart rate (HR) and arterial stiffness were considered as confounding factors in regression analysis. The PAT and HR were easily extracted from ECG and PPG signals. For arterial stiffness, the duration from the maximum derivative point to the maximum of the dicrotic notch in the PPG signal, a parameter called TDB, was employed. In two experiments that normally cause BP variation, the correlation between measured BP and the estimated BP was investigated. Multiple-regression analysis with the two confounding factors improved correlation coefficients for diastolic blood pressure and systolic blood pressure to acceptable confidence levels, compared to existing methods that consider PAT only. In addition, reproducibility for the proposed method was determined using constructed test sets. Our results demonstrate that non-invasive, non-intrusive BP estimation can be obtained using methods that can be applied in both clinical and daily healthcare situations.

Heterogeneity in white blood cells has potential to confound DNA methylation measurements.

Directory of Open Access Journals (Sweden)

Bjorn T Adalsteinsson

Full Text Available Epigenetic studies are commonly conducted on DNA from tissue samples. However, tissues are ensembles of cells that may each have their own epigenetic profile, and therefore inter-individual cellular heterogeneity may compromise these studies. Here, we explore the potential for such confounding on DNA methylation measurement outcomes when using DNA from whole blood. DNA methylation was measured using pyrosequencing-based methodology in whole blood (n = 50-179 and in two white blood cell fractions (n = 20, isolated using density gradient centrifugation, in four CGIs (CpG Islands located in genes HHEX (10 CpG sites assayed, KCNJ11 (8 CpGs, KCNQ1 (4 CpGs and PM20D1 (7 CpGs. Cellular heterogeneity (variation in proportional white blood cell counts of neutrophils, lymphocytes, monocytes, eosinophils and basophils, counted by an automated cell counter explained up to 40% (p<0.0001 of the inter-individual variation in whole blood DNA methylation levels in the HHEX CGI, but not a significant proportion of the variation in the other three CGIs tested. DNA methylation levels in the two cell fractions, polymorphonuclear and mononuclear cells, differed significantly in the HHEX CGI; specifically the average absolute difference ranged between 3.4-15.7 percentage points per CpG site. In the other three CGIs tested, methylation levels in the two fractions did not differ significantly, and/or the difference was more moderate. In the examined CGIs, methylation levels were highly correlated between cell fractions. In summary, our analysis detects region-specific differential DNA methylation between white blood cell subtypes, which can confound the outcome of whole blood DNA methylation measurements. Finally, by demonstrating the high correlation between methylation levels in cell fractions, our results suggest a possibility to use a proportional number of a single white blood cell type to correct for this confounding effect in analyses.

Confounding environmental colour and distribution shape leads to underestimation of population extinction risk.

Science.gov (United States)

Fowler, Mike S; Ruokolainen, Lasse

2013-01-01

The colour of environmental variability influences the size of population fluctuations when filtered through density dependent dynamics, driving extinction risk through dynamical resonance. Slow fluctuations (low frequencies) dominate in red environments, rapid fluctuations (high frequencies) in blue environments and white environments are purely random (no frequencies dominate). Two methods are commonly employed to generate the coloured spatial and/or temporal stochastic (environmental) series used in combination with population (dynamical feedback) models: autoregressive [AR(1)] and sinusoidal (1/f) models. We show that changing environmental colour from white to red with 1/f models, and from white to red or blue with AR(1) models, generates coloured environmental series that are not normally distributed at finite time-scales, potentially confounding comparison with normally distributed white noise models. Increasing variability of sample Skewness and Kurtosis and decreasing mean Kurtosis of these series alter the frequency distribution shape of the realised values of the coloured stochastic processes. These changes in distribution shape alter patterns in the probability of single and series of extreme conditions. We show that the reduced extinction risk for undercompensating (slow growing) populations in red environments previously predicted with traditional 1/f methods is an artefact of changes in the distribution shapes of the environmental series. This is demonstrated by comparison with coloured series controlled to be normally distributed using spectral mimicry. Changes in the distribution shape that arise using traditional methods lead to underestimation of extinction risk in normally distributed, red 1/f environments. AR(1) methods also underestimate extinction risks in traditionally generated red environments. This work synthesises previous results and provides further insight into the processes driving extinction risk in model populations. We must let

Is the association between general cognitive ability and violent crime caused by family-level confounders?

Directory of Open Access Journals (Sweden)

Thomas Frisell

Full Text Available BACKGROUND: Research has consistently found lower cognitive ability to be related to increased risk for violent and other antisocial behaviour. Since this association has remained when adjusting for childhood socioeconomic position, ethnicity, and parental characteristics, it is often assumed to be causal, potentially mediated through school adjustment problems and conduct disorder. Socioeconomic differences are notoriously difficult to quantify, however, and it is possible that the association between intelligence and delinquency suffer substantial residual confounding. METHODS: We linked longitudinal Swedish total population registers to study the association of general cognitive ability (intelligence at age 18 (the Conscript Register, 1980-1993 with the incidence proportion of violent criminal convictions (the Crime Register, 1973-2009, among all men born in Sweden 1961-1975 (N = 700,514. Using probit regression, we controlled for measured childhood socioeconomic variables, and further employed sibling comparisons (family pedigree data from the Multi-Generation Register to adjust for shared familial characteristics. RESULTS: Cognitive ability in early adulthood was inversely associated to having been convicted of a violent crime (β = -0.19, 95% CI: -0.19; -0.18, the association remained when adjusting for childhood socioeconomic factors (β = -0.18, 95% CI: -0.18; -0.17. The association was somewhat lower within half-brothers raised apart (β = -0.16, 95% CI: -0.18; -0.14, within half-brothers raised together (β = -0.13, 95% CI: (-0.15; -0.11, and lower still in full-brother pairs (β = -0.10, 95% CI: -0.11; -0.09. The attenuation among half-brothers raised together and full brothers was too strong to be attributed solely to attenuation from measurement error. DISCUSSION: Our results suggest that the association between general cognitive ability and violent criminality is confounded partly by factors shared by

The obesity paradox in stable chronic heart failure does not persist after matching for indicators of disease severity and confounders.

Science.gov (United States)

Frankenstein, Lutz; Zugck, Christian; Nelles, Manfred; Schellberg, Dieter; Katus, Hugo A; Remppis, B Andrew

2009-12-01

To verify whether controlling for indicators of disease severity and confounders represents a solution to the obesity paradox in chronic heart failure (CHF). From a cohort of 1790 patients, we formed 230 nested matched triplets by individually matching patients with body mass index (BMI) > 30 kg/m(2) (Group 3), BMI 20-24.9 k/m(2) (Group 1) and BMI 25-29.9 kg/m(2) (Group 2), according to NT-proBNP, age, sex, and NYHA class (triplet = one matched patient from each group). Although in the pre-matching cohort, BMI group was a significant univariable prognostic indicator, it did not retain significance [heart rate (HR): 0.91, 95% CI: 0.78-1.05, chi(2): 1.67] when controlled for group propensities as covariates. Furthermore, in the matched cohort, 1-year mortality and 3-year mortality did not differ significantly. Here, BMI again failed to reach statistical significance for prognosis, either as a continuous or categorical variable, whether crude or adjusted. This result was confirmed in the patients not selected for matching. NT-proBNP, however, remained statistically significant (log(NT-proBNP): HR: 1.49, 95% CI: 1.13-1.97, chi(2): 7.82) after multivariable adjustment. The obesity paradox does not appear to persist in a matched setting with respect to indicators of disease severity and other confounders. NT-proBNP remains an independent prognostic indicator of adverse outcome irrespective of obesity status.

Temporal variability in the importance of hydrologic, biotic, and climatic descriptors of dissolved oxygen dynamics in a shallow tidal-marsh creek

Science.gov (United States)

Nelson, N.; Munoz-Carpena, R.; Neale, P.; Tzortziou, M.; Megonigal, P.

2017-12-01

Due to strong abiotic forcing, dissolved oxygen (DO) in shallow tidal creeks often disobeys the conventional explanation of general aquatic DO cycling as biologically-regulated. In the present work, we seek to quantify the relative importance of abiotic (hydrologic and climatic), and biotic (primary productivity as represented by chlorophyll-a) descriptors of tidal creek DO. By fitting multiple linear regression models of DO to hourly chlorophyll-a, water quality, hydrology, and weather data collected in a tidal creek of a Chesapeake Bay marsh (Maryland, USA), temporal shifts (summer - early winter) in the relative importance of tidal creek DO descriptors were uncovered. Moreover, this analysis identified an alternative approach to evaluating tidal stage as a driver of DO by dividing stage into two DO-relevant variables: stage above and below bankfull depth. Within the hydrologic variable class, stage below bankfull depth dominated as an important descriptor, thus highlighting the role of pore water drainage and mixing as influential processes forcing tidal creek DO. Study findings suggest that tidal creek DO dynamics are explained by a balance of hydrologic, climatic, and biotic descriptors during warmer seasons due to many of these variables (i.e., chlorophyll-a, water temperature) acting as tracers of estuarine-marsh water mixing; conversely, in early winter months when estuarine and marsh waters differ less distinctly, hydrologic variables increase in relative importance as descriptors of tidal creek DO. These findings underline important distinctions in the underlying mechanisms dictating DO variability in shallow tidal marsh-creek environments relative to open water estuarine systems.

Everything that you have ever been told about assessment center ratings is confounded.

Science.gov (United States)

Jackson, Duncan J R; Michaelides, George; Dewberry, Chris; Kim, Young-Jae

2016-07-01

Despite a substantial research literature on the influence of dimensions and exercises in assessment centers (ACs), the relative impact of these 2 sources of variance continues to raise uncertainties because of confounding. With confounded effects, it is not possible to establish the degree to which any 1 effect, including those related to exercises and dimensions, influences AC ratings. In the current study (N = 698) we used Bayesian generalizability theory to unconfound all of the possible effects contributing to variance in AC ratings. Our results show that ≤1.11% of the variance in AC ratings was directly attributable to behavioral dimensions, suggesting that dimension-related effects have no practical impact on the reliability of ACs. Even when taking aggregation level into consideration, effects related to general performance and exercises accounted for almost all of the reliable variance in AC ratings. The implications of these findings for recent dimension- and exercise-based perspectives on ACs are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Assessing Mediation Using Marginal Structural Models in the Presence of Confounding and Moderation

Science.gov (United States)

Coffman, Donna L.; Zhong, Wei

2012-01-01

This article presents marginal structural models with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW…

Testing concordance of instrumental variable effects in generalized linear models with application to Mendelian randomization

Science.gov (United States)

Dai, James Y.; Chan, Kwun Chuen Gary; Hsu, Li

2014-01-01

Instrumental variable regression is one way to overcome unmeasured confounding and estimate causal effect in observational studies. Built on structural mean models, there has been considerale work recently developed for consistent estimation of causal relative risk and causal odds ratio. Such models can sometimes suffer from identification issues for weak instruments. This hampered the applicability of Mendelian randomization analysis in genetic epidemiology. When there are multiple genetic variants available as instrumental variables, and causal effect is defined in a generalized linear model in the presence of unmeasured confounders, we propose to test concordance between instrumental variable effects on the intermediate exposure and instrumental variable effects on the disease outcome, as a means to test the causal effect. We show that a class of generalized least squares estimators provide valid and consistent tests of causality. For causal effect of a continuous exposure on a dichotomous outcome in logistic models, the proposed estimators are shown to be asymptotically conservative. When the disease outcome is rare, such estimators are consistent due to the log-linear approximation of the logistic function. Optimality of such estimators relative to the well-known two-stage least squares estimator and the double-logistic structural mean model is further discussed. PMID:24863158

Limitations of the usual blood-pressure hypothesis and importance of variability, instability, and episodic hypertension.

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Rothwell, Peter M

2010-03-13

Although hypertension is the most prevalent treatable vascular risk factor, how it causes end-organ damage and vascular events is poorly understood. Yet, a widespread belief exists that underlying usual blood pressure can alone account for all blood-pressure-related risk of vascular events and for the benefits of antihypertensive drugs, and this notion has come to underpin all major clinical guidelines on diagnosis and treatment of hypertension. Other potentially informative measures, such as variability in clinic blood pressure or maximum blood pressure reached, have been neglected, and effects of antihypertensive drugs on such measures are largely unknown. Clinical guidelines recommend that episodic hypertension is not treated, and the potential risks of residual variability in blood pressure in treated hypertensive patients have been ignored. This Review discusses shortcomings of the usual blood-pressure hypothesis, provides background to accompanying reports on the importance of blood-pressure variability in prediction of risk of vascular events and in accounting for benefits of antihypertensive drugs, and draws attention to clinical implications and directions for future research. Copyright 2010 Elsevier Ltd. All rights reserved.

The Association between Headaches and Temporomandibular Disorders is Confounded by Bruxism and Somatic Complaints

NARCIS (Netherlands)

van der Meer, Hedwig A.; Speksnijder, Caroline M.; Engelbert, Raoul; Lobbezoo, Frank; Nijhuis – van der Sanden, Maria W G; Visscher, Corine M.

OBJECTIVES:: The objective of this observational study was to establish the possible presence of confounders on the association between temporomandibular disorders (TMD) and headaches in a patient population from a TMD and Orofacial Pain Clinic. METHODS:: Several subtypes of headaches were

Compromised Motor Dexterity Confounds Processing Speed Task Outcomes in Stroke Patients

Directory of Open Access Journals (Sweden)

Essie Low

2017-09-01

Full Text Available Most conventional measures of information processing speed require motor responses to facilitate performance. However, although not often addressed clinically, motor impairment, whether due to age or acquired brain injury, would be expected to confound the outcome measure of such tasks. The current study recruited 29 patients (20 stroke and 9 transient ischemic attack with documented reduction in dexterity of the dominant hand, and 29 controls, to investigate the extent to which 3 commonly used processing speed measures with varying motor demands (a Visuo-Motor Reaction Time task, and the Wechsler Adult Intelligence Scale-IV Symbol Search and Coding subtests may be measuring motor-related speed more so than cognitive speed. Analyses include correlations between indices of cognitive and motor speed obtained from two other tasks (Inspection Time and Pegboard task, respectively with the three speed measures, followed by hierarchical regressions to determine the relative contribution of cognitive and motor speed indices toward task performance. Results revealed that speed outcomes on tasks with relatively high motor demands, such as Coding, were largely reflecting motor speed in individuals with reduced dominant hand dexterity. Thus, findings indicate the importance of employing measures with minimal motor requirements, especially when the assessment of speed is aimed at understanding cognitive rather than physical function.

Uncertainty importance measure for models with correlated normal variables

International Nuclear Information System (INIS)

Hao, Wenrui; Lu, Zhenzhou; Wei, Pengfei

2013-01-01

In order to explore the contributions by correlated input variables to the variance of the model output, the contribution decomposition of the correlated input variables based on Mara's definition is investigated in detail. By taking the quadratic polynomial output without cross term as an illustration, the solution of the contribution decomposition is derived analytically using the statistical inference theory. After the correction of the analytical solution is validated by the numerical examples, they are employed to two engineering examples to show their wide application. The derived analytical solutions can directly be used to recognize the contributions by the correlated input variables in case of the quadratic or linear polynomial output without cross term, and the analytical inference method can be extended to the case of higher order polynomial output. Additionally, the origins of the interaction contribution of the correlated inputs are analyzed, and the comparisons of the existing contribution indices are completed, on which the engineer can select the suitable indices to know the necessary information. At last, the degeneration of the correlated inputs to the uncorrelated ones and some computational issues are discussed in concept

Prognostic importance of glycaemic variability on hospital mortality in patients hospitalised in Internal Medicine Departments.

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Sáenz-Abad, D; Gimeno-Orna, J A; Pérez-Calvo, J I

2015-12-01

The objective was to assess the prognostic importance of various glycaemic control measures on hospital mortality. Retrospective, analytical cohort study that included patients hospitalised in internal medicine departments with a diagnosis related to diabetes mellitus (DM), excluding acute decompensations. The clinical endpoint was hospital mortality. We recorded clinical, analytical and glycaemic control-related variables (scheduled insulin administration, plasma glycaemia at admission, HbA1c, mean glycaemia (MG) and in-hospital glycaemic variability and hypoglycaemia). The measurement of hospital mortality predictors was performed using univariate and multivariate logistic regression. A total of 384 patients (50.3% men) were included. The mean age was 78.5 (SD, 10.3) years. The DM-related diagnoses were type 2 diabetes (83.6%) and stress hyperglycaemia (6.8%). Thirty-one (8.1%) patients died while in hospital. In the multivariate analysis, the best model for predicting mortality (R(2)=0.326; P<.0001) consisted, in order of importance, of age (χ(2)=8.19; OR=1.094; 95% CI 1.020-1.174; P=.004), Charlson index (χ(2)=7.28; OR=1.48; 95% CI 1.11-1.99; P=.007), initial glycaemia (χ(2)=6.05; OR=1.007; 95% CI 1.001-1.014; P=.014), HbA1c (χ(2)=5.76; OR=0.59; 95% CI 0.33-1; P=.016), glycaemic variability (χ(2)=4.41; OR=1.031; 95% CI 1-1.062; P=.036), need for corticosteroid treatment (χ(2)=4.03; OR=3.1; 95% CI 1-9.64; P=.045), administration of scheduled insulin (χ(2)=3.98; OR=0.26; 95% CI 0.066-1; P=.046) and systolic blood pressure (χ(2)=2.92; OR=0.985; 95% CI 0.97-1.003; P=.088). An increase in initial glycaemia and in-hospital glycaemic variability predict the risk of mortality for hospitalised patients with DM. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Medicina Interna (SEMI). All rights reserved.

Target gene expression levels and competition between transfected and endogenous microRNAs are strong confounding factors in microRNA high-throughput experiments

Science.gov (United States)

2012-01-01

Background MicroRNA (miRNA) target genes tend to have relatively long and conserved 3' untranslated regions (UTRs), but to what degree these characteristics contribute to miRNA targeting is poorly understood. Different high-throughput experiments have, for example, shown that miRNAs preferentially regulate genes with both short and long 3' UTRs and that target site conservation is both important and irrelevant for miRNA targeting. Results We have analyzed several gene context-dependent features, including 3' UTR length, 3' UTR conservation, and messenger RNA (mRNA) expression levels, reported to have conflicting influence on miRNA regulation. By taking into account confounding factors such as technology-dependent experimental bias and competition between transfected and endogenous miRNAs, we show that two factors - target gene expression and competition - could explain most of the previously reported experimental differences. Moreover, we find that these and other target site-independent features explain about the same amount of variation in target gene expression as the target site-dependent features included in the TargetScan model. Conclusions Our results show that it is important to consider confounding factors when interpreting miRNA high throughput experiments and urge special caution when using microarray data to compare average regulatory effects between groups of genes that have different average gene expression levels. PMID:22325809

Comorbidities, confounders, and the white matter transcriptome in chronic alcoholism.

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Sutherland, Greg T; Sheedy, Donna; Sheahan, Pam J; Kaplan, Warren; Kril, Jillian J

2014-04-01

Alcohol abuse is the world's third leading cause of disease and disability, and one potential sequel of chronic abuse is alcohol-related brain damage (ARBD). This clinically manifests as cognitive dysfunction and pathologically as atrophy of white matter (WM) in particular. The mechanism linking chronic alcohol intoxication with ARBD remains largely unknown but it is also complicated by common comorbidities such as liver damage and nutritional deficiencies. Liver cirrhosis, in particular, often leads to hepatic encephalopathy (HE), a primary glial disease. In a novel transcriptomic study, we targeted the WM only of chronic alcoholics in an attempt to tease apart the pathogenesis of ARBD. Specifically, in alcoholics with and without HE, we explored both the prefrontal and primary motor cortices, 2 regions that experience differential levels of neuronal loss. Our results suggest that HE, along with 2 confounders, gray matter contamination, and low RNA quality are major drivers of gene expression in ARBD. All 3 exceeded the effects of alcohol itself. In particular, low-quality RNA samples were characterized by an up-regulation of translation machinery, while HE was associated with a down-regulation of mitochondrial energy metabolism pathways. The findings in HE alcoholics are consistent with the metabolic acidosis seen in this condition. In contrast non-HE alcoholics had widespread but only subtle changes in gene expression in their WM. Notwithstanding the latter result, this study demonstrates that significant confounders in transcriptomic studies of human postmortem brain tissue can be identified, quantified, and "removed" to reveal disease-specific signals. Copyright © 2014 by the Research Society on Alcoholism.

The Association Between Headaches and Temporomandibular Disorders is Confounded by Bruxism and Somatic Symptoms

NARCIS (Netherlands)

Meer, H.A. van der; Speksnijder, C.M.; Engelbert, R.H.; Lobbezoo, F.; Nijhuis-Van der Sanden, M.W.G.; Visscher, C.M.

2017-01-01

OBJECTIVES: The objective of this observational study was to establish the possible presence of confounders on the association between temporomandibular disorders (TMD) and headaches in a patient population from a TMD and Orofacial Pain Clinic. MATERIALS AND METHODS: Several subtypes of headaches

Instrumental variable methods in comparative safety and effectiveness research.

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Brookhart, M Alan; Rassen, Jeremy A; Schneeweiss, Sebastian

2010-06-01

Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial.

Instrumental variable methods in comparative safety and effectiveness research†

Science.gov (United States)

Brookhart, M. Alan; Rassen, Jeremy A.; Schneeweiss, Sebastian

2010-01-01

Summary Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial. PMID:20354968

Instrumental variables I: instrumental variables exploit natural variation in nonexperimental data to estimate causal relationships.

Science.gov (United States)

Rassen, Jeremy A; Brookhart, M Alan; Glynn, Robert J; Mittleman, Murray A; Schneeweiss, Sebastian

2009-12-01

The gold standard of study design for treatment evaluation is widely acknowledged to be the randomized controlled trial (RCT). Trials allow for the estimation of causal effect by randomly assigning participants either to an intervention or comparison group; through the assumption of "exchangeability" between groups, comparing the outcomes will yield an estimate of causal effect. In the many cases where RCTs are impractical or unethical, instrumental variable (IV) analysis offers a nonexperimental alternative based on many of the same principles. IV analysis relies on finding a naturally varying phenomenon, related to treatment but not to outcome except through the effect of treatment itself, and then using this phenomenon as a proxy for the confounded treatment variable. This article demonstrates how IV analysis arises from an analogous but potentially impossible RCT design, and outlines the assumptions necessary for valid estimation. It gives examples of instruments used in clinical epidemiology and concludes with an outline on estimation of effects.

Association between Anxiety Disorders and Heart Rate Variability in The Netherlands Study of Depression and Anxiety (NESDA)

NARCIS (Netherlands)

Licht, Carmilla M. M.; de Geus, Eco J. C.; van Dyck, Richard; Penninx, Brenda W. J. H.

Objective: To determine whether patients with different types of anxiety disorder (panic disorder, social phobia, generalized anxiety disorder) have higher heart rate and lower heart rate variability compared with healthy controls in a sample that was sufficiently powered to examine the confounding

Importance of Non-invasive Right and Left Ventricular Variables on Exercise Capacity in Patients with Tetralogy of Fallot Hemodynamics.

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Meierhofer, Christian; Tavakkoli, Timon; Kühn, Andreas; Ulm, Kurt; Hager, Alfred; Müller, Jan; Martinoff, Stefan; Ewert, Peter; Stern, Heiko

2017-12-01

Good quality of life correlates with a good exercise capacity in daily life in patients with tetralogy of Fallot (ToF). Patients after correction of ToF usually develop residual defects such as pulmonary regurgitation or stenosis of variable severity. However, the importance of different hemodynamic parameters and their impact on exercise capacity is unclear. We investigated several hemodynamic parameters measured by cardiovascular magnetic resonance (CMR) and echocardiography and evaluated which parameter has the most pronounced effect on maximal exercise capacity determined by cardiopulmonary exercise testing (CPET). 132 patients with ToF-like hemodynamics were tested during routine follow-up with CMR, echocardiography and CPET. Right and left ventricular volume data, ventricular ejection fraction and pulmonary regurgitation were evaluated by CMR. Echocardiographic pressure gradients in the right ventricular outflow tract and through the tricuspid valve were measured. All data were classified and correlated with the results of CPET evaluations of these patients. The analysis was performed using the Random Forest model. In this way, we calculated the importance of the different hemodynamic variables related to the maximal oxygen uptake in CPET (VO 2 %predicted). Right ventricular pressure showed the most important influence on maximal oxygen uptake, whereas pulmonary regurgitation and right ventricular enddiastolic volume were not important hemodynamic variables to predict maximal oxygen uptake in CPET. Maximal exercise capacity was only very weakly influenced by right ventricular enddiastolic volume and not at all by pulmonary regurgitation in patients with ToF. The variable with the most pronounced influence was the right ventricular pressure.

Partial Granger causality--eliminating exogenous inputs and latent variables.

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Guo, Shuixia; Seth, Anil K; Kendrick, Keith M; Zhou, Cong; Feng, Jianfeng

2008-07-15

Attempts to identify causal interactions in multivariable biological time series (e.g., gene data, protein data, physiological data) can be undermined by the confounding influence of environmental (exogenous) inputs. Compounding this problem, we are commonly only able to record a subset of all related variables in a system. These recorded variables are likely to be influenced by unrecorded (latent) variables. To address this problem, we introduce a novel variant of a widely used statistical measure of causality--Granger causality--that is inspired by the definition of partial correlation. Our 'partial Granger causality' measure is extensively tested with toy models, both linear and nonlinear, and is applied to experimental data: in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of sheep. Our results demonstrate that partial Granger causality can reveal the underlying interactions among elements in a network in the presence of exogenous inputs and latent variables in many cases where the existing conditional Granger causality fails.

'Mechanical restraint-confounders, risk, alliance score': testing the clinical validity of a new risk assessment instrument.

Science.gov (United States)

Deichmann Nielsen, Lea; Bech, Per; Hounsgaard, Lise; Alkier Gildberg, Frederik

2017-08-01

Unstructured risk assessment, as well as confounders (underlying reasons for the patient's risk behaviour and alliance), risk behaviour, and parameters of alliance, have been identified as factors that prolong the duration of mechanical restraint among forensic mental health inpatients. To clinically validate a new, structured short-term risk assessment instrument called the Mechanical Restraint-Confounders, Risk, Alliance Score (MR-CRAS), with the intended purpose of supporting the clinicians' observation and assessment of the patient's readiness to be released from mechanical restraint. The content and layout of MR-CRAS and its user manual were evaluated using face validation by forensic mental health clinicians, content validation by an expert panel, and pilot testing within two, closed forensic mental health inpatient units. The three sub-scales (Confounders, Risk, and a parameter of Alliance) showed excellent content validity. The clinical validations also showed that MR-CRAS was perceived and experienced as a comprehensible, relevant, comprehensive, and useable risk assessment instrument. MR-CRAS contains 18 clinically valid items, and the instrument can be used to support the clinical decision-making regarding the possibility of releasing the patient from mechanical restraint. The present three studies have clinically validated a short MR-CRAS scale that is currently being psychometrically tested in a larger study.

The spatial distribution of known predictors of autism spectrum disorders impacts geographic variability in prevalence in central North Carolina

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Hoffman Kate

2012-10-01

Full Text Available Abstract Background The causes of autism spectrum disorders (ASD remain largely unknown and widely debated; however, evidence increasingly points to the importance of environmental exposures. A growing number of studies use geographic variability in ASD prevalence or exposure patterns to investigate the association between environmental factors and ASD. However, differences in the geographic distribution of established risk and predictive factors for ASD, such as maternal education or age, can interfere with investigations of ASD etiology. We evaluated geographic variability in the prevalence of ASD in central North Carolina and the impact of spatial confounding by known risk and predictive factors. Methods Children meeting a standardized case definition for ASD at 8 years of age were identified through records-based surveillance for 8 counties biennially from 2002 to 2008 (n=532. Vital records were used to identify the underlying cohort (15% random sample of children born in the same years as children with an ASD, n=11,034, and to obtain birth addresses. We used generalized additive models (GAMs to estimate the prevalence of ASD across the region by smoothing latitude and longitude. GAMs, unlike methods used in previous spatial analyses of ASD, allow for extensive adjustment of individual-level risk factors (e.g. maternal age and education when evaluating spatial variability of disease prevalence. Results Unadjusted maps revealed geographic variation in surveillance-recognized ASD. Children born in certain regions of the study area were up to 1.27 times as likely to be recognized as having ASD compared to children born in the study area as a whole (prevalence ratio (PR range across the study area 0.57-1.27; global P=0.003. However, geographic gradients of ASD prevalence were attenuated after adjusting for spatial confounders (adjusted PR range 0.72-1.12 across the study area; global P=0.052. Conclusions In these data, spatial variation of ASD

Interpersonal discrimination and depressive symptomatology: examination of several personality-related characteristics as potential confounders in a racial/ethnic heterogeneous adult sample

Science.gov (United States)

2013-01-01

Background Research suggests that reports of interpersonal discrimination result in poor mental health. Because personality characteristics may either confound or mediate the link between these reports and mental health, there is a need to disentangle its role in order to better understand the nature of discrimination-mental health association. We examined whether hostility, anger repression and expression, pessimism, optimism, and self-esteem served as confounders in the association between perceived interpersonal discrimination and CESD-based depressive symptoms in a race/ethnic heterogeneous probability-based sample of community-dwelling adults. Methods We employed a series of ordinary least squares regression analyses to examine the potential confounding effect of hostility, anger repression and expression, pessimism, optimism, and self-esteem between interpersonal discrimination and depressive symptoms. Results Hostility, anger repression, pessimism and self-esteem were significant as possible confounders of the relationship between interpersonal discrimination and depressive symptoms, together accounting for approximately 38% of the total association (beta: 0.1892, p interpersonal discrimination remained a positive predictor of depressive symptoms (beta: 0.1176, p personality characteristics in the association between reports of interpersonal discrimination and mental health, our results suggest that personality-related characteristics may serve as potential confounders. Nevertheless, our results also suggest that, net of these characteristics, reports of interpersonal discrimination are associated with poor mental health. PMID:24256578

Medical versus surgical abortion: comparing satisfaction and potential confounders in a partly randomized study

DEFF Research Database (Denmark)

Rørbye, Christina; Nørgaard, Mogens; Nilas, Lisbeth

2005-01-01

BACKGROUND: The aim of the study was to compare satisfaction with medical and surgical abortion and to identify potential confounders affecting satisfaction. METHODS: 1033 women with gestational age (GA) < or = 63 days had either a medical (600 mg mifepristone followed by 1 mg gemeprost) or a sur...

Measurement error, time lag, unmeasured confounding: Considerations for longitudinal estimation of the effect of a mediator in randomised clinical trials.

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Goldsmith, K A; Chalder, T; White, P D; Sharpe, M; Pickles, A

2018-06-01

Clinical trials are expensive and time-consuming and so should also be used to study how treatments work, allowing for the evaluation of theoretical treatment models and refinement and improvement of treatments. These treatment processes can be studied using mediation analysis. Randomised treatment makes some of the assumptions of mediation models plausible, but the mediator-outcome relationship could remain subject to bias. In addition, mediation is assumed to be a temporally ordered longitudinal process, but estimation in most mediation studies to date has been cross-sectional and unable to explore this assumption. This study used longitudinal structural equation modelling of mediator and outcome measurements from the PACE trial of rehabilitative treatments for chronic fatigue syndrome (ISRCTN 54285094) to address these issues. In particular, autoregressive and simplex models were used to study measurement error in the mediator, different time lags in the mediator-outcome relationship, unmeasured confounding of the mediator and outcome, and the assumption of a constant mediator-outcome relationship over time. Results showed that allowing for measurement error and unmeasured confounding were important. Contemporaneous rather than lagged mediator-outcome effects were more consistent with the data, possibly due to the wide spacing of measurements. Assuming a constant mediator-outcome relationship over time increased precision.

Confounding environmental colour and distribution shape leads to underestimation of population extinction risk.

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Mike S Fowler

Full Text Available The colour of environmental variability influences the size of population fluctuations when filtered through density dependent dynamics, driving extinction risk through dynamical resonance. Slow fluctuations (low frequencies dominate in red environments, rapid fluctuations (high frequencies in blue environments and white environments are purely random (no frequencies dominate. Two methods are commonly employed to generate the coloured spatial and/or temporal stochastic (environmental series used in combination with population (dynamical feedback models: autoregressive [AR(1] and sinusoidal (1/f models. We show that changing environmental colour from white to red with 1/f models, and from white to red or blue with AR(1 models, generates coloured environmental series that are not normally distributed at finite time-scales, potentially confounding comparison with normally distributed white noise models. Increasing variability of sample Skewness and Kurtosis and decreasing mean Kurtosis of these series alter the frequency distribution shape of the realised values of the coloured stochastic processes. These changes in distribution shape alter patterns in the probability of single and series of extreme conditions. We show that the reduced extinction risk for undercompensating (slow growing populations in red environments previously predicted with traditional 1/f methods is an artefact of changes in the distribution shapes of the environmental series. This is demonstrated by comparison with coloured series controlled to be normally distributed using spectral mimicry. Changes in the distribution shape that arise using traditional methods lead to underestimation of extinction risk in normally distributed, red 1/f environments. AR(1 methods also underestimate extinction risks in traditionally generated red environments. This work synthesises previous results and provides further insight into the processes driving extinction risk in model populations. We

The behaviour of random forest permutation-based variable importance measures under predictor correlation.

Science.gov (United States)

Nicodemus, Kristin K; Malley, James D; Strobl, Carolin; Ziegler, Andreas

2010-02-27

Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observed. Recent works on permutation-based variable importance measures (VIMs) used in RF have come to apparently contradictory conclusions. We present an extended simulation study to synthesize results. In the case when both predictor correlation was present and predictors were associated with the outcome (HA), the unconditional RF VIM attributed a higher share of importance to correlated predictors, while under the null hypothesis that no predictors are associated with the outcome (H0) the unconditional RF VIM was unbiased. Conditional VIMs showed a decrease in VIM values for correlated predictors versus the unconditional VIMs under HA and was unbiased under H0. Scaled VIMs were clearly biased under HA and H0. Unconditional unscaled VIMs are a computationally tractable choice for large datasets and are unbiased under the null hypothesis. Whether the observed increased VIMs for correlated predictors may be considered a "bias" - because they do not directly reflect the coefficients in the generating model - or if it is a beneficial attribute of these VIMs is dependent on the application. For example, in genetic association studies, where correlation between markers may help to localize the functionally relevant variant, the increased importance of correlated predictors may be an advantage. On the other hand, we show examples where this increased importance may result in spurious signals.

Phenotypic variation as an indicator of pesticide stress in gudgeon: Accounting for confounding factors in the wild.

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Shinn, Cândida; Blanchet, Simon; Loot, Géraldine; Lek, Sovan; Grenouillet, Gaël

2015-12-15

The response of organisms to environmental stress is currently used in the assessment of ecosystem health. Morphological changes integrate the multiple effects of one or several stress factors upon the development of the exposed organisms. In a natural environment, many factors determine the patterns of morphological differentiation between individuals. However, few studies have sought to distinguish and measure the independent effect of these factors (genetic diversity and structure, spatial structuring of populations, physical-chemical conditions, etc.). Here we investigated the relationship between pesticide levels measured at 11 sites sampled in rivers of the Garonne river basin (SW France) and morphological changes of a freshwater fish species, the gudgeon (Gobio gobio). Each individual sampled was genotyped using 8 microsatellite markers and their phenotype characterized via 17 morphological traits. Our analysis detected a link between population genetic structure (revealed by a Bayesian method) and morphometry (linear discriminant analysis) of the studied populations. We then developed an original method based on general linear models using distance matrices, an extension of the partial Mantel test beyond 3 matrices. This method was used to test the relationship between contamination (toxicity index) and morphometry (PST of morphometric traits), taking into account (1) genetic differentiation between populations (FST), (2) geographical distances between sites, (3) site catchment area, and (4) various physical-chemical parameters for each sampling site. Upon removal of confounding effects, 3 of the 17 morphological traits studied were significantly correlated with pesticide toxicity, suggesting a response of these traits to the anthropogenic stress. These results underline the importance of taking into account the different sources of phenotypic variability between organisms when identifying the stress factors involved. The separation and quantification of

Importance of the macroeconomic variables for variance prediction: A GARCH-MIDAS approach

DEFF Research Database (Denmark)

Asgharian, Hossein; Hou, Ai Jun; Javed, Farrukh

2013-01-01

This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long-term compone......This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long...

Examining confounding by diet in the association between perfluoroalkyl acids and serum cholesterol in pregnancy

Energy Technology Data Exchange (ETDEWEB)

Skuladottir, Margret; Ramel, Alfons [Faculty of Food Science and Nutrition, University of Iceland, Reykjavik (Iceland); Unit for Nutrition Research, Landspitali National University Hospital, Reykjavik (Iceland); Rytter, Dorte [Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus (Denmark); Haug, Line Småstuen; Sabaredzovic, Azemira [Division of Environmental Medicine, Norwegian Institute of Public Health, Oslo (Norway); Bech, Bodil Hammer [Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus (Denmark); Henriksen, Tine Brink [Pediatric Department, Aarhus University Hospital, Aarhus (Denmark); Olsen, Sjurdur F. [Center for Fetal Programming, Department of Epidemiology Research, Statens Serum Institut, Copenhagen (Denmark); Department of Nutrition, Harvard School of Public Health, Boston, MA (United States); Halldorsson, Thorhallur I., E-mail: tih@hi.is [Faculty of Food Science and Nutrition, University of Iceland, Reykjavik (Iceland); Unit for Nutrition Research, Landspitali National University Hospital, Reykjavik (Iceland); Center for Fetal Programming, Department of Epidemiology Research, Statens Serum Institut, Copenhagen (Denmark)

2015-11-15

Background: Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) have consistently been associated with higher cholesterol levels in cross sectional studies. Concerns have, however, been raised about potential confounding by diet and clinical relevance. Objective: To examine the association between concentrations of PFOS and PFOA and total cholesterol in serum during pregnancy taking into considerations confounding by diet. Methods: 854 Danish women who gave birth in 1988–89 and provided a blood sample and reported their diet in week 30 of gestation. Results: Mean serum PFOS, PFOA and total cholesterol concentrations were 22.3 ng/mL, 4.1 ng/mL and 7.3 mmol/L, respectively. Maternal diet was a significant predictor of serum PFOS and PFOA concentrations. In particular intake of meat and meat products was positively associated while intake of vegetables was inversely associated (P for trend <0.01) with relative difference between the highest and lowest quartile in PFOS and PFOA concentrations ranging between 6% and 25% of mean values. After adjustment for dietary factors both PFOA and PFOS were positively and similarly associated with serum cholesterol (P for trend ≤0.01). For example, the mean increase in serum cholesterol was 0.39 mmol/L (95%CI: 0.09, 0.68) when comparing women in the highest to lowest quintile of PFOA concentrations. In comparison the mean increase in serum cholesterol was 0.61 mmol/L (95%CI: 0.17, 1.05) when comparing women in the highest to lowest quintile of saturated fat intake. Conclusion: In this study associations between PFOS and PFOA with serum cholesterol appeared unrelated to dietary intake and were similar in magnitude as the associations between saturated fat intake and serum cholesterol. - Highlights: • PFOS and PFOA have consistently been linked with raised serum cholesterol • Clinical relevance remains uncertain and confounding by diet has been suggested • The aim of this study was to address these issues in

Examining confounding by diet in the association between perfluoroalkyl acids and serum cholesterol in pregnancy

International Nuclear Information System (INIS)

Skuladottir, Margret; Ramel, Alfons; Rytter, Dorte; Haug, Line Småstuen; Sabaredzovic, Azemira; Bech, Bodil Hammer; Henriksen, Tine Brink; Olsen, Sjurdur F.; Halldorsson, Thorhallur I.

2015-01-01

Background: Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) have consistently been associated with higher cholesterol levels in cross sectional studies. Concerns have, however, been raised about potential confounding by diet and clinical relevance. Objective: To examine the association between concentrations of PFOS and PFOA and total cholesterol in serum during pregnancy taking into considerations confounding by diet. Methods: 854 Danish women who gave birth in 1988–89 and provided a blood sample and reported their diet in week 30 of gestation. Results: Mean serum PFOS, PFOA and total cholesterol concentrations were 22.3 ng/mL, 4.1 ng/mL and 7.3 mmol/L, respectively. Maternal diet was a significant predictor of serum PFOS and PFOA concentrations. In particular intake of meat and meat products was positively associated while intake of vegetables was inversely associated (P for trend <0.01) with relative difference between the highest and lowest quartile in PFOS and PFOA concentrations ranging between 6% and 25% of mean values. After adjustment for dietary factors both PFOA and PFOS were positively and similarly associated with serum cholesterol (P for trend ≤0.01). For example, the mean increase in serum cholesterol was 0.39 mmol/L (95%CI: 0.09, 0.68) when comparing women in the highest to lowest quintile of PFOA concentrations. In comparison the mean increase in serum cholesterol was 0.61 mmol/L (95%CI: 0.17, 1.05) when comparing women in the highest to lowest quintile of saturated fat intake. Conclusion: In this study associations between PFOS and PFOA with serum cholesterol appeared unrelated to dietary intake and were similar in magnitude as the associations between saturated fat intake and serum cholesterol. - Highlights: • PFOS and PFOA have consistently been linked with raised serum cholesterol • Clinical relevance remains uncertain and confounding by diet has been suggested • The aim of this study was to address these issues in

Serial Holter ST-segment monitoring after first acute myocardial infarction. Prevalence, variability, and long-term prognostic importance of transient myocardial ischemia

DEFF Research Database (Denmark)

Mickley, H; Nielsen, J R; Berning, J

1998-01-01

Based on serial Holter monitoring performed 7 times within 3 years after a first acute myocardial infarction, we assessed the prevalence, variability and long-term clinical importance of transient myocardial ischemia (TMI) defined as episodes of ambulatory ST-segment depression. In all, 121...... consecutive male patients variability was found within and between patients...

Clinical and evoked pain, personality traits, and emotional states: can familial confounding explain the associations?

Science.gov (United States)

Strachan, Eric; Poeschla, Brian; Dansie, Elizabeth; Succop, Annemarie; Chopko, Laura; Afari, Niloofar

2015-01-01

Pain is a complex phenomenon influenced by context and person-specific factors. Affective dimensions of pain involve both enduring personality traits and fleeting emotional states. We examined how personality traits and emotional states are linked with clinical and evoked pain in a twin sample. 99 female twin pairs were evaluated for clinical and evoked pain using the McGill Pain Questionnaire (MPQ) and dolorimetry, and completed the 120-item International Personality Item Pool (IPIP), the Positive and Negative Affect Scale (PANAS), and ratings of stress and mood. Using a co-twin control design we examined a) the relationship of personality traits and emotional states with clinical and evoked pain and b) whether genetics and common environment (i.e. familial factors) may account for the associations. Neuroticism was associated with the sensory component of the MPQ; this relationship was not confounded by familial factors. None of the emotional state measures was associated with the MPQ. PANAS negative affect was associated with lower evoked pressure pain threshold and tolerance; these associations were confounded by familial factors. There were no associations between IPIP traits and evoked pain. A relationship exists between neuroticism and clinical pain that is not confounded by familial factors. There is no similar relationship between negative emotional states and clinical pain. In contrast, the relationship between negative emotional states and evoked pain is strong while the relationship with enduring personality traits is weak. The relationship between negative emotional states and evoked pain appears to be non-causal and due to familial factors. Copyright © 2014 Elsevier Inc. All rights reserved.

On the Confounding Effect of Temperature on Chemical Shift-Encoded Fat Quantification

Science.gov (United States)

Hernando, Diego; Sharma, Samir D.; Kramer, Harald; Reeder, Scott B.

2014-01-01

Purpose To characterize the confounding effect of temperature on chemical shift-encoded (CSE) fat quantification. Methods The proton resonance frequency of water, unlike triglycerides, depends on temperature. This leads to a temperature dependence of the spectral models of fat (relative to water) that are commonly used by CSE-MRI methods. Simulation analysis was performed for 1.5 Tesla CSE fat–water signals at various temperatures and echo time combinations. Oil–water phantoms were constructed and scanned at temperatures between 0 and 40°C using spectroscopy and CSE imaging at three echo time combinations. An explanted human liver, rejected for transplantation due to steatosis, was scanned using spectroscopy and CSE imaging. Fat–water reconstructions were performed using four different techniques: magnitude and complex fitting, with standard or temperature-corrected signal modeling. Results In all experiments, magnitude fitting with standard signal modeling resulted in large fat quantification errors. Errors were largest for echo time combinations near TEinit ≈ 1.3 ms, ΔTE ≈ 2.2 ms. Errors in fat quantification caused by temperature-related frequency shifts were smaller with complex fitting, and were avoided using a temperature-corrected signal model. Conclusion Temperature is a confounding factor for fat quantification. If not accounted for, it can result in large errors in fat quantifications in phantom and ex vivo acquisitions. PMID:24123362

Spatial Variability of Geriatric Depression Risk in a High-Density City: A Data-Driven Socio-Environmental Vulnerability Mapping Approach.

Science.gov (United States)

Ho, Hung Chak; Lau, Kevin Ka-Lun; Yu, Ruby; Wang, Dan; Woo, Jean; Kwok, Timothy Chi Yui; Ng, Edward

2017-08-31

Previous studies found a relationship between geriatric depression and social deprivation. However, most studies did not include environmental factors in the statistical models, introducing a bias to estimate geriatric depression risk because the urban environment was found to have significant associations with mental health. We developed a cross-sectional study with a binomial logistic regression to examine the geriatric depression risk of a high-density city based on five social vulnerability factors and four environmental measures. We constructed a socio-environmental vulnerability index by including the significant variables to map the geriatric depression risk in Hong Kong, a high-density city characterized by compact urban environment and high-rise buildings. Crude and adjusted odds ratios (ORs) of the variables were significantly different, indicating that both social and environmental variables should be included as confounding factors. For the comprehensive model controlled by all confounding factors, older adults who were of lower education had the highest geriatric depression risks (OR: 1.60 (1.21, 2.12)). Higher percentage of residential area and greater variation in building height within the neighborhood also contributed to geriatric depression risk in Hong Kong, while average building height had negative association with geriatric depression risk. In addition, the socio-environmental vulnerability index showed that higher scores were associated with higher geriatric depression risk at neighborhood scale. The results of mapping and cross-section model suggested that geriatric depression risk was associated with a compact living environment with low socio-economic conditions in historical urban areas in Hong Kong. In conclusion, our study found a significant difference in geriatric depression risk between unadjusted and adjusted models, suggesting the importance of including environmental factors in estimating geriatric depression risk. We also

A review of instrumental variable estimators for Mendelian randomization.

Science.gov (United States)

Burgess, Stephen; Small, Dylan S; Thompson, Simon G

2017-10-01

Instrumental variable analysis is an approach for obtaining causal inferences on the effect of an exposure (risk factor) on an outcome from observational data. It has gained in popularity over the past decade with the use of genetic variants as instrumental variables, known as Mendelian randomization. An instrumental variable is associated with the exposure, but not associated with any confounder of the exposure-outcome association, nor is there any causal pathway from the instrumental variable to the outcome other than via the exposure. Under the assumption that a single instrumental variable or a set of instrumental variables for the exposure is available, the causal effect of the exposure on the outcome can be estimated. There are several methods available for instrumental variable estimation; we consider the ratio method, two-stage methods, likelihood-based methods, and semi-parametric methods. Techniques for obtaining statistical inferences and confidence intervals are presented. The statistical properties of estimates from these methods are compared, and practical advice is given about choosing a suitable analysis method. In particular, bias and coverage properties of estimators are considered, especially with weak instruments. Settings particularly relevant to Mendelian randomization are prioritized in the paper, notably the scenario of a continuous exposure and a continuous or binary outcome.

phMRI: methodological considerations for mitigating potential confounding factors

Directory of Open Access Journals (Sweden)

Julius H Bourke

2015-05-01

Full Text Available Pharmacological Magnetic Resonance Imaging (phMRI is a variant of conventional MRI that adds pharmacological manipulations in order to study the effects of drugs, or uses pharmacological probes to investigate basic or applied (e.g. clinical neuroscience questions. Issues that may confound the interpretation of results from various types of phMRI studies are briefly discussed, and a set of methodological strategies that can mitigate these problems are described. These include strategies that can be employed at every stage of investigation, from study design to interpretation of resulting data, and additional techniques suited for use with clinical populations are also featured. Pharmacological MRI is a challenging area of research that has both significant advantages and formidable difficulties, however with due consideration and use of these strategies many of the key obstacles can be overcome.

The importance of histopathological and clinical variables in predicting the evolution of colon cancer.

Science.gov (United States)

Diculescu, Mircea; Iacob, Răzvan; Iacob, Speranţa; Croitoru, Adina; Becheanu, Gabriel; Popeneciu, Valentin

2002-09-01

It has been a consensus that prognostic factors should always be taken into account before planning treatment in colorectal cancer. A 5 year prospective study was conducted, in order to assess the importance of several histopathological and clinical prognostic variables in the prediction of evolution in colon cancer. Some of the factors included in the analysis are still subject to dispute by different authors. 46 of 53 screened patients qualified to enter the study and underwent a potentially curative resection of the tumor, followed, when necessary, by adjuvant chemotherapy. Univariate and multivariate analyses were carried out in order to identify independent prognostic indicators. The endpoint of the study was considered the recurrence of the tumor or the detection of metastases. 65.2% of the patients had a good evolution during the follow up period. Multivariate survival analysis performed by Cox proportional hazard model identified 3 independent prognostic factors: Dukes stage (p = 0.00002), the grade of differentiation (p = 0.0009) and the weight loss index, representing the weight loss of the patient divided by the number of months when it was actually lost (p = 0.02). Age under 40 years, sex, microscopic aspect of the tumor, tumor location, anemia degree were not identified by our analysis as having prognostic importance. Histopathological factors continue to be the most valuable source of information regarding the possible evolution of patients with colorectal cancer. Individual clinical symptoms or biological parameters such as erytrocyte sedimentation rate or hemoglobin level are of little or no prognostic value. More research is required relating to the impact of a performance status index (which could include also weight loss index) as another reliable prognostic variable.

Confounding factors in determining causal soil moisture-precipitation feedback

Science.gov (United States)

Tuttle, Samuel E.; Salvucci, Guido D.

2017-07-01

Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data.

Why is variability important for performance assessment and what are its consequences for site characterisation and repository design?

International Nuclear Information System (INIS)

Dverstorp, B.; Smith, P.A.; Zuidema, P.

1998-01-01

The importance of spatial variability is discussed in terms of its consequences for site characterisation and for repository design and safety. Variability is described in terms of various scales of discrete structural features and a pragmatic classification is proposed according to whether the features are: feasibility-determining (i.e. features within which repository construction and operation is not practical and which preclude long-term safety); layout-determining (i.e. features which, if avoided, would enhance long-term safety); safety-determining features (i.e. features which cannot be shown to be avoidable and which strongly influence the calculated long-term safety of the repository system). The significance with respect to the geosphere-transport barrier of small-scale pore structure within the various classes of feature is also discussed. The practical problems of characterising variability and modelling its effects on radionuclide transport are described. Key factors affecting groundwater flow and radionuclide transport are identified, models that incorporate spatial variability are described and the estimation of appropriate parameters for these models is discussed. (author)

Accounting for the Confound of Meninges in Segmenting Entorhinal and Perirhinal Cortices in T1-Weighted MRI.

Science.gov (United States)

Xie, Long; Wisse, Laura E M; Das, Sandhitsu R; Wang, Hongzhi; Wolk, David A; Manjón, Jose V; Yushkevich, Paul A

2016-10-01

Quantification of medial temporal lobe (MTL) cortices, including entorhinal cortex (ERC) and perirhinal cortex (PRC), from in vivo MRI is desirable for studying the human memory system as well as in early diagnosis and monitoring of Alzheimer's disease. However, ERC and PRC are commonly over-segmented in T1-weighted (T1w) MRI because of the adjacent meninges that have similar intensity to gray matter in T1 contrast. This introduces errors in the quantification and could potentially confound imaging studies of ERC/PRC. In this paper, we propose to segment MTL cortices along with the adjacent meninges in T1w MRI using an established multi-atlas segmentation framework together with super-resolution technique. Experimental results comparing the proposed pipeline with existing pipelines support the notion that a large portion of meninges is segmented as gray matter by existing algorithms but not by our algorithm. Cross-validation experiments demonstrate promising segmentation accuracy. Further, agreement between the volume and thickness measures from the proposed pipeline and those from the manual segmentations increase dramatically as a result of accounting for the confound of meninges. Evaluated in the context of group discrimination between patients with amnestic mild cognitive impairment and normal controls, the proposed pipeline generates more biologically plausible results and improves the statistical power in discriminating groups in absolute terms comparing to other techniques using T1w MRI. Although the performance of the proposed pipeline is inferior to that using T2-weighted MRI, which is optimized to image MTL sub-structures, the proposed pipeline could still provide important utilities in analyzing many existing large datasets that only have T1w MRI available.

Interpersonal discrimination and depressive symptomatology: examination of several personality-related characteristics as potential confounders in a racial/ethnic heterogeneous adult sample

OpenAIRE

Hunte, Haslyn ER; King, Katherine; Hicken, Margaret; Lee, Hedwig; Lewis, Ten? T

2013-01-01

Background Research suggests that reports of interpersonal discrimination result in poor mental health. Because personality characteristics may either confound or mediate the link between these reports and mental health, there is a need to disentangle its role in order to better understand the nature of discrimination-mental health association. We examined whether hostility, anger repression and expression, pessimism, optimism, and self-esteem served as confounders in the association between ...

Parametric Study on Important Variables of Aircraft Impact to Prestressed Concrete Containment Vessels

Energy Technology Data Exchange (ETDEWEB)

Shin, Sangshup; Hahm, Daegi; Choi, Inkil [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2013-05-15

In this paper, to find the damage parameter, it is necessary to use many analysis cases and the time reduction. Thus, this paper uses a revised version of Riera's method. Using this method, the response has been found a Prestressed Concrete Containments Vessels (PCCVs) subject to impact loading, and the results of the velocity and mass of the important parameters have been analyzed. To find the response of the PCCVs subjected to aircraft impact load, it is made that a variable forcing functions depending on the velocity and fuel in the paper. The velocity variation affects more than fuel percentage, and we expect that the severe damage of the PCCVs with the same material properties is subject to aircraft impact load (more than 200m/s and 70%)

Effect of water quality and confounding factors on digestive enzyme activities in Gammarus fossarum.

Science.gov (United States)

Charron, L; Geffard, O; Chaumot, A; Coulaud, R; Queau, H; Geffard, A; Dedourge-Geffard, O

2013-12-01

The feeding activity and subsequent assimilation of the products resulting from food digestion allow organisms to obtain energy for growth, maintenance and reproduction. Among these biological parameters, we studied digestive enzymes (amylase, cellulase and trypsin) in Gammarus fossarum to assess the impact of contaminants on their access to energy resources. However, to enable objective assessment of a toxic effect of decreased water quality on an organisms' digestive capacity, it is necessary to establish reference values based on its natural variability as a function of changing biotic and abiotic factors. To limit the confounding influence of biotic factors, a caging approach with calibrated male organisms from the same population was used. This study applied an in situ deployment at 23 sites of the Rhone basin rivers, complemented by a laboratory experiment assessing the influence of two abiotic factors (temperature and conductivity). The results showed a small effect of conductivity on cellulase activity and a significant effect of temperature on digestive enzyme activity but only at the lowest temperature (7 °C). The experimental conditions allowed us to define an environmental reference value for digestive enzyme activities to select sites where the quality of the water impacted the digestive capacity of the organisms. In addition to the feeding rate, this study showed the relevance of digestive enzymes as biomarkers to be used as an early warning tool to reflect organisms' health and the chemical quality of aquatic ecosystems.

Heart period variability and psychopathology in urban boys at risk for delinquency.

Science.gov (United States)

Pine, D S; Wasserman, G A; Miller, L; Coplan, J D; Bagiella, E; Kovelenku, P; Myers, M M; Sloan, R P

1998-09-01

To examine associations between heart period variability (HPV) and psychopathology in young urban boys at risk for delinquency, a series of 697-11-year-old younger brothers of adjudicated delinquents received a standardized psychiatric evaluation and an assessment of heart period variability (HPV). Psychiatric symptoms were rated in two domains: externalizing and internalizing psychopathology. Continuous measures of both externalizing and internalizing psychopathology were associated with reductions in HPV components related to parasympathetic activity. These associations could not be explained by a number of potentially confounding variables, such as age, ethnicity, social class, body size, or family history of hypertension. Although familial hypertension predicted reduced HPV and externalizing psychopathology, associations between externalizing psychopathology and HPV were independent of familial hypertension. Psychiatric symptoms are associated with reduced HPV in young urban boys at risk for delinquency.

Monitoring of airborne biological particles in outdoor atmosphere. Part 1: Importance, variability and ratios.

Science.gov (United States)

Núñez, Andrés; Amo de Paz, Guillermo; Rastrojo, Alberto; García, Ana M; Alcamí, Antonio; Gutiérrez-Bustillo, A Montserrat; Moreno, Diego A

2016-03-01

The first part of this review ("Monitoring of airborne biological particles in outdoor atmosphere. Part 1: Importance, variability and ratios") describes the current knowledge on the major biological particles present in the air regarding their global distribution, concentrations, ratios and influence of meteorological factors in an attempt to provide a framework for monitoring their biodiversity and variability in such a singular environment as the atmosphere. Viruses, bacteria, fungi, pollen and fragments thereof are the most abundant microscopic biological particles in the air outdoors. Some of them can cause allergy and severe diseases in humans, other animals and plants, with the subsequent economic impact. Despite the harsh conditions, they can be found from land and sea surfaces to beyond the troposphere and have been proposed to play a role also in weather conditions and climate change by acting as nucleation particles and inducing water vapour condensation. In regards to their global distribution, marine environments act mostly as a source for bacteria while continents additionally provide fungal and pollen elements. Within terrestrial environments, their abundances and diversity seem to be influenced by the land-use type (rural, urban, coastal) and their particularities. Temporal variability has been observed for all these organisms, mostly triggered by global changes in temperature, relative humidity, et cetera. Local fluctuations in meteorological factors may also result in pronounced changes in the airbiota. Although biological particles can be transported several hundreds of meters from the original source, and even intercontinentally, the time and final distance travelled are strongly influenced by factors such as wind speed and direction. [Int Microbiol 2016; 19(1):1-1 3]. Copyright© by the Spanish Society for Microbiology and Institute for Catalan Studies.

Parasitism can be a confounding factor in assessing the response of zebra mussels to water contamination.

Science.gov (United States)

Minguez, Laëtitia; Buronfosse, Thierry; Beisel, Jean-Nicolas; Giambérini, Laure

2012-03-01

Biological responses measured in aquatic organisms to monitor environmental pollution could be also affected by different biotic and abiotic factors. Among these environmental factors, parasitism has often been neglected even if infection by parasites is very frequent. In the present field investigation, the parasite infra-communities and zebra mussel biological responses were studied up- and downstream a waste water treatment plant in northeast France. In both sites, mussels were infected by ciliates and/or intracellular bacteria, but prevalence rates and infection intensities were different according to the habitat. Concerning the biological responses differences were observed related to the site quality and the infection status. Parasitism affects both systems but seemed to depend mainly on environmental conditions. The influence of parasites is not constant, but remains important to consider it as a potential confounding factor in ecotoxicological studies. This study also emphasizes the interesting use of integrative indexes to synthesize data set. Copyright © 2011 Elsevier Ltd. All rights reserved.

Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles.

Science.gov (United States)

Massol, François; Débarre, Florence

2015-07-01

Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life-cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Evaluation in medical education: A topical review of target parameters, data collection tools and confounding factors

Science.gov (United States)

Schiekirka, Sarah; Feufel, Markus A.; Herrmann-Lingen, Christoph; Raupach, Tobias

2015-01-01

Background and objective: Evaluation is an integral part of education in German medical schools. According to the quality standards set by the German Society for Evaluation, evaluation tools must provide an accurate and fair appraisal of teaching quality. Thus, data collection tools must be highly reliable and valid. This review summarises the current literature on evaluation of medical education with regard to the possible dimensions of teaching quality, the psychometric properties of survey instruments and potential confounding factors. Methods: We searched Pubmed, PsycINFO and PSYNDEX for literature on evaluation in medical education and included studies published up until June 30, 2011 as well as articles identified in the “grey literature”. Results are presented as a narrative review. Results: We identified four dimensions of teaching quality: structure, process, teacher characteristics, and outcome. Student ratings are predominantly used to address the first three dimensions, and a number of reliable tools are available for this purpose. However, potential confounders of student ratings pose a threat to the validity of these instruments. Outcome is usually operationalised in terms of student performance on examinations, but methodological problems may limit the usability of these data for evaluation purposes. In addition, not all examinations at German medical schools meet current quality standards. Conclusion: The choice of tools for evaluating medical education should be guided by the dimension that is targeted by the evaluation. Likewise, evaluation results can only be interpreted within the context of the construct addressed by the data collection tool that was used as well as its specific confounding factors. PMID:26421003

Separating decadal global water cycle variability from sea level rise.

Science.gov (United States)

Hamlington, B D; Reager, J T; Lo, M-H; Karnauskas, K B; Leben, R R

2017-04-20

Under a warming climate, amplification of the water cycle and changes in precipitation patterns over land are expected to occur, subsequently impacting the terrestrial water balance. On global scales, such changes in terrestrial water storage (TWS) will be reflected in the water contained in the ocean and can manifest as global sea level variations. Naturally occurring climate-driven TWS variability can temporarily obscure the long-term trend in sea level rise, in addition to modulating the impacts of sea level rise through natural periodic undulation in regional and global sea level. The internal variability of the global water cycle, therefore, confounds both the detection and attribution of sea level rise. Here, we use a suite of observations to quantify and map the contribution of TWS variability to sea level variability on decadal timescales. In particular, we find that decadal sea level variability centered in the Pacific Ocean is closely tied to low frequency variability of TWS in key areas across the globe. The unambiguous identification and clean separation of this component of variability is the missing step in uncovering the anthropogenic trend in sea level and understanding the potential for low-frequency modulation of future TWS impacts including flooding and drought.

Climate variables explain neutral and adaptive variation within salmonid metapopulations: The importance of replication in landscape genetics

Science.gov (United States)

Hand, Brian K.; Muhlfeld, Clint C.; Wade, Alisa A.; Kovach, Ryan; Whited, Diane C.; Narum, Shawn R.; Matala, Andrew P.; Ackerman, Michael W.; Garner, B. A.; Kimball, John S; Stanford, Jack A.; Luikart, Gordon

2016-01-01

Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

Do time-invariant confounders explain away the association between job stress and workers' mental health? Evidence from Japanese occupational panel data.

Science.gov (United States)

Oshio, Takashi; Tsutsumi, Akizumi; Inoue, Akiomi

2015-02-01

It is well known that job stress is negatively related to workers' mental health, but most recent studies have not controlled for unobserved time-invariant confounders. In the current study, we attempted to validate previous observations on the association between job stress and workers' mental health, by removing the effects of unobserved time-invariant confounders. We used data from three to four waves of an occupational Japanese cohort survey, focusing on 31,382 observations of 9741 individuals who participated in at least two consecutive waves. We estimated mean-centered fixed effects models to explain psychological distress in terms of the Kessler 6 (K6) scores (range: 0-24) by eight job stress indicators related to the job demands-control, effort-reward imbalance, and organizational injustice models. Mean-centered fixed effects models reduced the magnitude of the association between jobs stress and K6 scores to 44.8-54.2% of those observed from pooled ordinary least squares. However, the association remained highly significant even after controlling for unobserved time-invariant confounders for all job stress indicators. In addition, alternatively specified models showed the robustness of the results. In all, we concluded that the validity of major job stress models, which link job stress and workers' mental health, was robust, although unobserved time-invariant confounders led to an overestimation of the association. Copyright © 2014 Elsevier Ltd. All rights reserved.

Combining fixed effects and instrumental variable approaches for estimating the effect of psychosocial job quality on mental health: evidence from 13 waves of a nationally representative cohort study.

Science.gov (United States)

Milner, Allison; Aitken, Zoe; Kavanagh, Anne; LaMontagne, Anthony D; Pega, Frank; Petrie, Dennis

2017-06-23

Previous studies suggest that poor psychosocial job quality is a risk factor for mental health problems, but they use conventional regression analytic methods that cannot rule out reverse causation, unmeasured time-invariant confounding and reporting bias. This study combines two quasi-experimental approaches to improve causal inference by better accounting for these biases: (i) linear fixed effects regression analysis and (ii) linear instrumental variable analysis. We extract 13 annual waves of national cohort data including 13 260 working-age (18-64 years) employees. The exposure variable is self-reported level of psychosocial job quality. The instruments used are two common workplace entitlements. The outcome variable is the Mental Health Inventory (MHI-5). We adjust for measured time-varying confounders. In the fixed effects regression analysis adjusted for time-varying confounders, a 1-point increase in psychosocial job quality is associated with a 1.28-point improvement in mental health on the MHI-5 scale (95% CI: 1.17, 1.40; P variable analysis, a 1-point increase psychosocial job quality is related to 1.62-point improvement on the MHI-5 scale (95% CI: -0.24, 3.48; P = 0.088). Our quasi-experimental results provide evidence to confirm job stressors as risk factors for mental ill health using methods that improve causal inference. © The Author 2017. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Neighbourhood social and built environment factors and falls in community-dwelling canadian older adults: A validation study and exploration of structural confounding

Directory of Open Access Journals (Sweden)

Afshin Vafaei

2016-12-01

Full Text Available Older persons are vulnerable to the ill effects of their social and built environment due to age-related limitations in mobility and bio-psychological vulnerability. Falls are common in older adults and result from complex interactions between individual, social, and contextual determinants. We addressed two methodological issues of neighbourhood-health and social epidemiological studies in this analysis: (1 validity of measures of neighbourhood contexts, and (2 structural confounding resulting from social sorting mechanisms. Baseline data from International Mobility in Aging Study were used. Samples included community-dwelling Canadians older than 65 living in Kingston (Ontario and St-Hyacinthe (Quebec. We performed factor analysis and ecometric analysis to assess the validity of measures of neighbourhood social capital, socioeconomic status, and the built environment and stratified tabular analyses to explore structural confounding. The scales all demonstrated good psychometric and ecometric properties. There was an evidence of the existence of structural confounding in this sample of Canadian older adults as some combinations of strata for the three neighbourhood measures had no population. This limits causal inference in studying relationships between neighbourhood factors and falls and should be taken into account in aetiological aging research. Keywords: Ecometric analysis, Falls, Social and built environment, Neighbourhoods, Older adults, Social Capital, Structural confounding, Validity

Instrumental variable analysis as a complementary analysis in studies of adverse effects : venous thromboembolism and second-generation versus third-generation oral contraceptives

NARCIS (Netherlands)

Boef, Anna G C; Souverein, Patrick C|info:eu-repo/dai/nl/243074948; Vandenbroucke, Jan P; van Hylckama Vlieg, Astrid; de Boer, Anthonius|info:eu-repo/dai/nl/075097346; le Cessie, Saskia; Dekkers, Olaf M

2016-01-01

PURPOSE: A potentially useful role for instrumental variable (IV) analysis may be as a complementary analysis to assess the presence of confounding when studying adverse drug effects. There has been discussion on whether the observed increased risk of venous thromboembolism (VTE) for

Time-Dependent Confounding in the Study of the Effects of Regular Physical Activity in Chronic Obstructive Pulmonary Disease: An Application of the Marginal Structural Model

DEFF Research Database (Denmark)

Garcia-Aymerich, J.; Lange, P.; Serra, I.

2008-01-01

this type of confounding. We sought to assess the presence of time-dependent confounding in the association between physical activity and COPD development and course by comparing risk estimates between standard statistical methods and MSMs. METHODS: By using the population-based cohort Copenhagen City Heart...

Metabolic Syndrome and Importance of Associated Variables in Children and Adolescents in Guabiruba - SC, Brazil

Directory of Open Access Journals (Sweden)

Nilton Rosini

2015-07-01

Full Text Available Background:The risk factors that characterize metabolic syndrome (MetS may be present in childhood and adolescence, increasing the risk of cardiovascular disease in adulthood.Objective:Evaluate the prevalence of MetS and the importance of its associated variables, including insulin resistance (IR, in children and adolescents in the city of Guabiruba-SC, Brazil.Methods:Cross-sectional study with 1011 students (6–14 years, 52.4% girls, 58.5% children. Blood samples were collected for measurement of biochemical parameters by routine laboratory methods. IR was estimated by the HOMA-IR index, and weight, height, waist circumference and blood pressure were determined. Multivariate logistic regression models were used to examine the associations between risk variables and MetS.Results:The prevalence of MetS, IR, overweight and obesity in the cohort were 14%, 8.5%, 21% and 13%, respectively. Among students with MetS, 27% had IR, 33% were overweight, 45.5% were obese and 22% were eutrophic. IR was more common in overweight (48% and obese (41% students when compared with eutrophic individuals (11%; p = 0.034. The variables with greatest influence on the development of MetS were obesity (OR = 32.7, overweight (OR = 6.1, IR (OR = 4.4; p ≤ 0.0001 for all and age (OR = 1.15; p = 0.014.Conclusion:There was a high prevalence of MetS in children and adolescents evaluated in this study. Students who were obese, overweight or insulin resistant had higher chances of developing the syndrome.

Modelling Cardiac Signal as a Confound in EEG-fMRI and its Application in Focal Epilepsy

DEFF Research Database (Denmark)

Liston, Adam David; Salek-Haddadi, Afraim; Hamandi, Khalid

2005-01-01

Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance Imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet...

Negative confounding by essential fatty acids in methylmercury neurotoxicity associations

DEFF Research Database (Denmark)

Choi, Anna L; Mogensen, Ulla Brasch; Bjerve, Kristian S

2014-01-01

acid concentrations in the analysis (-22.0, 95% confidence interval [CI]=-39.4, -4.62). In structural equation models, poorer memory function (corresponding to a lower score in the learning trials and short delay recall in CVLT) was associated with a doubling of prenatal exposure to methylmercury after...... concentrations of fatty acids were determined in cord serum phospholipids. Neuropsychological performance in verbal, motor, attention, spatial, and memory functions was assessed at 7 years of age. Multiple regression and structural equation models (SEMs) were carried out to determine the confounder......-adjusted associations with methylmercury exposure. RESULTS: A short delay recall (in percent change) in the California Verbal Learning Test (CVLT) was associated with a doubling of cord blood methylmercury (-18.9, 95% confidence interval [CI]=-36.3, -1.51). The association became stronger after the inclusion of fatty...

Is the co-occurrence of smoking and poor consumption of fruits and vegetables confounded by socioeconomic conditions?

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Muff, Christine; Dragano, N; Jöckel, K-H; Moebus, S; Möhlenkamp, S; Erbel, R; Mann, K; Siegrist, J

2010-08-01

As smoking and unhealthy diet are more prevalent in lower socioeconomic groups, this study aims at exploring whether associations between smoking and fruit and vegetable consumption are confounded by socioeconomic conditions or if smoking is independently associated with consumption. Cross-sectional analyses of 4,814 middle-aged participants from the Heinz Nixdorf recall study, a population-based cohort study in Germany. Fruit and vegetable consumption was assessed by a food frequency questionnaire. Education and income were used as indicators for socioeconomic groups. Logistic regression models were run to estimate odds ratios for consumption by smoking status. Smoking is associated with poor consumption of fruits and raw vegetables/salad in both genders, and with poor consumption of boiled vegetables and fruit/vegetable juice in men. Importantly, poor consumption is related to smoking independently of people's socioeconomic conditions. The findings imply that smokers in all socioeconomic groups are at higher risk for unhealthy intake of fruits and vegetables. Public health interventions targeted to smokers should include dietary instructions.

College quality and hourly wages: evidence from the self-revelation model, sibling models and instrumental variables.

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Borgen, Nicolai T

2014-11-01

This paper addresses the recent discussion on confounding in the returns to college quality literature using the Norwegian case. The main advantage of studying Norway is the quality of the data. Norwegian administrative data provide information on college applications, family relations and a rich set of control variables for all Norwegian citizens applying to college between 1997 and 2004 (N = 141,319) and their succeeding wages between 2003 and 2010 (676,079 person-year observations). With these data, this paper uses a subset of the models that have rendered mixed findings in the literature in order to investigate to what extent confounding biases the returns to college quality. I compare estimates obtained using standard regression models to estimates obtained using the self-revelation model of Dale and Krueger (2002), a sibling fixed effects model and the instrumental variable model used by Long (2008). Using these methods, I consistently find increasing returns to college quality over the course of students' work careers, with positive returns only later in students' work careers. I conclude that the standard regression estimate provides a reasonable estimate of the returns to college quality. Copyright © 2014 Elsevier Inc. All rights reserved.

Daily commuting to work is not associated with variables of health.

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Mauss, Daniel; Jarczok, Marc N; Fischer, Joachim E

2016-01-01

Commuting to work is thought to have a negative impact on employee health. We tested the association of work commute and different variables of health in German industrial employees. Self-rated variables of an industrial cohort (n = 3805; 78.9 % male) including absenteeism, presenteeism and indices reflecting stress and well-being were assessed by a questionnaire. Fasting blood samples, heart-rate variability and anthropometric data were collected. Commuting was grouped into one of four categories: 0-19.9, 20-44.9, 45-59.9, ≥60 min travelling one way to work. Bivariate associations between commuting and all variables under study were calculated. Linear regression models tested this association further, controlling for potential confounders. Commuting was positively correlated with waist circumference and inversely with triglycerides. These associations did not remain statistically significant in linear regression models controlling for age, gender, marital status, and shiftwork. No other association with variables of physical, psychological, or mental health and well-being could be found. The results indicate that commuting to work has no significant impact on well-being and health of German industrial employees.

Spatial Variability of Geriatric Depression Risk in a High-Density City: A Data-Driven Socio-Environmental Vulnerability Mapping Approach

Directory of Open Access Journals (Sweden)

Hung Chak Ho

2017-08-01

Full Text Available Previous studies found a relationship between geriatric depression and social deprivation. However, most studies did not include environmental factors in the statistical models, introducing a bias to estimate geriatric depression risk because the urban environment was found to have significant associations with mental health. We developed a cross-sectional study with a binomial logistic regression to examine the geriatric depression risk of a high-density city based on five social vulnerability factors and four environmental measures. We constructed a socio-environmental vulnerability index by including the significant variables to map the geriatric depression risk in Hong Kong, a high-density city characterized by compact urban environment and high-rise buildings. Crude and adjusted odds ratios (ORs of the variables were significantly different, indicating that both social and environmental variables should be included as confounding factors. For the comprehensive model controlled by all confounding factors, older adults who were of lower education had the highest geriatric depression risks (OR: 1.60 (1.21, 2.12. Higher percentage of residential area and greater variation in building height within the neighborhood also contributed to geriatric depression risk in Hong Kong, while average building height had negative association with geriatric depression risk. In addition, the socio-environmental vulnerability index showed that higher scores were associated with higher geriatric depression risk at neighborhood scale. The results of mapping and cross-section model suggested that geriatric depression risk was associated with a compact living environment with low socio-economic conditions in historical urban areas in Hong Kong. In conclusion, our study found a significant difference in geriatric depression risk between unadjusted and adjusted models, suggesting the importance of including environmental factors in estimating geriatric depression risk

Phosphate binder use and mortality among hemodialysis patients in the Dialysis Outcomes and Practice Patterns Study (DOPPS): evaluation of possible confounding by nutritional status.

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Lopes, Antonio Alberto; Tong, Lin; Thumma, Jyothi; Li, Yun; Fuller, Douglas S; Morgenstern, Hal; Bommer, Jürgen; Kerr, Peter G; Tentori, Francesca; Akiba, Takashi; Gillespie, Brenda W; Robinson, Bruce M; Port, Friedrich K; Pisoni, Ronald L

2012-07-01

Poor nutritional status and both hyper- and hypophosphatemia are associated with increased mortality in maintenance hemodialysis (HD) patients. We assessed associations of phosphate binder prescription with survival and indicators of nutritional status in maintenance HD patients. Prospective cohort study (DOPPS [Dialysis Outcomes and Practice Patterns Study]), 1996-2008. 23,898 maintenance HD patients at 923 facilities in 12 countries. Patient-level phosphate binder prescription and case-mix-adjusted facility percentage of phosphate binder prescription using an instrumental-variable analysis. All-cause mortality. Overall, 88% of patients were prescribed phosphate binders. Distributions of age, comorbid conditions, and other characteristics showed small differences between facilities with higher and lower percentages of phosphate binder prescription. Patient-level phosphate binder prescription was associated strongly at baseline with indicators of better nutrition, ie, higher values for serum creatinine, albumin, normalized protein catabolic rate, and body mass index and absence of cachectic appearance. Overall, patients prescribed phosphate binders had 25% lower mortality (HR, 0.75; 95% CI, 0.68-0.83) when adjusted for serum phosphorus level and other covariates; further adjustment for nutritional indicators attenuated this association (HR, 0.88; 95% CI, 0.80-0.97). However, this inverse association was observed for only patients with serum phosphorus levels ≥3.5 mg/dL. In the instrumental-variable analysis, case-mix-adjusted facility percentage of phosphate binder prescription (range, 23%-100%) was associated positively with better nutritional status and inversely with mortality (HR for 10% more phosphate binders, 0.93; 95% CI, 0.89-0.96). Further adjustment for nutritional indicators reduced this association to an HR of 0.95 (95% CI, 0.92-0.99). Results were based on phosphate binder prescription; phosphate binder and nutritional data were cross

Importance of fishing as a segmentation variable in the application of a social worlds model

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Gigliotti, Larry M.; Chase, Loren

2017-01-01

Market segmentation is useful to understanding and classifying the diverse range of outdoor recreation experiences sought by different recreationists. Although many different segmentation methodologies exist, many are complex and difficult to measure accurately during in-person intercepts, such as that of creel surveys. To address that gap in the literature, we propose a single-item measure of the importance of fishing as a surrogate to often overly- or needlesslycomplex segmentation techniques. The importance of fishing item is a measure of the value anglers place on the activity or a coarse quantification of how central the activity is to the respondent’s lifestyle (scale: 0 = not important, 1 = slightly, 2 = moderately, 3 = very, and 4 = fishing is my most important recreational activity). We suggest the importance scale may be a proxy measurement for segmenting anglers using the social worlds model as a theoretical framework. Vaske (1980) suggested that commitment to recreational activities may be best understood in relation to social group participation and the social worlds model provides a rich theoretical framework for understanding social group segments. Unruh (1983) identified four types of actor involvement in social worlds: strangers, tourists, regulars, and insiders, differentiated by four characteristics (orientation, experiences, relationships, and commitment). We evaluated the importance of fishing as a segmentation variable using data collected by a mixed-mode survey of South Dakota anglers fishing in 2010. We contend that this straightforward measurement may be useful for segmenting outdoor recreation activities when more complicated segmentation schemes are not suitable. Further, this index, when coupled with the social worlds model, provides a valuable framework for understanding the segments and making management decisions.

Insulin-Like Growth Factor 1 (IGF-1) in Parkinson's Disease: Potential as Trait-, Progression- and Prediction Marker and Confounding Factors

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Binder, Gerhard; Weber, Karin; Apel, Anja; Roeben, Benjamin; Deuschle, Christian; Maechtel, Mirjam; Heger, Tanja; Nussbaum, Susanne; Gasser, Thomas; Maetzler, Walter; Berg, Daniela

2016-01-01

Introduction Biomarkers indicating trait, progression and prediction of pathology and symptoms in Parkinson's disease (PD) often lack specificity or reliability. Investigating biomarker variance between individuals and over time and the effect of confounding factors is essential for the evaluation of biomarkers in PD, such as insulin-like growth factor 1 (IGF-1). Materials and Methods IGF-1 serum levels were investigated in up to 8 biannual visits in 37 PD patients and 22 healthy controls (HC) in the longitudinal MODEP study. IGF-1 baseline levels and annual changes in IGF-1 were compared between PD patients and HC while accounting for baseline disease duration (19 early stage: ≤3.5 years; 18 moderate stage: >4 years), age, sex, body mass index (BMI) and common medical factors putatively modulating IGF-1. In addition, associations of baseline IGF-1 with annual changes of motor, cognitive and depressive symptoms and medication dose were investigated. Results PD patients in moderate (130±26 ng/mL; p = .004), but not early stages (115±19, p>.1), showed significantly increased baseline IGF-1 levels compared with HC (106±24 ng/mL; p = .017). Age had a significant negative correlation with IGF-1 levels in HC (r = -.47, p = .028) and no correlation in PD patients (r = -.06, p>.1). BMI was negatively correlated in the overall group (r = -.28, p = .034). The annual changes in IGF-1 did not differ significantly between groups and were not correlated with disease duration. Baseline IGF-1 levels were not associated with annual changes of clinical parameters. Discussion Elevated IGF-1 in serum might differentiate between patients in moderate PD stages and HC. However, the value of serum IGF-1 as a trait-, progression- and prediction marker in PD is limited as IGF-1 showed large inter- and intraindividual variability and may be modulated by several confounders. PMID:26967642

Determining Confounding Sensitivities In Eddy Current Thin Film Measurements

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Gros, Ethan; Udpa, Lalita; Smith, James A.; Wachs, Katelyn

2016-07-01

Determining Confounding Sensitivities In Eddy Current Thin Film Measurements Ethan Gros, Lalita Udpa, Electrical Engineering, Michigan State University, East Lansing MI 48824 James A. Smith, Experiment Analysis, Idaho National Laboratory, Idaho Falls ID 83415 Eddy current (EC) techniques are widely used in industry to measure the thickness of non-conductive films on a metal substrate. This is done using a system whereby a coil carrying a high-frequency alternating current is used to create an alternating magnetic field at the surface of the instrument's probe. When the probe is brought near a conductive surface, the alternating magnetic field will induce ECs in the conductor. The substrate characteristics and the distance of the probe from the substrate (the coating thickness) affect the magnitude of the ECs. The induced currents load the probe coil affecting the terminal impedance of the coil. The measured probe impedance is related to the lift off between coil and conductor as well as conductivity of the test sample. For a known conductivity sample, the probe impedance can be converted into an equivalent film thickness value. The EC measurement can be confounded by a number of measurement parameters. It is the goal of this research to determine which physical properties of the measurement set-up and sample can adversely affect the thickness measurement. The eddy current testing is performed using a commercially available, hand held eddy current probe (ETA3.3H spring loaded eddy probe running at 8 MHz) that comes with a stand to hold the probe. The stand holds the probe and adjusts the probe on the z-axis to help position the probe in the correct area as well as make precise measurements. The signal from the probe is sent to a hand held readout, where the results are recorded directly in terms of liftoff or film thickness. Understanding the effect of certain factors on the measurements of film thickness, will help to evaluate how accurate the ETA3.3H spring

Assessment of oil content and fatty acid composition variability in two economically important Hibiscus species.

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Wang, Ming Li; Morris, Brad; Tonnis, Brandon; Davis, Jerry; Pederson, Gary A

2012-07-04

The Hibiscus genus encompasses more than 300 species, but kenaf (Hibiscus cannabinus L.) and roselle (Hibiscus sabdariffa L.) are the two most economically important species within the genus. Seeds from these two Hibiscus species contain a relatively high amount of oil with two unusual fatty acids: dihydrosterculic and vernolic acids. The fatty acid composition in the oil can directly affect oil quality and its utilization. However, the variability in oil content and fatty acid composition for these two species is unclear. For these two species, 329 available accessions were acquired from the USDA germplasm collection. Their oil content and fatty acid composition were determined by nuclear magnetic resonance (NMR) and gas chromatography (GC), respectively. Using NMR and GC analyses, we found that Hibiscus seeds on average contained 18% oil and seed oil was composed of six major fatty acids (each >1%) and seven minor fatty acids (each Hibiscus cannabinus seeds contained significantly higher amounts of oil (18.14%), palmitic (20.75%), oleic (28.91%), vernolic acids (VA, 4.16%), and significantly lower amounts of stearic (3.96%), linoleic (39.49%), and dihydrosterculic acids (DHSA, 1.08%) than H. sabdariffa seeds (17.35%, 18.52%, 25.16%, 3.52%, 4.31%, 44.72%, and 1.57%, respectively). For edible oils, a higher oleic/linoleic (O/L) ratio and lower level of DHSA are preferred, and for industrial oils a high level of VA is preferred. Our results indicate that seeds from H. cannabinus may be of higher quality than H. sabdariffa seeds for these reasons. Significant variability in oil content and major fatty acids was also detected within both species. The variability in oil content and fatty acid composition revealed from this study will be useful for exploring seed utilization and developing new cultivars in these Hibiscus species.

Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

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Schmidt, Amand F; Klungel, Olaf H; Groenwold, Rolf H H

2016-01-01

Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and stabilized inverse probability weighting methods to adjust for confounding. Model misspecification was induced in the independent derivation dataset. We evaluated performance using relative bias confidence interval coverage of the true effect, among other metrics. At low events per coefficient (1.0 and 0.5), the logistic regression estimates had a large relative bias (greater than -100%). Bias of the disease risk score estimates was at most 13.48% and 18.83%. For the propensity score model, this was 8.74% and >100%, respectively. At events per coefficient of 1.0 and 0.5, inverse probability weighting frequently failed or reduced to a crude regression, resulting in biases of -8.49% and 24.55%. Coverage of logistic regression estimates became less than the nominal level at events per coefficient ≤5. For the disease risk score, inverse probability weighting, and propensity score, coverage became less than nominal at events per coefficient ≤2.5, ≤1.0, and ≤1.0, respectively. Bias of misspecified disease risk score models was 16.55%. In settings with low events/exposed subjects per coefficient, disease risk score methods can be useful alternatives to logistic regression models, especially when propensity score models cannot be used. Despite better performance of disease risk score methods than logistic regression and propensity score models in small events per coefficient settings, bias, and coverage still deviated from nominal.

Learning from Television News: A Critique of the Research.

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Berry, Colin

1983-01-01

This critical review of some approaches to research on the effectiveness of television newscasts considers viewer characteristics, news item characteristics, presentation variables, and the confounding of these variables. The importance of behavioral science issues to such research is stressed. (MBR)

Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report--Part II.

Science.gov (United States)

Cox, Emily; Martin, Bradley C; Van Staa, Tjeerd; Garbe, Edeltraut; Siebert, Uwe; Johnson, Michael L

2009-01-01

The goal of comparative effectiveness analysis is to examine the relationship between two variables, treatment, or exposure and effectiveness or outcome. Unlike data obtained through randomized controlled trials, researchers face greater challenges with causal inference with observational studies. Recognizing these challenges, a task force was formed to develop a guidance document on methodological approaches to addresses these biases. The task force was commissioned and a Chair was selected by the International Society for Pharmacoeconomics and Outcomes Research Board of Directors in October 2007. This report, the second of three reported in this issue of the Journal, discusses the inherent biases when using secondary data sources for comparative effectiveness analysis and provides methodological recommendations to help mitigate these biases. The task force report provides recommendations and tools for researchers to mitigate threats to validity from bias and confounding in measurement of exposure and outcome. Recommendations on design of study included: the need for data analysis plan with causal diagrams; detailed attention to classification bias in definition of exposure and clinical outcome; careful and appropriate use of restriction; extreme care to identify and control for confounding factors, including time-dependent confounding. Design of nonrandomized studies of comparative effectiveness face several daunting issues, including measurement of exposure and outcome challenged by misclassification and confounding. Use of causal diagrams and restriction are two techniques that can improve the theoretical basis for analyzing treatment effects in study populations of more homogeneity, with reduced loss of generalizability.

VITAMIN A DEFICIENCY IN BRAZILIAN CHILDREN AND ASSOCIATED VARIABLES.

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Lima, Daniela Braga; Damiani, Lucas Petri; Fujimori, Elizabeth

2018-03-29

To analyze the variables associated with vitamin A deficiency (VAD) in Brazilian children aged 6 to 59 months, considering a hierarchical model of determination. This is part of the National Survey on Demography and Health of Women and Children, held in 2006. Data analysis included 3,417 children aged from six to 59 months with retinol data. Vitamin A deficiency was defined as serum retinol Poisson regression analysis were performed, with significance level set at 5%, using a hierarchical model of determination that considered three conglomerates of variables: those linked to the structural processes of community (socioeconomic-demographic variables); to the immediate environment of the child (maternal variables, safety and food consumption); and individual features (biological characteristics of the child). Data were expressed in prevalence ratio (PR). After adjustment for confounding variables, the following remained associated with VAD: living in the Southeast [PR=1,59; 95%CI 1,19-2,17] and Northeast [PR=1,56; 95%CI 1,16-2,15]; in urban area [RP=1,31; 95%CI 1,02-1,72]; and mother aged ≥36 years [RP=2,28; 95%CI 1,37-3,98], the consumption of meat at least once in the last seven days was a protective factor [PR=0,24; 95%CI 0,13-0,42]. The main variables associated with VAD in the country are related to structural processes of society and to the immediate, but not individual, environment of the child.

Spatial variability of methane production and methanogen communities within a eutrophic reservoir: evaluating the importance of organic matter source and quantity

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Freshwater reservoirs are an important source of the greenhouse gas methane (CH4) to the atmosphere, but there is a wide range of estimates of global emissions, due in part to variability of methane emissions rates within reservoirs. While morphological characteristics, including...

Bayesian inference in a discrete shock model using confounded common cause data

International Nuclear Information System (INIS)

Kvam, Paul H.; Martz, Harry F.

1995-01-01

We consider redundant systems of identical components for which reliability is assessed statistically using only demand-based failures and successes. Direct assessment of system reliability can lead to gross errors in estimation if there exist external events in the working environment that cause two or more components in the system to fail in the same demand period which have not been included in the reliability model. We develop a simple Bayesian model for estimating component reliability and the corresponding probability of common cause failure in operating systems for which the data is confounded; that is, the common cause failures cannot be distinguished from multiple independent component failures in the narrative event descriptions

No evidence for thermal transgenerational plasticity in metabolism when minimizing the potential for confounding effects.

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Kielland, Ø N; Bech, C; Einum, S

2017-01-11

Environmental change may cause phenotypic changes that are inherited across generations through transgenerational plasticity (TGP). If TGP is adaptive, offspring fitness increases with an increasing match between parent and offspring environment. Here we test for adaptive TGP in somatic growth and metabolic rate in response to temperature in the clonal zooplankton Daphnia pulex Animals of the first focal generation experienced thermal transgenerational 'mismatch' (parental and offspring temperatures differed), whereas conditions of the next two generations matched the (grand)maternal thermal conditions. Adjustments of metabolic rate occurred during the lifetime of the first generation (i.e. within-generation plasticity). However, no further change was observed during the subsequent two generations, as would be expected under TGP. Furthermore, we observed no tendency for increased juvenile somatic growth (a trait highly correlated with fitness in Daphnia) over the three generations when reared at new temperatures. These results are inconsistent with existing studies of thermal TGP, and we describe how previous experimental designs may have confounded TGP with within-generation plasticity and selective mortality. We suggest that the current evidence for thermal TGP is weak. To increase our understanding of the ecological and evolutionary role of TGP, future studies should more carefully identify possible confounding factors. © 2017 The Author(s).

An AUC-based permutation variable importance measure for random forests.

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Janitza, Silke; Strobl, Carolin; Boulesteix, Anne-Laure

2013-04-05

The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the new AUC-based permutation VIM outperforms the standard permutation VIM for unbalanced data settings while both permutation VIMs have equal performance for balanced data settings. The standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html.

Variability in Adaptive Behavior in Autism: Evidence for the Importance of Family History

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Mazefsky, Carla A.; Williams, Diane L.; Minshew, Nancy J.

2008-01-01

Adaptive behavior in autism is highly variable and strongly related to prognosis. This study explored family history as a potential source of variability in adaptive behavior in autism. Participants included 77 individuals (mean age = 18) with average or better intellectual ability and autism. Parents completed the Family History Interview about…

Analysis of Longitudinal Studies With Repeated Outcome Measures: Adjusting for Time-Dependent Confounding Using Conventional Methods.

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Keogh, Ruth H; Daniel, Rhian M; VanderWeele, Tyler J; Vansteelandt, Stijn

2018-05-01

Estimation of causal effects of time-varying exposures using longitudinal data is a common problem in epidemiology. When there are time-varying confounders, which may include past outcomes, affected by prior exposure, standard regression methods can lead to bias. Methods such as inverse probability weighted estimation of marginal structural models have been developed to address this problem. However, in this paper we show how standard regression methods can be used, even in the presence of time-dependent confounding, to estimate the total effect of an exposure on a subsequent outcome by controlling appropriately for prior exposures, outcomes, and time-varying covariates. We refer to the resulting estimation approach as sequential conditional mean models (SCMMs), which can be fitted using generalized estimating equations. We outline this approach and describe how including propensity score adjustment is advantageous. We compare the causal effects being estimated using SCMMs and marginal structural models, and we compare the two approaches using simulations. SCMMs enable more precise inferences, with greater robustness against model misspecification via propensity score adjustment, and easily accommodate continuous exposures and interactions. A new test for direct effects of past exposures on a subsequent outcome is described.

Offspring ADHD as a risk factor for parental marital problems: controls for genetic and environmental confounds.

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Schermerhorn, Alice C; D'Onofrio, Brian M; Slutske, Wendy S; Emery, Robert E; Turkheimer, Eric; Harden, K Paige; Heath, Andrew C; Martin, Nicholas G

2012-12-01

Previous studies have found that child attention-deficit/hyperactivity disorder (ADHD) is associated with more parental marital problems. However, the reasons for this association are unclear. The association might be due to genetic or environmental confounds that contribute to both marital problems and ADHD. Data were drawn from the Australian Twin Registry, including 1,296 individual twins, their spouses, and offspring. We studied adult twins who were discordant for offspring ADHD.Using a discordant twin pairs design, we examined the extent to which genetic and environmental confounds,as well as measured parental and offspring characteristics, explain the ADHD-marital problems association. Offspring ADHD predicted parental divorce and marital conflict. The associations were also robust when comparing differentially exposed identical twins to control for unmeasured genetic and environmental factors, when controlling for measured maternal and paternal psychopathology,when restricting the sample based on timing of parental divorce and ADHD onset, and when controlling for other forms of offspring psychopathology. Each of these controls rules out alternative explanations for the association. The results of the current study converge with those of prior research in suggesting that factors directly associated with offspring ADHD increase parental marital problems.

Cryptic confounding compounds: A brief consideration of the influences of anthropogenic contaminants on courtship and mating behavior

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Blocker, Tomica D.; Ophir, Alexander G.

2012-01-01

Contaminants, like pesticides, polychlorinated biphenyls (PCBs), dioxins and metals, are persistent and ubiquitous and are known to threaten the environment. Traditionally, scientists have considered the direct physiological risks that these contaminants pose. However, scientists have just begun to integrate ethology and toxicology to investigate the effects that contaminants have on behavior. This review considers the potential for contaminant effects on mating behavior. Here we assess the growing body of research concerning disruptions in sexual differentiation, courtship, sexual receptivity, arousal, and mating. We discuss the implications of these disruptions on conservation efforts and highlight the importance of recognizing the potential for environmental stressors to affect behavioral experimentation. More specifically, we consider the negative implications for anthropogenic contaminants to affect the immediate behavior of animals, and their potential to have cascading and/or long-term effects on the behavioral ecology and evolution of populations. Overall, we aim to raise awareness of the confounding influence that contaminants can have, and promote caution when interpreting results where the potential for cryptic affects are possible. PMID:24244068

Time-Dependent Confounding in the Study of the Effects of Regular Physical Activity in Chronic Obstructive Pulmonary Disease: An Application of the Marginal Structural Model

DEFF Research Database (Denmark)

Garcia-Aymerich, Judith; Lange, Peter; Serra, Ignasi

2008-01-01

PURPOSE: Results from longitudinal studies about the association between physical activity and chronic obstructive pulmonary disease (COPD) may have been biased because they did not properly adjust for time-dependent confounders. Marginal structural models (MSMs) have been proposed to address...... this type of confounding. We sought to assess the presence of time-dependent confounding in the association between physical activity and COPD development and course by comparing risk estimates between standard statistical methods and MSMs. METHODS: By using the population-based cohort Copenhagen City Heart...... Study, 6,568 subjects selected from the general population in 1976 were followed up until 2004 with three repeated examinations. RESULTS: Moderate to high compared with low physical activity was associated with a reduced risk of developing COPD both in the standard analysis (odds ratio [OR] 0.76, p = 0...

HOW NORMAL IS VARIABLE, OR HOW VARIABLE IS NORMAL

NARCIS (Netherlands)

TOUWEN, BCL

Variability is an important property of the central nervous system, and it shows characteristic changes during infancy and childhood. The large amount of variations in the performance of sensomotor functions in infancy is called indiscriminate or primary variability. During toddling age the child

Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer

Directory of Open Access Journals (Sweden)

Doyle Scott

2012-10-01

Full Text Available Abstract Background Automated classification of histopathology involves identification of multiple classes, including benign, cancerous, and confounder categories. The confounder tissue classes can often mimic and share attributes with both the diseased and normal tissue classes, and can be particularly difficult to identify, both manually and by automated classifiers. In the case of prostate cancer, they may be several confounding tissue types present in a biopsy sample, posing as major sources of diagnostic error for pathologists. Two common multi-class approaches are one-shot classification (OSC, where all classes are identified simultaneously, and one-versus-all (OVA, where a “target” class is distinguished from all “non-target” classes. OSC is typically unable to handle discrimination of classes of varying similarity (e.g. with images of prostate atrophy and high grade cancer, while OVA forces several heterogeneous classes into a single “non-target” class. In this work, we present a cascaded (CAS approach to classifying prostate biopsy tissue samples, where images from different classes are grouped to maximize intra-group homogeneity while maximizing inter-group heterogeneity. Results We apply the CAS approach to categorize 2000 tissue samples taken from 214 patient studies into seven classes: epithelium, stroma, atrophy, prostatic intraepithelial neoplasia (PIN, and prostate cancer Gleason grades 3, 4, and 5. A series of increasingly granular binary classifiers are used to split the different tissue classes until the images have been categorized into a single unique class. Our automatically-extracted image feature set includes architectural features based on location of the nuclei within the tissue sample as well as texture features extracted on a per-pixel level. The CAS strategy yields a positive predictive value (PPV of 0.86 in classifying the 2000 tissue images into one of 7 classes, compared with the OVA (0.77 PPV and OSC

Familial confounding of the association between maternal smoking during pregnancy and offspring substance use and problems.

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D'Onofrio, Brian M; Rickert, Martin E; Langström, Niklas; Donahue, Kelly L; Coyne, Claire A; Larsson, Henrik; Ellingson, Jarrod M; Van Hulle, Carol A; Iliadou, Anastasia N; Rathouz, Paul J; Lahey, Benjamin B; Lichtenstein, Paul

2012-11-01

Previous epidemiological, animal, and human cognitive neuroscience research suggests that maternal smoking during pregnancy (SDP) causes increased risk of substance use/problems in offspring. To determine the extent to which the association between SDP and offspring substance use/problems depends on confounded familial background factors by using a quasi-experimental design. We used 2 separate samples from the United States and Sweden. The analyses prospectively predicted multiple indices of substance use and problems while controlling for statistical covariates and comparing differentially exposed siblings to minimize confounding. Offspring of a representative sample of women in the United States (sample 1) and the total Swedish population born during the period from January 1, 1983, to December 31, 1995 (sample 2). Adolescent offspring of the women in the National Longitudinal Survey of Youth 1979 (n = 6904) and all offspring born in Sweden during the 13-year period (n = 1,187,360). Self-reported adolescent alcohol, cigarette, and marijuana use and early onset (before 14 years of age) of each substance (sample 1) and substance-related convictions and hospitalizations for an alcohol- or other drug-related problem (sample 2). The same pattern emerged for each index of substance use/problems across the 2 samples. At the population level, maternal SDP predicted every measure of offspring substance use/problems in both samples, ranging from adolescent alcohol use (hazard ratio [HR](moderate), 1.32 [95% CI, 1.22-1.43]; HR(high), 1.33 [1.17-1.53]) to a narcotics-related conviction (HR(moderate), 2.23 [2.14-2.31]; HR(high), 2.97 [2.86-3.09]). When comparing differentially exposed siblings to minimize genetic and environmental confounds, however, the association between SDP and each measure of substance use/problems was minimal and not statistically significant. The association between maternal SDP and offspring substance use/problems is likely due to familial background

Recommendations to standardize preanalytical confounding factors in Alzheimer's and Parkinson's disease cerebrospinal fluid biomarkers

DEFF Research Database (Denmark)

del Campo, Marta; Mollenhauer, Brit; Bertolotto, Antonio

2012-01-01

Early diagnosis of neurodegenerative disorders such as Alzheimer's (AD) or Parkinson's disease (PD) is needed to slow down or halt the disease at the earliest stage. Cerebrospinal fluid (CSF) biomarkers can be a good tool for early diagnosis. However, their use in clinical practice is challenging...... the need to establish standardized operating procedures. Here, we merge two previous consensus guidelines for preanalytical confounding factors in order to achieve one exhaustive guideline updated with new evidence for Aβ42, total tau and phosphorylated tau, and α-synuclein. The proposed standardized...

Ecological niche models reveal the importance of climate variability for the biogeography of protosteloid amoebae.

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Aguilar, María; Lado, Carlos

2012-08-01

Habitat availability and environmental preferences of species are among the most important factors in determining the success of dispersal processes and therefore in shaping the distribution of protists. We explored the differences in fundamental niches and potential distributions of an ecological guild of slime moulds-protosteloid amoebae-in the Iberian Peninsula. A large set of samples collected in a north-east to south-west transect of approximately 1000 km along the peninsula was used to test the hypothesis that, together with the existence of suitable microhabitats, climate conditions may determine the probability of survival of species. Although protosteloid amoebae share similar morphologies and life history strategies, canonical correspondence analyses showed that they have varied ecological optima, and that climate conditions have an important effect in niche differentiation. Maxent environmental niche models provided consistent predictions of the probability of presence of the species based on climate data, and they were used to generate maps of potential distribution in an 'everything is everywhere' scenario. The most important climatic factors were, in both analyses, variables that measure changes in conditions throughout the year, confirming that the alternation of fruiting bodies, cysts and amoeboid stages in the life cycles of protosteloid amoebae constitutes an advantage for surviving in a changing environment. Microhabitat affinity seems to be influenced by climatic conditions, which suggests that the micro-environment may vary at a local scale and change together with the external climate at a larger scale.

A Study of the Relative Importance of Communication and Economic Variables in Diffusion: Dwarf Wheats on Unirrigated Small Holdings in Pakistan.

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Rochin, Refugio I.

The purpose of this paper is twofold: (1) it presents some empirical findings of the relative importance of both "economic" and "communication" variables in the diffusion of an innovation (dwarf wheats) in an unirrigated region of Pakistan which is densely populated by smallholders. The sample of farmers reported are…

Adjusting for the Confounding Effects of Treatment Switching—The BREAK-3 Trial: Dabrafenib Versus Dacarbazine

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Abrams, Keith R.; Amonkar, Mayur M.; Stapelkamp, Ceilidh; Swann, R. Suzanne

2015-01-01

Background. Patients with previously untreated BRAF V600E mutation-positive melanoma in BREAK-3 showed a median overall survival (OS) of 18.2 months for dabrafenib versus 15.6 months for dacarbazine (hazard ratio [HR], 0.76; 95% confidence interval, 0.48–1.21). Because patients receiving dacarbazine were allowed to switch to dabrafenib at disease progression, we attempted to adjust for the confounding effects on OS. Materials and Methods. Rank preserving structural failure time models (RPSFTMs) and the iterative parameter estimation (IPE) algorithm were used. Two analyses, “treatment group” (assumes treatment effect could continue until death) and “on-treatment observed” (assumes treatment effect disappears with discontinuation), were used to test the assumptions around the durability of the treatment effect. Results. A total of 36 of 63 patients (57%) receiving dacarbazine switched to dabrafenib. The adjusted OS HRs ranged from 0.50 to 0.55, depending on the analysis. The RPSFTM and IPE “treatment group” and “on-treatment observed” analyses performed similarly well. Conclusion. RPSFTM and IPE analyses resulted in point estimates for the OS HR that indicate a substantial increase in the treatment effect compared with the unadjusted OS HR of 0.76. The results are uncertain because of the assumptions associated with the adjustment methods. The confidence intervals continued to cross 1.00; thus, the adjusted estimates did not provide statistically significant evidence of a treatment benefit on survival. However, it is clear that a standard intention-to-treat analysis will be confounded in the presence of treatment switching—a reliance on unadjusted analyses could lead to inappropriate practice. Adjustment analyses provide useful additional information on the estimated treatment effects to inform decision making. Implications for Practice: Treatment switching is common in oncology trials, and the implications of this for the interpretation of the

Adjusting for the Confounding Effects of Treatment Switching-The BREAK-3 Trial: Dabrafenib Versus Dacarbazine.

Science.gov (United States)

Latimer, Nicholas R; Abrams, Keith R; Amonkar, Mayur M; Stapelkamp, Ceilidh; Swann, R Suzanne

2015-07-01

Patients with previously untreated BRAF V600E mutation-positive melanoma in BREAK-3 showed a median overall survival (OS) of 18.2 months for dabrafenib versus 15.6 months for dacarbazine (hazard ratio [HR], 0.76; 95% confidence interval, 0.48-1.21). Because patients receiving dacarbazine were allowed to switch to dabrafenib at disease progression, we attempted to adjust for the confounding effects on OS. Rank preserving structural failure time models (RPSFTMs) and the iterative parameter estimation (IPE) algorithm were used. Two analyses, "treatment group" (assumes treatment effect could continue until death) and "on-treatment observed" (assumes treatment effect disappears with discontinuation), were used to test the assumptions around the durability of the treatment effect. A total of 36 of 63 patients (57%) receiving dacarbazine switched to dabrafenib. The adjusted OS HRs ranged from 0.50 to 0.55, depending on the analysis. The RPSFTM and IPE "treatment group" and "on-treatment observed" analyses performed similarly well. RPSFTM and IPE analyses resulted in point estimates for the OS HR that indicate a substantial increase in the treatment effect compared with the unadjusted OS HR of 0.76. The results are uncertain because of the assumptions associated with the adjustment methods. The confidence intervals continued to cross 1.00; thus, the adjusted estimates did not provide statistically significant evidence of a treatment benefit on survival. However, it is clear that a standard intention-to-treat analysis will be confounded in the presence of treatment switching-a reliance on unadjusted analyses could lead to inappropriate practice. Adjustment analyses provide useful additional information on the estimated treatment effects to inform decision making. Treatment switching is common in oncology trials, and the implications of this for the interpretation of the clinical effectiveness and cost-effectiveness of the novel treatment are important to consider. If

Important variables for parents' postnatal sense of security: evaluating a new Swedish instrument (the PPSS instrument).

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Persson, Eva K; Dykes, Anna-Karin

2009-08-01

to evaluate dimensions of both parents' postnatal sense of security the first week after childbirth, and to determine associations between the PPSS instrument and different sociodemographic and situational background variables. evaluative, cross-sectional design. 113 mothers and 99 fathers with children live born at term, from five hospitals in southern Sweden. mothers and fathers had similar feelings concerning postnatal sense of security. Of the dimensions in the PPSS instrument, a sense of midwives'/nurses' empowering behaviour, a sense of one's own general well-being and a sense of the mother's well-being as experienced by the father were the most important dimensions for parents' experienced security. A sense of affinity within the family (for both parents) and a sense of manageable breast feeding (for mothers) were not significantly associated with their experienced security. A sense of participation during pregnancy and general anxiety were significantly associated background variables for postnatal sense of security for both parents. For the mothers, parity and a sense that the father was participating during pregnancy were also significantly associated. more focus on parents' participation during pregnancy as well as midwives'/nurses' empowering behaviour during the postnatal period will be beneficial for both parents' postnatal sense of security.

Importance of fruit variability in the assessment of apple quality by sensory evaluation

DEFF Research Database (Denmark)

Bavay, Cécile; Symoneaux, Ronan; Maître, Isabelle

2013-01-01

cultivars, apples were sorted into homogenous acoustic firmness categories within each cultivar. The discrimination ability of the trained panel was observed not only between cultivars but also within each cultivar for crunchiness, firmness, juiciness and acidity. Following these results, a mixed......The assessment of produce quality is a major aspect of applied postharvest biology. Horticultural researchers working on organoleptic quality of fruit need objective methods for the evaluation of sensory properties. The development of sensory methodologies specifically for apples highlighted...... the problem of handling variation due to fruit variability and assessor differences. The aim of this study was to investigate the weight of within-batch variability in sensory evaluation of apples and to propose a methodology that accounts for this variability. Prior to sensory analysis, for three apple...

Salivary alpha-amylase: More than an enzyme Investigating confounders of stress-induced and basal amylase activity

OpenAIRE

Strahler, Jana

2010-01-01

Summary: Salivary alpha-amylase: More than an enzyme - Investigating confounders of stress-induced and basal amylase activity (Dipl.-Psych. Jana Strahler) The hypothalamus-pituitary-adrenal (HPA) axis and the autonomic nervous system (ANS) are two of the major systems playing a role in the adaptation of organisms to developmental changes that threaten homeostasis. The HPA system involves the secretion of glucocorticoids, including cortisol, into the circulatory system. Numerous studies hav...

Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

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Rose, Sherri

2018-03-11

To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending. 2011-2012 Truven MarketScan database. I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression. My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression. The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. © Health Research and Educational Trust.

Risk of bias and confounding of observational studies of Zika virus infection: A scoping review of research protocols.

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Reveiz, Ludovic; Haby, Michelle M; Martínez-Vega, Ruth; Pinzón-Flores, Carlos E; Elias, Vanessa; Smith, Emma; Pinart, Mariona; Broutet, Nathalie; Becerra-Posada, Francisco; Aldighieri, Sylvain; Van Kerkhove, Maria D

2017-01-01

Given the severity and impact of the current Zika virus (ZIKV) outbreak in the Americas, numerous countries have rushed to develop research studies to assess ZIKV and its potential health consequences. In an effort to ensure that studies are comprehensive, both internally and externally valid, and with reliable results, the World Health Organization, the Pan American Health Organization, Institut Pasteur, the networks of Fiocruz, the Consortia for the Standardization of Influenza Seroepidemiology (CONSISE) and the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) have generated six standardized clinical and epidemiological research protocols and questionnaires to address key public health questions on ZIKV. We conducted a systematic search of ongoing study protocols related to ZIKV research. We analyzed the content of protocols of 32 cohort studies and 13 case control studies for systematic bias that could produce erroneous results. Additionally we aimed to characterize the risks of bias and confounding in observational studies related to ZIKV and to propose ways to minimize them, including the use of six newly standardized research protocols. Observational studies of ZIKV face an array of challenges, including measurement of exposure and outcomes (microcephaly and Guillain-Barré Syndrome). Potential confounders need to be measured where known and controlled for in the analysis. Selection bias due to non-random selection is a significant issue, particularly in the case-control design, and losses to follow-up is equally important for the cohort design. Observational research seeking to answer key questions on the ZIKV should consider these restrictions and take precautions to minimize bias in an effort to provide reliable and valid results. Utilization of the standardized research protocols developed by the WHO, PAHO, Institut Pasteur, and CONSISE will harmonize the key methodological aspects of each study design to minimize bias at

Risk of bias and confounding of observational studies of Zika virus infection: A scoping review of research protocols.

Directory of Open Access Journals (Sweden)

Ludovic Reveiz

Full Text Available Given the severity and impact of the current Zika virus (ZIKV outbreak in the Americas, numerous countries have rushed to develop research studies to assess ZIKV and its potential health consequences. In an effort to ensure that studies are comprehensive, both internally and externally valid, and with reliable results, the World Health Organization, the Pan American Health Organization, Institut Pasteur, the networks of Fiocruz, the Consortia for the Standardization of Influenza Seroepidemiology (CONSISE and the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC have generated six standardized clinical and epidemiological research protocols and questionnaires to address key public health questions on ZIKV.We conducted a systematic search of ongoing study protocols related to ZIKV research. We analyzed the content of protocols of 32 cohort studies and 13 case control studies for systematic bias that could produce erroneous results. Additionally we aimed to characterize the risks of bias and confounding in observational studies related to ZIKV and to propose ways to minimize them, including the use of six newly standardized research protocols.Observational studies of ZIKV face an array of challenges, including measurement of exposure and outcomes (microcephaly and Guillain-Barré Syndrome. Potential confounders need to be measured where known and controlled for in the analysis. Selection bias due to non-random selection is a significant issue, particularly in the case-control design, and losses to follow-up is equally important for the cohort design.Observational research seeking to answer key questions on the ZIKV should consider these restrictions and take precautions to minimize bias in an effort to provide reliable and valid results. Utilization of the standardized research protocols developed by the WHO, PAHO, Institut Pasteur, and CONSISE will harmonize the key methodological aspects of each study design to

Biasogram: visualization of confounding technical bias in gene expression data

DEFF Research Database (Denmark)

Krzystanek, Marcin; Szallasi, Zoltan Imre; Eklund, Aron Charles

2013-01-01

Gene expression profiles of clinical cohorts can be used to identify genes that are correlated with a clinical variable of interest such as patient outcome or response to a particular drug. However, expression measurements are susceptible to technical bias caused by variation in extraneous factors...... such as RNA quality and array hybridization conditions. If such technical bias is correlated with the clinical variable of interest, the likelihood of identifying false positive genes is increased. Here we describe a method to visualize an expression matrix as a projection of all genes onto a plane defined...... by a clinical variable and a technical nuisance variable. The resulting plot indicates the extent to which each gene is correlated with the clinical variable or the technical variable. We demonstrate this method by applying it to three clinical trial microarray data sets, one of which identified genes that may...

Accounting for genetic and environmental confounds in associations between parent and child characteristics: a systematic review of children-of-twins studies.

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McAdams, Tom A; Neiderhiser, Jenae M; Rijsdijk, Fruhling V; Narusyte, Jurgita; Lichtenstein, Paul; Eley, Thalia C

2014-07-01

Parental psychopathology, parenting style, and the quality of intrafamilial relationships are all associated with child mental health outcomes. However, most research can say little about the causal pathways underlying these associations. This is because most studies are not genetically informative and are therefore not able to account for the possibility that associations are confounded by gene-environment correlation. That is, biological parents not only provide a rearing environment for their child, but also contribute 50% of their genes. Any associations between parental phenotype and child phenotype are therefore potentially confounded. One technique for disentangling genetic from environmental effects is the children-of-twins (COT) method. This involves using data sets comprising twin parents and their children to distinguish genetic from environmental associations between parent and child phenotypes. The COT technique has grown in popularity in the last decade, and we predict that this surge in popularity will continue. In the present article we explain the COT method for those unfamiliar with its use. We present the logic underlying this approach, discuss strengths and weaknesses, and highlight important methodological considerations for researchers interested in the COT method. We also cover variations on basic COT approaches, including the extended-COT method, capable of distinguishing forms of gene-environment correlation. We then present a systematic review of all the behavioral COT studies published to date. These studies cover such diverse phenotypes as psychosis, substance abuse, internalizing, externalizing, parenting, and marital difficulties. In reviewing this literature, we highlight past applications, identify emergent patterns, and suggest avenues for future research. PsycINFO Database Record (c) 2014 APA, all rights reserved.

High blood pressure and sedentary behavior in adolescents are associated even after controlling for confounding factors.

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Christofaro, Diego Giulliano Destro; De Andrade, Selma Maffei; Cardoso, Jefferson Rosa; Mesas, Arthur Eumann; Codogno, Jamile Sanches; Fernandes, Rômulo Araújo

2015-01-01

The aim of this study was to determine whether high blood pressure (HBP) is associated with sedentary behavior in young people even after controlling for potential confounders (gender, age, socioeconomic level, tobacco, alcohol, obesity and physical activity). In this epidemiological study, 1231 adolescents were evaluated. Blood pressure was measured with an oscillometric device and waist circumference with an inextensible tape. Sedentary behavior (watching television, computer use and playing video games) and physical activity were assessed by a questionnaire. We used mean and standard deviation to describe the statistical analysis, and the association between HBP and sedentary behavior was assessed by the chi-squared test. Binary logistic regression was used to observe the magnitude of association and cluster analyses (sedentary behavior and abdominal obesity; sedentary behavior and physical inactivity). HBP was associated with sedentary behaviors [odds ratio (OR) = 2.21, 95% confidence interval (CI) = 1.41-3.96], even after controlling for various confounders (OR = 1.68, CI = 1.03-2.75). In cluster analysis the combination of sedentary behavior and elevated abdominal obesity contributed significantly to an increased likelihood of having HBP (OR = 13.51, CI 7.21-23.97). Sedentary behavior was associated with HBP, and excess fat in the abdominal region contributed to the modulation of this association.

Fresh fruit intake and asthma symptoms in young British adults: confounding or effect modification by smoking?

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Butland, B K; Strachan, D P; Anderson, H R

1999-04-01

Antioxidant vitamins have been postulated as a protective factor in asthma. The associations between the frequency of fresh fruit consumption in summer, and the prevalence of self-reported asthma symptoms were investigated. The analysis was based on 5,582 males and 5,770 females, born in England, Wales and Scotland between March 3-9, 1958 and aged 33 yrs at the time of survey. The 12-month period prevalence of wheeze and frequent wheeze were inversely associated with frequent intakes of fresh fruit and salad/raw vegetables and positively associated with smoking and lower social class. After adjustment for mutual confounding and sex, associations with smoking persisted, but those with social class and salad/raw vegetable consumption lost significance. The frequency of fresh fruit intake was no longer associated with wheeze after adjustment, but was inversely associated with frequent wheeze and speech-limiting attacks. The association with frequent wheeze differed significantly between smoking groups (never, former, current) and appeared to be confined to exsmokers and current smokers. These findings support postulated associations between infrequent fresh fruit consumption and the prevalence of frequent or severe asthma symptoms in adults. Associations appeared to be restricted to smokers, with effect modification as a more likely explanation of this pattern than residual confounding by smoking.

FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

Science.gov (United States)

Lorenzo-Seva, Urbano; Ferrando, Pere J

2011-03-01

We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

Pathogen prevalence predicts human cross-cultural variability in individualism/collectivism.

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Fincher, Corey L; Thornhill, Randy; Murray, Damian R; Schaller, Mark

2008-06-07

Pathogenic diseases impose selection pressures on the social behaviour of host populations. In humans (Homo sapiens), many psychological phenomena appear to serve an antipathogen defence function. One broad implication is the existence of cross-cultural differences in human cognition and behaviour contingent upon the relative presence of pathogens in the local ecology. We focus specifically on one fundamental cultural variable: differences in individualistic versus collectivist values. We suggest that specific behavioural manifestations of collectivism (e.g. ethnocentrism, conformity) can inhibit the transmission of pathogens; and so we hypothesize that collectivism (compared with individualism) will more often characterize cultures in regions that have historically had higher prevalence of pathogens. Drawing on epidemiological data and the findings of worldwide cross-national surveys of individualism/collectivism, our results support this hypothesis: the regional prevalence of pathogens has a strong positive correlation with cultural indicators of collectivism and a strong negative correlation with individualism. The correlations remain significant even when controlling for potential confounding variables. These results help to explain the origin of a paradigmatic cross-cultural difference, and reveal previously undocumented consequences of pathogenic diseases on the variable nature of human societies.

Are Changes in Heart Rate Variability During Hypoglycemia Confounded by the Presence of Cardiovascular Autonomic Neuropathy in Patients with Diabetes?

DEFF Research Database (Denmark)

Cichosz, Simon Lebech; Frystyk, Jan; Tarnow, Lise

2017-01-01

BACKGROUND: We have recently shown how the combination of information from continuous glucose monitor (CGM) and heart rate variability (HRV) measurements can be used to construct an algorithm for prediction of hypoglycemia in both bedbound and active patients with type 1 diabetes (T1D). Questions...... with CGM and a Holter device while they performed normal daily activities. CAN was diagnosed using two cardiac reflex tests: (1) deep breathing and (2) orthostatic hypotension and end organ symptoms. Early CAN was defined as the presence of one abnormal reflex test and severe CAN was defined as two...

The comet assay as a rapid test in biomonitoring occupational exposure to DNA-damaging agents and effect of confounding factors

DEFF Research Database (Denmark)

Møller, P; Knudsen, Lisbeth E.; Loft, S

2000-01-01

appeared to have less power than the positive studies. Also, there were poor dose-response relationships in many of the biomonitoring studies. Many factors have been reported to produce effects by the comet assay, e.g., age, air pollution exposure, diet, exercise, gender, infection, residential radon...... be used as criteria for the selection of populations and that data on exercise, diet, and recent infections be registered before blood sampling. Samples from exposed and unexposed populations should be collected at the same time to avoid seasonal variation. In general, the comet assay is considered...... exposure, smoking, and season. Until now, the use of the comet assay has been hampered by the uncertainty of the influence of confounding factors. We argue that none of the confounding factors are unequivocally positive in the majority of the studies. We recommend that age, gender, and smoking status...

ZnO crystals obtained by electrodeposition: Statistical analysis of most important process variables

International Nuclear Information System (INIS)

Cembrero, Jesus; Busquets-Mataix, David

2009-01-01

In this paper a comparative study by means of a statistical analysis of the main process variables affecting ZnO crystal electrodeposition is presented. ZnO crystals were deposited on two different substrates, silicon wafer and indium tin oxide. The control variables were substrate types, electrolyte concentration, temperature, exposition time and current density. The morphologies of the different substrates were observed using scanning electron microscopy. The percentage of substrate area covered by ZnO deposit was calculated by computational image analysis. The design of the applied experiments was based on a two-level factorial analysis involving a series of 32 experiments and an analysis of variance. Statistical results reveal that variables exerting a significant influence on the area covered by ZnO deposit are electrolyte concentration, substrate type and time of deposition, together with a combined two-factor interaction between temperature and current density. However, morphology is also influenced by surface roughness of the substrates

Reducing confounding and suppression effects in TCGA data: an integrated analysis of chemotherapy response in ovarian cancer

Directory of Open Access Journals (Sweden)

Hsu Fang-Han

2012-10-01

Full Text Available Abstract Background Despite initial response in adjuvant chemotherapy, ovarian cancer patients treated with the combination of paclitaxel and carboplatin frequently suffer from recurrence after few cycles of treatment, and the underlying mechanisms causing the chemoresistance remain unclear. Recently, The Cancer Genome Atlas (TCGA research network concluded an ovarian cancer study and released the dataset to the public. The TCGA dataset possesses large sample size, comprehensive molecular profiles, and clinical outcome information; however, because of the unknown molecular subtypes in ovarian cancer and the great diversity of adjuvant treatments TCGA patients went through, studying chemotherapeutic response using the TCGA data is difficult. Additionally, factors such as sample batches, patient ages, and tumor stages further confound or suppress the identification of relevant genes, and thus the biological functions and disease mechanisms. Results To address these issues, herein we propose an analysis procedure designed to reduce suppression effect by focusing on a specific chemotherapeutic treatment, and to remove confounding effects such as batch effect, patient's age, and tumor stages. The proposed procedure starts with a batch effect adjustment, followed by a rigorous sample selection process. Then, the gene expression, copy number, and methylation profiles from the TCGA ovarian cancer dataset are analyzed using a semi-supervised clustering method combined with a novel scoring function. As a result, two molecular classifications, one with poor copy number profiles and one with poor methylation profiles, enriched with unfavorable scores are identified. Compared with the samples enriched with favorable scores, these two classifications exhibit poor progression-free survival (PFS and might be associated with poor chemotherapy response specifically to the combination of paclitaxel and carboplatin. Significant genes and biological processes are

Relation between sick leave and selected exposure variables among women semiconductor workers in Malaysia

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Chee, H; Rampal, K

2003-01-01

Aims: To determine the relation between sick leave and selected exposure variables among women semiconductor workers. Methods: This was a cross sectional survey of production workers from 18 semiconductor factories. Those selected had to be women, direct production operators up to the level of line leader, and Malaysian citizens. Sick leave and exposure to physical and chemical hazards were determined by self reporting. Three sick leave variables were used; number of sick leave days taken in the past year was the variable of interest in logistic regression models where the effects of age, marital status, work task, work schedule, work section, and duration of work in factory and work section were also explored. Results: Marital status was strongly linked to the taking of sick leave. Age, work schedule, and duration of work in the factory were significant confounders only in certain cases. After adjusting for these confounders, chemical and physical exposures, with the exception of poor ventilation and smelling chemicals, showed no significant relation to the taking of sick leave within the past year. Work section was a good predictor for taking sick leave, as wafer polishing workers faced higher odds of taking sick leave for each of the three cut off points of seven days, three days, and not at all, while parts assembly workers also faced significantly higher odds of taking sick leave. Conclusion: In Malaysia, the wafer fabrication factories only carry out a limited portion of the work processes, in particular, wafer polishing and the processes immediately prior to and following it. This study, in showing higher illness rates for workers in wafer polishing compared to semiconductor assembly, has implications for the governmental policy of encouraging the setting up of wafer fabrication plants with the full range of work processes. PMID:12660374

Spatially-Resolved Influence of Temperature and Salinity on Stock and Recruitment Variability of Commercially Important Fishes in the North Sea.

Directory of Open Access Journals (Sweden)

Anna Akimova

Full Text Available Understanding of the processes affecting recruitment of commercially important fish species is one of the major challenges in fisheries science. Towards this aim, we investigated the relation between North Sea hydrography (temperature and salinity and fish stock variables (recruitment, spawning stock biomass and pre-recruitment survival index for 9 commercially important fishes using spatially-resolved cross-correlation analysis. We used high-resolution (0.2° × 0.2° hydrographic data fields matching the maximal temporal extent of the fish population assessments (1948-2013. Our approach allowed for the identification of regions in the North Sea where environmental variables seem to be more influential on the fish stocks, as well as the regions of a lesser or nil influence. Our results confirmed previously demonstrated negative correlations between temperature and recruitment of cod and plaice and identified regions of the strongest correlations (German Bight for plaice and north-western North Sea for cod. We also revealed a positive correlation between herring spawning stock biomass and temperature in the Orkney-Shetland area, as well as a negative correlation between sole pre-recruitment survival index and temperature in the German Bight. A strong positive correlation between sprat stock variables and salinity in the central North Sea was also found. To our knowledge the results concerning correlations between North Sea hydrography and stocks' dynamics of herring, sole and sprat are novel. The new information about spatial distribution of the correlation provides an additional help to identify mechanisms underlying these correlations. As an illustration of the utility of these results for fishery management, an example is provided that incorporates the identified environmental covariates in stock-recruitment models.

Ultrasonic variables affecting inspection

International Nuclear Information System (INIS)

Lautzenheiser, C.E.; Whiting, A.R.; McElroy, J.T.

1977-01-01

There are many variables which affect the detection of the effects and reproducibility of results when utilizing ultrasonic techniques. The most important variable is the procedure, as this document specifies, to a great extent, the controls that are exercised over the other variables. The most important variable is personnel with regards to training, qualification, integrity, data recording, and data analysis. Although the data is very limited, these data indicate that, if the procedure is carefully controlled, reliability of defect detection and reproducibility of results are both approximately 90 percent for reliability of detection, this applies to relatively small defects as reliability increases substantially as defect size increases above the recording limit. (author)

Risk adjustment models for interhospital comparison of CS rates using Robson's ten group classification system and other socio-demographic and clinical variables.

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Colais, Paola; Fantini, Maria P; Fusco, Danilo; Carretta, Elisa; Stivanello, Elisa; Lenzi, Jacopo; Pieri, Giulia; Perucci, Carlo A

2012-06-21

Caesarean section (CS) rate is a quality of health care indicator frequently used at national and international level. The aim of this study was to assess whether adjustment for Robson's Ten Group Classification System (TGCS), and clinical and socio-demographic variables of the mother and the fetus is necessary for inter-hospital comparisons of CS rates. The study population includes 64,423 deliveries in Emilia-Romagna between January 1, 2003 and December 31, 2004, classified according to theTGCS. Poisson regression was used to estimate crude and adjusted hospital relative risks of CS compared to a reference category. Analyses were carried out in the overall population and separately according to the Robson groups (groups I, II, III, IV and V-X combined). Adjusted relative risks (RR) of CS were estimated using two risk-adjustment models; the first (M1) including the TGCS group as the only adjustment factor; the second (M2) including in addition demographic and clinical confounders identified using a stepwise selection procedure. Percentage variations between crude and adjusted RRs by hospital were calculated to evaluate the confounding effect of covariates. The percentage variations from crude to adjusted RR proved to be similar in M1 and M2 model. However, stratified analyses by Robson's classification groups showed that residual confounding for clinical and demographic variables was present in groups I (nulliparous, single, cephalic, ≥37 weeks, spontaneous labour) and III (multiparous, excluding previous CS, single, cephalic, ≥37 weeks, spontaneous labour) and IV (multiparous, excluding previous CS, single, cephalic, ≥37 weeks, induced or CS before labour) and to a minor extent in groups II (nulliparous, single, cephalic, ≥37 weeks, induced or CS before labour) and IV (multiparous, excluding previous CS, single, cephalic, ≥37 weeks, induced or CS before labour). The TGCS classification is useful for inter-hospital comparison of CS section rates, but

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations

Science.gov (United States)

Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

2018-02-01

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Does Anaemia Have Major Public Health Importance in Children Aged 6-59 Months in the Duggina Fanigo District of Wolaita Zone, Southern Ethiopia?

Science.gov (United States)

Tiku, Yohannes Samuel; Mekonnen, Tefera Chane; Workie, Shimelash Bitew; Amare, Endale

2018-01-01

Globally, a large number of children aged 6-59 months are affected by anaemia. In Ethiopia, like other developing countries, more than 40% of children under 5 years are affected by anaemia. Anaemia during infancy and childhood period is associated with poor health and impaired cognitive development, leading to reduced academic achievement and earning potential in their adult life. The aim of this research was to assess whether anaemia remained a major public health problem among children aged 6-59 months or not in Duggina Fanigo District of Wolaita Zone, South Ethiopia in 2016. A community-based cross-sectional study was conducted from February to March 2016, on 404 mothers with children aged 6-59 months who were selected through the systematic sampling method. Socio-demographic and other data on associated factors was collected using a pre-tested questionnaire. Capillary blood was taken from the fingertip of each child and hemoglobin was measured using Haemo-Cue digital photometer. All the necessary safety measures were taken during blood collection. Data analysis was made using SPSS version 21. Multivariable logistic regression analysis was used to assess the association of independent variables with outcome variables and to control the possible confounding factors. The overall prevalence of anaemia was 51.4%. Anaemia was common among young children as compared to older children. After controlling the effect of confounding and adjusting for age, gender and altitude, explanatory variables like low dietary diversity (AOR = 3.24; 95% CI [1.68-6.23]), food insecurity (AOR = 3.63; 95% CI [2.18-6.04]), stunting (AOR = 2.60; 95% CI [1.56-4.35]), underweight (AOR = 2.46; 95% CI [1.29-4.67]) and fever within 2 weeks (AOR = 2.49; 95% CI [1.29-4.81]) prior to the survey were significantly associated with anaemia. In conclusion, the overall prevalence of anaemia among children aged 6-59 months has remained a major public health importance in the study area. Integrated

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

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Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Intratumoral heterogeneity as a confounding factor in clonogenic assays for tumour radioresponsiveness

International Nuclear Information System (INIS)

Britten, R.A.; Evans, A.J.; Allalunis-Turner, M.J.; Franko, A.J.; Pearcey, R.G.

1996-01-01

The level of intra-tumoral heterogeneity of cellular radiosensitivity within primary cultures of three carcinomas of the cervix has been established. All three cultures contained clones that varied by as much as 3-fold in their clinically relevant radiosensitivity (SF 2 ). The level of intra-tumoral heterogeneity observed in these cervical tumour cultures was sufficient to be a major confounding factor to the use of pre-treatment assessments of radiosensitivity to predict for clinical radioresponsiveness. Mathematical modeling of the relative elimination of the tumour clones during fractionated radiotherapy indicates that, in two of the three biopsy samples, the use of pre-treatment derived SF 2 values from the heterogeneous tumour sample would significantly overestimate radioresponsiveness. We conclude that assays of cellular radiosensitivity that identify the radiosensitivity of the most radioresistant clones and measure their relative abundance could potentially increase the effectiveness of SF 2 values as a predictive marker of radioresponsiveness

Combined Pulmonary Fibrosis and Emphysema in Scleroderma-Related Lung Disease Has a Major Confounding Effect on Lung Physiology and Screening for Pulmonary Hypertension.

Science.gov (United States)

Antoniou, K M; Margaritopoulos, G A; Goh, N S; Karagiannis, K; Desai, S R; Nicholson, A G; Siafakas, N M; Coghlan, J G; Denton, C P; Hansell, D M; Wells, A U

2016-04-01

To assess the prevalence of combined pulmonary fibrosis and emphysema (CPFE) in systemic sclerosis (SSc) patients with interstitial lung disease (ILD) and the effect of CPFE on the pulmonary function tests used to evaluate the severity of SSc-related ILD and the likelihood of pulmonary hypertension (PH). High-resolution computed tomography (HRCT) scans were obtained in 333 patients with SSc-related ILD and were evaluated for the presence of emphysema and the extent of ILD. The effects of emphysema on the associations between pulmonary function variables and the extent of SSc-related ILD as visualized on HRCT and echocardiographic evidence of PH were quantified. Emphysema was present in 41 (12.3%) of the 333 patients with SSc-related ILD, in 26 (19.7%) of 132 smokers, and in 15 (7.5%) of 201 lifelong nonsmokers. When the extent of fibrosis was taken into account, emphysema was associated with significant additional differences from the expected values for diffusing capacity for carbon monoxide (DLco) (average reduction of 24.1%; P emphysema had a greater effect than echocardiographically determined PH on the FVC/DLco ratio, regardless of whether it was analyzed as a continuous variable or using a threshold value of 1.6 or 2.0. Among patients with SSc-related ILD, emphysema is sporadically present in nonsmokers and is associated with a low pack-year history in smokers. The confounding effect of CPFE on measures of gas exchange has major implications for the construction of screening algorithms for PH in patients with SSc-related ILD. © 2016, American College of Rheumatology.

Estimating the monetary value of willingness to pay for E-book reader's attributes using partially confounded factorial conjoint choice experiment

Science.gov (United States)

Yong, Chin-Khian

2013-09-01

A partially confounded factorial conjoint choice experiments design was used to examine the monetary value of the willingness to pay for E-book Reader's attributes. Conjoint analysis is an efficient, cost-effective, and most widely used quantitative method in marketing research to understand consumer preferences and value trade-off. Value can be interpreted by customer or consumer as the received of multiple benefits from a price that was paid. The monetary value of willingness to pay for battery life, internal memory, external memory, screen size, text to Speech, touch screen, and converting handwriting to digital text of E-book reader were estimated in this study. Due to the significant interaction effect of the attributes with the price, the monetary values for the seven attributes were found to be different at different values of odds of purchasing versus not purchasing. The significant interactions effects were one of the main contribution of the partially confounded factorial conjoint choice experiment.

Importance of predictor variables for models of chemical function

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U.S. Environmental Protection Agency — Importance of random forest predictors for all classification models of chemical function. This dataset is associated with the following publication: Isaacs , K., M....

Evaluating disease management programme effectiveness: an introduction to instrumental variables.

Science.gov (United States)

Linden, Ariel; Adams, John L

2006-04-01

This paper introduces the concept of instrumental variables (IVs) as a means of providing an unbiased estimate of treatment effects in evaluating disease management (DM) programme effectiveness. Model development is described using zip codes as the IV. Three diabetes DM outcomes were evaluated: annual diabetes costs, emergency department (ED) visits and hospital days. Both ordinary least squares (OLS) and IV estimates showed a significant treatment effect for diabetes costs (P = 0.011) but neither model produced a significant treatment effect for ED visits. However, the IV estimate showed a significant treatment effect for hospital days (P = 0.006) whereas the OLS model did not. These results illustrate the utility of IV estimation when the OLS model is sensitive to the confounding effect of hidden bias.

Weighty data: importance information influences estimated weight of digital information storage devices.

Directory of Open Access Journals (Sweden)

Iris eSchneider

2015-01-01

Full Text Available Previous work has suggested that perceived importance of an object influences estimates of its weight. Specifically, important books were estimated to be heavier than non-important books. However, the experimental set-up of these studies may have suffered from a potential confound and findings may be confined to books only. Addressing this, we investigate the effect of importance on weight estimates by examining whether the importance of information stored on a data storage device (USB-stick or portable hard drive can alter weight estimates. Results show that people thinking a USB-stick holds important tax information (vs. expired vs. no information estimate it to be heavier (Experiment 1 compared to people who do not. Similarly, people who are told a portable hard-drive holds personally relevant information (vs. irrelevant, also estimate the drive to be heavier (Experiment 2a and 2b. The current work shows that importance influences weight perceptions beyond specific objects.

The importance of variables and parameters in radiolytic chemical kinetics modeling

International Nuclear Information System (INIS)

Piepho, M.G.; Turner, P.J.; Reimus, P.W.

1989-01-01

Many of the pertinent radiochemical reactions are not completely understood, and most of the associated rate constants are poorly characterized. To help identify the important radiochemical reactions, rate constants, species, and environmental conditions, an importance theory code, SWATS (Sensitivitiy With Adjoint Theory-Sparse version)-LOOPCHEM, has been developed for the radiolytic chemical kinetics model in the radiolysis code LOOPCHEM. The LOOPCHEM code calculates the concentrations of various species in a radiolytic field over time. The SWATS-LOOPCHEM code efficiently calculates: the importance (relative to a defined response of interest) of each species concentration over time, the sensitivity of each parameter of interest, and the importance of each equation in the radiolysis model. The calculated results will be used to guide future experimental and modeling work for determining the importance of radiolysis on waste package performance. A demonstration (the importance of selected concentrations and the sensitivities of selected parameters) of the SWATS-LOOPCHEM code is provided for illustrative purposes

High Levels of Sample-to-Sample Variation Confound Data Analysis for Non-Invasive Prenatal Screening of Fetal Microdeletions.

Directory of Open Access Journals (Sweden)

Tianjiao Chu

Full Text Available Our goal was to test the hypothesis that inter-individual genomic copy number variation in control samples is a confounding factor in the non-invasive prenatal detection of fetal microdeletions via the sequence-based analysis of maternal plasma DNA. The database of genomic variants (DGV was used to determine the "Genomic Variants Frequency" (GVF for each 50kb region in the human genome. Whole genome sequencing of fifteen karyotypically normal maternal plasma and six CVS DNA controls samples was performed. The coefficient of variation of relative read counts (cv.RTC for these samples was determined for each 50kb region. Maternal plasma from two pregnancies affected with a chromosome 5p microdeletion was also sequenced, and analyzed using the GCREM algorithm. We found strong correlation between high variance in read counts and GVF amongst controls. Consequently we were unable to confirm the presence of the microdeletion via sequencing of maternal plasma samples obtained from two sequential affected pregnancies. Caution should be exercised when performing NIPT for microdeletions. It is vital to develop our understanding of the factors that impact the sensitivity and specificity of these approaches. In particular, benign copy number variation amongst controls is a major confounder, and their effects should be corrected bioinformatically.

Associations between lifestyle and air pollution exposure: Potential for confounding in large administrative data cohorts.

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Strak, Maciej; Janssen, Nicole; Beelen, Rob; Schmitz, Oliver; Karssenberg, Derek; Houthuijs, Danny; van den Brink, Carolien; Dijst, Martin; Brunekreef, Bert; Hoek, Gerard

2017-07-01

Cohorts based on administrative data have size advantages over individual cohorts in investigating air pollution risks, but often lack in-depth information on individual risk factors related to lifestyle. If there is a correlation between lifestyle and air pollution, omitted lifestyle variables may result in biased air pollution risk estimates. Correlations between lifestyle and air pollution can be induced by socio-economic status affecting both lifestyle and air pollution exposure. Our overall aim was to assess potential confounding by missing lifestyle factors on air pollution mortality risk estimates. The first aim was to assess associations between long-term exposure to several air pollutants and lifestyle factors. The second aim was to assess whether these associations were sensitive to adjustment for individual and area-level socioeconomic status (SES), and whether they differed between subgroups of the population. Using the obtained air pollution-lifestyle associations and indirect adjustment methods, our third aim was to investigate the potential bias due to missing lifestyle information on air pollution mortality risk estimates in administrative cohorts. We used a recent Dutch national health survey of 387,195 adults to investigate the associations of PM 10 , PM 2.5 , PM 2.5-10 , PM 2.5 absorbance, OP DTT, OP ESR and NO 2 annual average concentrations at the residential address from land use regression models with individual smoking habits, alcohol consumption, physical activity and body mass index. We assessed the associations with and without adjustment for neighborhood and individual SES characteristics typically available in administrative data cohorts. We illustrated the effect of including lifestyle information on the air pollution mortality risk estimates in administrative cohort studies using a published indirect adjustment method. Current smoking and alcohol consumption were generally positively associated with air pollution. Physical activity

On the importance of being bilingual: word stress processing in a context of segmental variability.

Science.gov (United States)

Abboub, Nawal; Bijeljac-Babic, Ranka; Serres, Josette; Nazzi, Thierry

2015-04-01

French-learning infants have language-specific difficulties in processing lexical stress due to the lack of lexical stress in French. These difficulties in discriminating between words with stress-initial (trochaic) and stress-final (iambic) patterns emerge by 10months of age in the easier context of low variability (using a single item pronounced with a trochaic pattern vs. an iambic pattern) as well as in the more challenging context of high segmental variability (using lists of segmentally different trochaic and iambic items). These findings raise the question of stress pattern perception in simultaneous bilinguals learning French and a second language using stress at the lexical level. Bijeljac-Babic, Serres, Höhle, and Nazzi (2012) established that at 10 months of age, in the simpler context of low variability, such bilinguals have better stress discrimination abilities than French-learning monolinguals. The current study explored whether this advantage extends to the more challenging context of high segmental variability. Results first establish stress pattern discrimination in a group of bilingual 10-month-olds learning French and one language with (variable) lexical stress, but not in French-learning 10-month-old monolinguals. Second, discrimination in bilinguals appeared not to be affected by the language balance of the infants, suggesting that sensitivity to stress patterns might be maintained in these bilingual infants provided that they hear at least 30% of a language with lexical stress. Copyright © 2014 Elsevier Inc. All rights reserved.

Examination of the Relationship between Oral Health and Arterial Sclerosis without Genetic Confounding through the Study of Older Japanese Twins.

Directory of Open Access Journals (Sweden)

Yuko Kurushima

Full Text Available Although researchers have recently demonstrated a relationship between oral health and arterial sclerosis, the genetic contribution to this relationship has been ignored even though genetic factors are expected to have some effect on various diseases. The aim of this study was to evaluate oral health as a significant risk factor related to arterial sclerosis after eliminating genetic confounding through study of older Japanese twins.Medical and dental surveys were conducted individually for 106 Japanese twin pairs over the age of 50 years. Maximal carotid intima-media thickness (IMT-Cmax was measured as a surrogate marker of arterial sclerosis. IMT-Cmax > 1.0 mm was diagnosed as arterial sclerosis. All of the twins were examined for the number of remaining teeth, masticatory performance, and periodontal status. We evaluated each measurement related with IMT-Cmax and arterial sclerosis using generalized estimating equations analysis adjusted for potential risk factors. For non-smoking monozygotic twins, a regression analysis using a "between within" model was conducted to evaluate the relationship between IMT-Cmax and the number of teeth as the environmental factor controlling genetic and familial confounding.We examined 91 monozygotic and 15 dizygotic twin pairs (males: 42, females: 64 with a mean (± standard deviation age of 67.4 ± 10.0 years. Out of all of the oral health-related measurements collected, only the number of teeth was significantly related to arterial sclerosis (odds ratio: 0.72, 95% confidence interval: 0.52-0.99 per five teeth. Regression analysis showed a significant association between the IMT-Cmax and the number of teeth as an environmental factor (p = 0.037.Analysis of monozygotic twins older than 50 years of age showed that having fewer teeth could be a significant environmental factor related to arterial sclerosis, even after controlling for genetic and familial confounding.

Focus on variability : New tools to study intra-individual variability in developmental data

NARCIS (Netherlands)

van Geert, P; van Dijk, M

2002-01-01

In accordance with dynamic systems theory, we assume that variability is an important developmental phenomenon. However, the standard methodological toolkit of the developmental psychologist offers few instruments for the study of variability. In this article we will present several new methods that

Variability: A Pernicious Hypothesis.

Science.gov (United States)

Noddings, Nel

1992-01-01

The hypothesis of greater male variability in test results is discussed in its historical context, and reasons feminists have objected to the hypothesis are considered. The hypothesis acquires political importance if it is considered that variability results from biological, rather than cultural, differences. (SLD)

Cataclysmic Variable Stars

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Hellier, Coel

2001-01-01

Cataclysmic variable stars are the most variable stars in the night sky, fluctuating in brightness continually on timescales from seconds to hours to weeks to years. The changes can be recorded using amateur telescopes, yet are also the subject of intensive study by professional astronomers. That study has led to an understanding of cataclysmic variables as binary stars, orbiting so closely that material transfers from one star to the other. The resulting process of accretion is one of the most important in astrophysics. This book presents the first account of cataclysmic variables at an introductory level. Assuming no previous knowledge of the field, it explains the basic principles underlying the variability, while providing an extensive compilation of cataclysmic variable light curves. Aimed at amateur astronomers, undergraduates, and researchers, the main text is accessible to those with no mathematical background, while supplementary boxes present technical details and equations.

Non-Chemical Distant Cellular Interactions as a potential confounder of Cell Biology Experiments

Directory of Open Access Journals (Sweden)

Ashkan eFarhadi

2014-10-01

Full Text Available Distant cells can communicate with each other through a variety of methods. Two such methods involve electrical and/or chemical mechanisms. Non-chemical, distant cellular interactions may be another method of communication that cells can use to modify the behavior of other cells that are mechanically separated. Moreover, non-chemical, distant cellular interactions may explain some cases of confounding effects in Cell Biology experiments. In this article, we review non-chemical, distant cellular interactions studies to try to shed light on the mechanisms in this highly unconventional field of cell biology. Despite the existence of several theories that try to explain the mechanism of non-chemical, distant cellular interactions, this phenomenon is still speculative. Among candidate mechanisms, electromagnetic waves appear to have the most experimental support. In this brief article, we try to answer a few key questions that may further clarify this mechanism.

Complex variables

CERN Document Server

Fisher, Stephen D

1999-01-01

The most important topics in the theory and application of complex variables receive a thorough, coherent treatment in this introductory text. Intended for undergraduates or graduate students in science, mathematics, and engineering, this volume features hundreds of solved examples, exercises, and applications designed to foster a complete understanding of complex variables as well as an appreciation of their mathematical beauty and elegance. Prerequisites are minimal; a three-semester course in calculus will suffice to prepare students for discussions of these topics: the complex plane, basic

The Performance of Variable Annuities

OpenAIRE

Michael J. McNamara; Henry R. Oppenheimer

1991-01-01

Variable annuities have become increasingly important in retirement plans. This paper provides an examination of the investment performance of variable annuities for the period year-end 1973 to year-end 1988. Returns, risk, and selectivity measures are analyzed for the sample of annuities, for individual variable annuities, and for subsamples of annuities with similar portfolio size and turnover. While the investment returns of variable annuities were greater than inflation over the period, t...

Decreased Heart Rate Variability in HIV Positive Patients Receiving Antiretroviral Therapy: Importance of Blood Glucose and Cholesterol

DEFF Research Database (Denmark)

Askgaard, Gro; Kristoffersen, Ulrik Sloth; Mehlsen, Jesper

2011-01-01

whether autonomic dysfunction is present in an ART treated HIV population and if so to identify factors of importance. METHODS: HIV patients receiving ART for at least 12 months (n¿=¿97) and an age-matched control group of healthy volunteers (n¿=¿52) were included. All were non-diabetic and had never......-intervals (RMSSD) or the percent of differences between adjacent NN intervals greater than 50 ms (pNN50). In the HIV positives, haemoglobin A1c correlated inversely with SDNN, RMSSD and pNN50 (pcorrelated inversely with RMSSD and pNN50 (p...4 cell count nor CD4 nadir correlated with time or phase domain HRV variables. CONCLUSIONS: Moderate autonomic dysfunction is present in HIV positives patients even with suppressed viral load due to ART. The dysfunction is correlated with HbA1c and hypercholesterolemia but not to duration of HIV...

Surgery confounds biology: the predictive value of stage-, grade- and prostate-specific antigen for recurrence after radical prostatectomy as a function of surgeon experience.

Science.gov (United States)

Vickers, Andrew J; Savage, Caroline J; Bianco, Fernando J; Klein, Eric A; Kattan, Michael W; Secin, Fernando P; Guilloneau, Bertrand D; Scardino, Peter T

2011-04-01

Statistical models predicting cancer recurrence after surgery are based on biologic variables. We have shown previously that prostate cancer recurrence is related to both tumor biology and to surgical technique. Here, we evaluate the association between several biological predictors and biochemical recurrence across varying surgical experience. The study included two separate cohorts: 6,091 patients treated by open radical prostatectomy and an independent replication set of 2,298 patients treated laparoscopically. We calculated the odds ratios for biological predictors of biochemical recurrence-stage, Gleason grade and prostate-specific antigen (PSA)-and also the predictive accuracy (area under the curve, AUC) of a multivariable model, for subgroups of patients defined by the experience of their surgeon. In the open cohort, the odds ratio for Gleason score 8+ and advanced pathologic stage, though not PSA or Gleason score 7, increased dramatically when patients treated by surgeons with lower levels of experience were excluded (Gleason 8+: odds ratios 5.6 overall vs. 13.0 for patients treated by surgeons with 1,000+ prior cases; locally advanced disease: odds ratios of 6.6 vs. 12.2, respectively). The AUC of the multivariable model was 0.750 for patients treated by surgeons with 50 or fewer cases compared to 0.849 for patients treated by surgeons with 500 or more. Although predictiveness was lower overall for the independent replication set cohort, the main findings were replicated. Surgery confounds biology. Although our findings have no direct clinical implications, studies investigating biological variables as predictors of outcome after curative resection of cancer should consider the impact of surgeon-specific factors. Copyright © 2010 UICC.

Interindividual variability in the dose-specific effect of dopamine on carotid chemoreceptor sensitivity to hypoxia

Science.gov (United States)

Limberg, Jacqueline K.; Johnson, Blair D.; Holbein, Walter W.; Ranadive, Sushant M.; Mozer, Michael T.

2015-01-01

Human studies use varying levels of low-dose (1-4 μg·kg−1·min−1) dopamine to examine peripheral chemosensitivity, based on its known ability to blunt carotid body responsiveness to hypoxia. However, the effect of dopamine on the ventilatory responses to hypoxia is highly variable between individuals. Thus we sought to determine 1) the dose response relationship between dopamine and peripheral chemosensitivity as assessed by the ventilatory response to hypoxia in a cohort of healthy adults, and 2) potential confounding cardiovascular responses at variable low doses of dopamine. Young, healthy adults (n = 30, age = 32 ± 1, 24 male/6 female) were given intravenous (iv) saline and a range of iv dopamine doses (1–4 μg·kg−1·min−1) prior to and throughout five hypoxic ventilatory response (HVR) tests. Subjects initially received iv saline, and after each HVR the dopamine infusion rate was increased by 1 μg·kg−1·min−1. Tidal volume, respiratory rate, heart rate, blood pressure, and oxygen saturation were continuously measured. Dopamine significantly reduced HVR at all doses (P HVR in the high group only (P HVR in the low group (P > 0.05). Dopamine infusion also resulted in a reduction in blood pressure (3 μg·kg−1·min−1) and total peripheral resistance (1–4 μg·kg−1·min−1), driven primarily by subjects with low baseline chemosensitivity. In conclusion, we did not find a single dose of dopamine that elicited a nadir HVR in all subjects. Additionally, potential confounding cardiovascular responses occur with dopamine infusion, which may limit its usage. PMID:26586909

Exome sequencing identifies pathogenic variants of VPS13B in a patient with familial 16p11.2 duplication

OpenAIRE

Dastan, Jila; Chijiwa, Chieko; Tang, Flamingo; Martell, Sally; Qiao, Ying; Rajcan-Separovic, Evica; Lewis, M. E. Suzanne

2016-01-01

Background The recurrent microduplication of 16p11.2 (dup16p11.2) is associated with a broad spectrum of neurodevelopmental disorders (NDD) confounded by incomplete penetrance and variable expressivity. This inter- and intra-familial clinical variability highlights the importance of personalized genetic counselling in individuals at-risk. Case presentation In this study, we performed whole exome sequencing (WES) to look for other genomic alterations that could explain the clinical variability...

Glucose variability negatively impacts long-term functional outcome in patients with traumatic brain injury.

Science.gov (United States)

Matsushima, Kazuhide; Peng, Monica; Velasco, Carlos; Schaefer, Eric; Diaz-Arrastia, Ramon; Frankel, Heidi

2012-04-01

Significant glycemic excursions (so-called glucose variability) affect the outcome of generic critically ill patients but has not been well studied in patients with traumatic brain injury (TBI). The purpose of this study was to evaluate the impact of glucose variability on long-term functional outcome of patients with TBI. A noncomputerized tight glucose control protocol was used in our intensivist model surgical intensive care unit. The relationship between the glucose variability and long-term (a median of 6 months after injury) functional outcome defined by extended Glasgow Outcome Scale (GOSE) was analyzed using ordinal logistic regression models. Glucose variability was defined by SD and percentage of excursion (POE) from the preset range glucose level. A total of 109 patients with TBI under tight glucose control had long-term GOSE evaluated. In univariable analysis, there was a significant association between lower GOSE score and higher mean glucose, higher SD, POE more than 60, POE 80 to 150, and single episode of glucose less than 60 mg/dL but not POE 80 to 110. After adjusting for possible confounding variables in multivariable ordinal logistic regression models, higher SD, POE more than 60, POE 80 to 150, and single episode of glucose less than 60 mg/dL were significantly associated with lower GOSE score. Glucose variability was significantly associated with poorer long-term functional outcome in patients with TBI as measured by the GOSE score. Well-designed protocols to minimize glucose variability may be key in improving long-term functional outcome. Copyright © 2012 Elsevier Inc. All rights reserved.

Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease.

Science.gov (United States)

Rohr, Jason R; Raffel, Thomas R

2010-05-04

The role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial, and the effect of climatic variability, in particular, has largely been ignored. For instance, it was recently revealed that the proposed link between climate change and widespread amphibian declines, putatively caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), was tenuous because it was based on a temporally confounded correlation. Here we provide temporally unconfounded evidence that global El Niño climatic events drive widespread amphibian losses in genus Atelopus via increased regional temperature variability, which can reduce amphibian defenses against pathogens. Of 26 climate variables tested, only factors associated with temperature variability could account for the spatiotemporal patterns of declines thought to be associated with Bd. Climatic predictors of declines became significant only after controlling for a pattern consistent with epidemic spread (by temporally detrending the data). This presumed spread accounted for 59% of the temporal variation in amphibian losses, whereas El Niño accounted for 59% of the remaining variation. Hence, we could account for 83% of the variation in declines with these two variables alone. Given that global climate change seems to increase temperature variability, extreme climatic events, and the strength of Central Pacific El Niño episodes, climate change might exacerbate worldwide enigmatic declines of amphibians, presumably by increasing susceptibility to disease. These results suggest that changes to temperature variability associated with climate change might be as significant to biodiversity losses and disease emergence as changes to mean temperature.

Variable selection by lasso-type methods

Directory of Open Access Journals (Sweden)

Sohail Chand

2011-09-01

Full Text Available Variable selection is an important property of shrinkage methods. The adaptive lasso is an oracle procedure and can do consistent variable selection. In this paper, we provide an explanation that how use of adaptive weights make it possible for the adaptive lasso to satisfy the necessary and almost sufcient condition for consistent variable selection. We suggest a novel algorithm and give an important result that for the adaptive lasso if predictors are normalised after the introduction of adaptive weights, it makes the adaptive lasso performance identical to the lasso.

Impact of menstruation on select hematology and clinical chemistry variables in cynomolgus macaques.

Science.gov (United States)

Perigard, Christopher J; Parrula, M Cecilia M; Larkin, Matthew H; Gleason, Carol R

2016-06-01

In preclinical studies with cynomolgus macaques, it is common to have one or more females presenting with menses. Published literature indicates that the blood lost during menses causes decreases in red blood cell mass variables (RBC, HGB, and HCT), which would be a confounding factor in the interpretation of drug-related effects on clinical pathology data, but no scientific data have been published to support this claim. This investigation was conducted to determine if the amount of blood lost during menses in cynomolgus macaques has an effect on routine hematology and serum chemistry variables. Ten female cynomolgus macaques (Macaca fascicularis), 5 to 6.5 years old, were observed daily during approximately 3 months (97 days) for the presence of menses. Hematology and serum chemistry variables were evaluated twice weekly. The results indicated that menstruation affects the erythrogram including RBC, HGB, HCT, MCHC, MCV, reticulocyte count, RDW, the leukogram including neutrophil, lymphocyte, and monocyte counts, and chemistry variables, including GGT activity, and the concentrations of total proteins, albumin, globulins, and calcium. The magnitude of the effect of menstruation on susceptible variables is dependent on the duration of the menstrual phase. Macaques with menstrual phases lasting ≥ 7 days are more likely to develop changes in variables related to chronic blood loss. In preclinical toxicology studies with cynomolgus macaques, interpretation of changes in several commonly evaluated hematology and serum chemistry variables requires adequate clinical observation and documentation concerning presence and duration of menses. There is a concern that macaques with long menstrual cycles can develop iron deficiency anemia due to chronic menstrual blood loss. © 2016 American Society for Veterinary Clinical Pathology.

Correlation between radon level and confounders of cancer. A note on epidemiological inference at low doses

International Nuclear Information System (INIS)

Hajnal, M.A.; Toth, E.; Hamori, K.; Minda, M.; Koteles, Gy.J.

2007-01-01

Complete text of publication follows. Objective. The aim of this study was to examine and further clarify the extent of radon and progeny induced carcinogenesis, both separated from and combined with other confounders and health risk factors. This work was financed by National Development Agency, Hungary, with GVOP-3.1.1.-2004-05-0384/3.0. Methods. A case-control study was conducted in a Hungarian countryside region where the proportion of houses with yearly average radon level above 200 Bq.m -3 was estimated to be higher than 20% by our preceding regional surveys. Radon levels were measured with CR39 closed etched detectors for three seasons separately yielding yearly average by estimating the low summer level. The detectors were placed in the bedrooms, where people were expected to spend one third of a day. 520 patients with diagnosed cancers were included in these measurements, amongst which 77 developed lung or respiratory cancers. The control group consisted 6333 individuals, above 30 years of age. Lifestyle risk factors of cancers were collected by surveys including social status, pollution from indoor heating, smoking and alcohol history, nutrition, exercise and mental health index 5. Except smoking and alcohol habits, these cofactors were only available for the control group. Comparing disease occurrences the authors selected the multivariate generalised linear models. The case and control proportions along a given factor are binomially distributed, thus the logit link function was used. For radon both log and linear terms were probed for. Results. Many known health confounders of cancers correlated with radon levels, with an estimated total net increase of 50-150 Bq m -3 with increased risks. For lung cancers the model with the terms radon, age, gender and smoking was found to have the lowest Akaike Information Criterion (AIC). Heavy dependency on age, gender and smoking contribute largely to observed lung cancer incidence. However log linear relationship

Phenology and growth adjustments of oil palm (Elaeis guineensis) to photoperiod and climate variability.

Science.gov (United States)

Legros, S; Mialet-Serra, I; Caliman, J-P; Siregar, F A; Clément-Vidal, A; Dingkuhn, M

2009-11-01

Oil palm flowering and fruit production show seasonal maxima whose causes are unknown. Drought periods confound these rhythms, making it difficult to analyse or predict dynamics of production. The present work aims to analyse phenological and growth responses of adult oil palms to seasonal and inter-annual climatic variability. Two oil palm genotypes planted in a replicated design at two sites in Indonesia underwent monthly observations during 22 months in 2006-2008. Measurements included growth of vegetative and reproductive organs, morphology and phenology. Drought was estimated from climatic water balance (rainfall - potential evapotranspiration) and simulated fraction of transpirable soil water. Production history of the same plants for 2001-2005 was used for inter-annual analyses. Drought was absent at the equatorial Kandista site (0 degrees 55'N) but the Batu Mulia site (3 degrees 12'S) had a dry season with variable severity. Vegetative growth and leaf appearance rate fluctuated with drought level. Yield of fruit, a function of the number of female inflorescences produced, was negatively correlated with photoperiod at Kandista. Dual annual maxima were observed supporting a recent theory of circadian control. The photoperiod-sensitive phases were estimated at 9 (or 9 + 12 x n) months before bunch maturity for a given phytomer. The main sensitive phase for drought effects was estimated at 29 months before bunch maturity, presumably associated with inflorescence sex determination. It is assumed that seasonal peaks of flowering in oil palm are controlled even near the equator by photoperiod response within a phytomer. These patterns are confounded with drought effects that affect flowering (yield) with long time-lag. Resulting dynamics are complex, but if the present results are confirmed it will be possible to predict them with models.

Variable and subset selection in PLS regression

DEFF Research Database (Denmark)

Høskuldsson, Agnar

2001-01-01

The purpose of this paper is to present some useful methods for introductory analysis of variables and subsets in relation to PLS regression. We present here methods that are efficient in finding the appropriate variables or subset to use in the PLS regression. The general conclusion...... is that variable selection is important for successful analysis of chemometric data. An important aspect of the results presented is that lack of variable selection can spoil the PLS regression, and that cross-validation measures using a test set can show larger variation, when we use different subsets of X, than...

Using variable combination population analysis for variable selection in multivariate calibration.

Science.gov (United States)

Yun, Yong-Huan; Wang, Wei-Ting; Deng, Bai-Chuan; Lai, Guang-Bi; Liu, Xin-bo; Ren, Da-Bing; Liang, Yi-Zeng; Fan, Wei; Xu, Qing-Song

2015-03-03

Variable (wavelength or feature) selection techniques have become a critical step for the analysis of datasets with high number of variables and relatively few samples. In this study, a novel variable selection strategy, variable combination population analysis (VCPA), was proposed. This strategy consists of two crucial procedures. First, the exponentially decreasing function (EDF), which is the simple and effective principle of 'survival of the fittest' from Darwin's natural evolution theory, is employed to determine the number of variables to keep and continuously shrink the variable space. Second, in each EDF run, binary matrix sampling (BMS) strategy that gives each variable the same chance to be selected and generates different variable combinations, is used to produce a population of subsets to construct a population of sub-models. Then, model population analysis (MPA) is employed to find the variable subsets with the lower root mean squares error of cross validation (RMSECV). The frequency of each variable appearing in the best 10% sub-models is computed. The higher the frequency is, the more important the variable is. The performance of the proposed procedure was investigated using three real NIR datasets. The results indicate that VCPA is a good variable selection strategy when compared with four high performing variable selection methods: genetic algorithm-partial least squares (GA-PLS), Monte Carlo uninformative variable elimination by PLS (MC-UVE-PLS), competitive adaptive reweighted sampling (CARS) and iteratively retains informative variables (IRIV). The MATLAB source code of VCPA is available for academic research on the website: http://www.mathworks.com/matlabcentral/fileexchange/authors/498750. Copyright © 2015 Elsevier B.V. All rights reserved.

The importance of recording physical and chemical variables simultaneously with remote radiological surveillance of aquatic systems: a perspective for environmental modelling

International Nuclear Information System (INIS)

Abril, J.M.; El-Mrabet, R.; Barros, H.

2004-01-01

Modern nuclear metrological tools allow the remote surveillance of the radiological status of the aquatic systems, providing an important advance in the protection of the environment. Nevertheless, the significance of the radiological data could be highly improved through simultaneous recording of physical and chemical variables that govern the behaviour and bioavailability of radionuclides in these aquatic systems. This work reviews some of these variables from the point of view of the environmental modelling. The amount, nature and dynamics of the suspended loads and bottom sediments strongly influence the behaviour of particle-reactive radionuclides. The kinetics of this process has a very fast component, as it is shown from our recent studies with 241 Am, 239 Pu and 133 Ba in several aquatic systems from southern Spain. Changes in pH, temperature and in the electrical conductivity are influencing the uptake kinetics and the final partitioning of the radioactivity. Water currents govern the radionuclide transport and dispersion. These points are illustrated with modelling exercises in the scenarios of the Suez Canal (Egypt) and the Haersvatten Lake (Sweden)

Anxiety disorders are associated with reduced heart rate variability: A meta-analysis

Directory of Open Access Journals (Sweden)

John eChalmers

2014-07-01

Full Text Available Background: Anxiety disorders increase risk of future cardiovascular disease (CVD and mortality, even after controlling for confounds including smoking, lifestyle, and socioeconomic status, and irrespective of a history of medical disorders. While impaired vagal function, indicated by reductions in heart rate variability (HRV, may be one mechanism linking anxiety disorders to CVD, prior studies have reported inconsistent findings highlighting the need for meta-analysis.Method: Studies comparing resting state HRV recordings in patients with an anxiety disorder as a primary diagnosis and healthy controls were considered for meta-analysis. Results: Meta-analyses were based on 36 articles, including 2086 patients with an anxiety disorder and 2294 controls. Overall, anxiety disorders were characterised by lower HRV (high frequency: Hedges’ g = -.29. 95%CI: -.41 to -.17, p < 0.001; time domain: Hedges’ g = -0.45, 95%CI: -0.57 to -0.33, p < .001 than controls. Panic Disorder (n=447, Post-Traumatic Stress Disorder (n=192, Generalized Anxiety Disorder (n=68, and Social anxiety disorder (n=90, but not Obsessive Compulsive Disorder (n=40, displayed reductions in high frequency HRV relative to controls (all ps < .001. Conclusions: Anxiety disorders are associated with reduced HRV, findings associated with a small to moderate effect size. Findings have important implications for future physical health and wellbeing of patients, highlighting a need for comprehensive cardiovascular risk reduction.

Confounding factors and genetic polymorphism in the evaluation of individual steroid profiling

Science.gov (United States)

Kuuranne, Tiia; Saugy, Martial; Baume, Norbert

2014-01-01

In the fight against doping, steroid profiling is a powerful tool to detect drug misuse with endogenous anabolic androgenic steroids. To establish sensitive and reliable models, the factors influencing profiling should be recognised. We performed an extensive literature review of the multiple factors that could influence the quantitative levels and ratios of endogenous steroids in urine matrix. For a comprehensive and scientific evaluation of the urinary steroid profile, it is necessary to define the target analytes as well as testosterone metabolism. The two main confounding factors, that is, endogenous and exogenous factors, are detailed to show the complex process of quantifying the steroid profile within WADA-accredited laboratories. Technical aspects are also discussed as they could have a significant impact on the steroid profile, and thus the steroid module of the athlete biological passport (ABP). The different factors impacting the major components of the steroid profile must be understood to ensure scientifically sound interpretation through the Bayesian model of the ABP. Not only should the statistical data be considered but also the experts in the field must be consulted for successful implementation of the steroidal module. PMID:24764553

Importance and Impact of Preanalytical Variables on Alzheimer Disease Biomarker Concentrations in Cerebrospinal Fluid

NARCIS (Netherlands)

Le Bastard, Nathalie; De Deyn, Peter Paul; Engelborghs, Sebastiaan

BACKGROUND: Analyses of cerebrospinal fluid (CSF) biomarkers (beta-amyloid protein, total tau protein, and hyperphosphorylated tau protein) are part of the diagnostic criteria of Alzheimer disease. Different preanalytical sample procedures contribute to variability of CSF biomarker concentrations,

Desire thinking as a confounder in the relationship between mindfulness and craving: Evidence from a cross-cultural validation of the Desire Thinking Questionnaire.

Science.gov (United States)

Chakroun-Baggioni, Nadia; Corman, Maya; Spada, Marcantonio M; Caselli, Gabriele; Gierski, Fabien

2017-10-01

Desire thinking and mindfulness have been associated with craving. The aim of the present study was to validate the French version of the Desire Thinking Questionnaire (DTQ) and to investigate the relationship between mindfulness, desire thinking and craving among a sample of university students. Four hundred and ninety six university students completed the DTQ and measures of mindfulness, craving and alcohol use. Results from confirmatory factor analyses showed that the two-factor structure proposed in the original DTQ exhibited suitable goodness-of-fit statistics. The DTQ also demonstrated good internal reliability, temporal stability and predictive validity. A set of linear regressions revealed that desire thinking had a confounding effect in the relationship between mindfulness and craving. The confounding role of desire thinking in the relationship between mindfulness and craving suggests that interrupting desire thinking may be a viable clinical option aimed at reducing craving. Copyright © 2017 Elsevier B.V. All rights reserved.

Climate variability and climate change

International Nuclear Information System (INIS)

Rind, D.

1990-01-01

Changes of variability with climate change are likely to have a substantial impact on vegetation and society, rivaling the importance of changes in the mean values themselves. A variety of paleoclimate and future climate simulations performed with the GISS global climate model is used to assess how the variabilities of temperature and precipitation are altered as climate warms or cools. In general, as climate warms, temperature variability decreases due to reductions in the latitudinal temperature gradient and precipitation variability increases together with the intensity of the hydrologic cycle. If future climate projections are accurate, the reduction in temperature variability will be minimized by the rapid change in mean temperatures, but the hydrologic variability will be amplified by increased evapotranspiration. Greater hydrologic variability would appear to pose a potentially severe problem for the next century

Associations of Perfluoroalkyl Substances (PFAS) with Lower Birth Weight: An Evaluation of Potential Confounding by Glomerular Filtration Rate Using a Physiologically Based Pharmacokinetic Model (PBPK).

Science.gov (United States)

Verner, Marc-André; Loccisano, Anne E; Morken, Nils-Halvdan; Yoon, Miyoung; Wu, Huali; McDougall, Robin; Maisonet, Mildred; Marcus, Michele; Kishi, Reiko; Miyashita, Chihiro; Chen, Mei-Huei; Hsieh, Wu-Shiun; Andersen, Melvin E; Clewell, Harvey J; Longnecker, Matthew P

2015-12-01

Prenatal exposure to perfluoroalkyl substances (PFAS) has been associated with lower birth weight in epidemiologic studies. This association could be attributable to glomerular filtration rate (GFR), which is related to PFAS concentration and birth weight. We used a physiologically based pharmacokinetic (PBPK) model of pregnancy to assess how much of the PFAS-birth weight association observed in epidemiologic studies might be attributable to GFR. We modified a PBPK model to reflect the association of GFR with birth weight (estimated from three studies of GFR and birth weight) and used it to simulate PFAS concentrations in maternal and cord plasma. The model was run 250,000 times, with variation in parameters, to simulate a population. Simulated data were analyzed to evaluate the association between PFAS levels and birth weight due to GFR. We compared simulated estimates with those from a meta-analysis of epidemiologic data. The reduction in birth weight for each 1-ng/mL increase in simulated cord plasma for perfluorooctane sulfonate (PFOS) was 2.72 g (95% CI: -3.40, -2.04), and for perfluorooctanoic acid (PFOA) was 7.13 g (95% CI: -8.46, -5.80); results based on maternal plasma at term were similar. Results were sensitive to variations in PFAS level distributions and the strength of the GFR-birth weight association. In comparison, our meta-analysis of epidemiologic studies suggested that each 1-ng/mL increase in prenatal PFOS and PFOA levels was associated with 5.00 g (95% CI: -21.66, -7.78) and 14.72 g (95% CI: -8.92, -1.09) reductions in birth weight, respectively. Results of our simulations suggest that a substantial proportion of the association between prenatal PFAS and birth weight may be attributable to confounding by GFR and that confounding by GFR may be more important in studies with sample collection later in pregnancy.

Determination of Causality between Remittance and Import: Evidence from Bangladesh

Directory of Open Access Journals (Sweden)

Dewan Muktadir-Al-Mukit

2013-07-01

Full Text Available This study investigates the relationship between remittance and import for the economy of Bangladesh. The study used different econometric techniques of measuring the long and short term relationship between variables. The Johansen Cointegration test is used to determine the existence of a long term relationships between study variables. The normalized Cointegrating coefficients are found statistically significant and show a stable and positive relationship between study variables. Our Granger causality analysis suggests the existence of a unidirectional causality running from import to remittance. This confirms that remittances have no significant impact on the demand for imported goods rather import exerts a positive shock on the remittance of Bangladesh.

Dynamic Variability of Isometric Action Tremor in Precision Pinching

Directory of Open Access Journals (Sweden)

Tim Eakin

2012-01-01

Full Text Available Evolutionary development of isometric force impulse frequencies, power, and the directional concordance of changes in oscillatory tremor during performance of a two-digit force regulation task was examined. Analyses compared a patient group having tremor confounding volitional force regulation with a control group having no neuropathological diagnosis. Dependent variables for tremor varied temporally and spatially, both within individual trials and across trials, across individuals, across groups, and between digits. Particularly striking findings were magnitude increases during approaches to cue markers and shifts in the concordance phase from pinching toward rigid sway patterns as the magnitude increased. Magnitudes were significantly different among trace line segments of the task and were characterized by differences in relative force required and by the task progress with respect to cue markers for beginning, reversing force change direction, or task termination. The main systematic differences occurred during cue marker approach and were independent of trial sequence order.

Interindividual variability in the dose-specific effect of dopamine on carotid chemoreceptor sensitivity to hypoxia.

Science.gov (United States)

Limberg, Jacqueline K; Johnson, Blair D; Holbein, Walter W; Ranadive, Sushant M; Mozer, Michael T; Joyner, Michael J

2016-01-15

Human studies use varying levels of low-dose (1-4 μg·kg(-1)·min(-1)) dopamine to examine peripheral chemosensitivity, based on its known ability to blunt carotid body responsiveness to hypoxia. However, the effect of dopamine on the ventilatory responses to hypoxia is highly variable between individuals. Thus we sought to determine 1) the dose response relationship between dopamine and peripheral chemosensitivity as assessed by the ventilatory response to hypoxia in a cohort of healthy adults, and 2) potential confounding cardiovascular responses at variable low doses of dopamine. Young, healthy adults (n = 30, age = 32 ± 1, 24 male/6 female) were given intravenous (iv) saline and a range of iv dopamine doses (1-4 μg·kg(-1)·min(-1)) prior to and throughout five hypoxic ventilatory response (HVR) tests. Subjects initially received iv saline, and after each HVR the dopamine infusion rate was increased by 1 μg·kg(-1)·min(-1). Tidal volume, respiratory rate, heart rate, blood pressure, and oxygen saturation were continuously measured. Dopamine significantly reduced HVR at all doses (P HVR in the high group only (P HVR in the low group (P > 0.05). Dopamine infusion also resulted in a reduction in blood pressure (3 μg·kg(-1)·min(-1)) and total peripheral resistance (1-4 μg·kg(-1)·min(-1)), driven primarily by subjects with low baseline chemosensitivity. In conclusion, we did not find a single dose of dopamine that elicited a nadir HVR in all subjects. Additionally, potential confounding cardiovascular responses occur with dopamine infusion, which may limit its usage. Copyright © 2016 the American Physiological Society.

Physical attraction to reliable, low variability nervous systems: Reaction time variability predicts attractiveness.

Science.gov (United States)

Butler, Emily E; Saville, Christopher W N; Ward, Robert; Ramsey, Richard

2017-01-01

The human face cues a range of important fitness information, which guides mate selection towards desirable others. Given humans' high investment in the central nervous system (CNS), cues to CNS function should be especially important in social selection. We tested if facial attractiveness preferences are sensitive to the reliability of human nervous system function. Several decades of research suggest an operational measure for CNS reliability is reaction time variability, which is measured by standard deviation of reaction times across trials. Across two experiments, we show that low reaction time variability is associated with facial attractiveness. Moreover, variability in performance made a unique contribution to attractiveness judgements above and beyond both physical health and sex-typicality judgements, which have previously been associated with perceptions of attractiveness. In a third experiment, we empirically estimated the distribution of attractiveness preferences expected by chance and show that the size and direction of our results in Experiments 1 and 2 are statistically unlikely without reference to reaction time variability. We conclude that an operating characteristic of the human nervous system, reliability of information processing, is signalled to others through facial appearance. Copyright © 2016 Elsevier B.V. All rights reserved.

The Relationship between Patient Satisfaction with Service Quality and Survival in Non-Small Cell Lung Cancer - Is Self-Rated Health a Potential Confounder?

Directory of Open Access Journals (Sweden)

Christopher G Lis

other concerning your medical condition and treatment" (HR = 0.59; 95% CI: 0.36 to 0.94; p = 0.03.SRH appears to confound the PS-survival relationship in NSCLC. SRH should be used as a control/stratification variable in analyses involving PS as a predictor of clinical cancer outcomes.

The Relationship between Patient Satisfaction with Service Quality and Survival in Non-Small Cell Lung Cancer - Is Self-Rated Health a Potential Confounder?

Science.gov (United States)

Lis, Christopher G; Patel, Kamal; Gupta, Digant

2015-01-01

concerning your medical condition and treatment" (HR = 0.59; 95% CI: 0.36 to 0.94; p = 0.03). SRH appears to confound the PS-survival relationship in NSCLC. SRH should be used as a control/stratification variable in analyses involving PS as a predictor of clinical cancer outcomes.

Influence of GSTM1 and GSTT1 genotypes and confounding factors on the frequency of sister chromatid exchange and micronucleus among road construction workers.

Science.gov (United States)

Kumar, Anil; Yadav, Anita; Giri, Shiv Kumar; Dev, Kapil; Gautam, Sanjeev Kumar; Gupta, Ranjan; Aggarwal, Neeraj

2011-07-01

In the present study, we have investigated the influence of polymorphism of GSTM1 and GSTT1 genes and confounding factors such as age, sex, exposure duration and consumption habits on cytogenetic biomarkers. Frequency of sister chromatid exchanges (SCEs), high frequency cell (HFC) and cytokinesis blocked micronuclei (CBMN) were evaluated in peripheral blood lymphocytes of 115 occupationally exposed road construction workers and 105 unexposed individuals. The distribution of null and positive genotypes of glutathione-S transferase gene was evaluated by multiplex PCR among control and exposed subjects. An increased frequency of CBMN (7.03±2.08); SCE (6.95±1.76) and HFC (6.28±1.69) were found in exposed subjects when compared to referent (CBMN - 3.35±1.10; SCE - 4.13±1.30 and HFC - 3.98±1.56). These results were found statistically significant at p<0.05. When the effect of confounding factors on the frequency of studied biomarkers was evaluated, a strong positive interaction was found. The individuals having GSTM1 and GSTT1 null genotypes had higher frequency of CBMN, SCE and HFC. The association between GSTM1 and GSTT1 genotypes and studied biomarkers was found statistically significant at p<0.05. Our findings suggest that individuals having null type of GST are more susceptible to cytogenetic damage by occupational exposure regardless of confounding factors. There is a significant effect of polymorphism of these genes on cytogenetic biomarkers which are considered as early effects of genotoxic carcinogens. Copyright © 2011 Elsevier Ltd. All rights reserved.

How to ask about patient satisfaction? The visual analogue scale is less vulnerable to confounding factors and ceiling effect than a symmetric Likert scale.

Science.gov (United States)

Voutilainen, Ari; Pitkäaho, Taina; Kvist, Tarja; Vehviläinen-Julkunen, Katri

2016-04-01

To study the effects of scale type (visual analogue scale vs. Likert), item order (systematic vs. random), item non-response and patient-related characteristics (age, gender, subjective health, need for assistance with filling out the questionnaire and length of stay) on the results of patient satisfaction surveys. Although patient satisfaction is one of the most intensely studied issues in the health sciences, research information about the effects of possible instrument-related confounding factors on patient satisfaction surveys is scant. A quasi-experimental design was employed. A non-randomized sample of 150 surgical patients was gathered to minimize possible alterations in care quality. Data were collected in May-September 2014 from one tertiary hospital in Finland using the Revised Humane Caring Scale instrument. New versions of the instrument were created for the present purposes. In these versions, items were either in a visual analogue format or Likert-scaled, in systematic or random order. The data were analysed using an analysis of covariance and a paired samples t-test. The visual analogue scale items were less vulnerable to bias from confounding factors than were the Likert-scaled items. The visual analogue scale also avoided the ceiling effect better than Likert and the time needed to complete the visual analogue scale questionnaire was 28% shorter than that needed to complete the Likert-scaled questionnaire. The present results supported the use of visual analogue scale rather than Likert scaling in patient satisfaction surveys and stressed the need to account for as many potential confounding factors as possible. © 2015 John Wiley & Sons Ltd.

Random Forest Variable Importance Spectral Indices Scheme for Burnt Forest Recovery Monitoring—Multilevel RF-VIMP

Directory of Open Access Journals (Sweden)

Sornkitja Boonprong

2018-05-01

Full Text Available Burnt forest recovery is normally monitored with a time-series analysis of satellite data because of its proficiency for large observation areas. Traditional methods, such as linear correlation plotting, have been proven to be effective, as forest recovery naturally increases with time. However, these methods are complicated and time consuming when increasing the number of observed parameters. In this work, we present a random forest variable importance (RF-VIMP scheme called multilevel RF-VIMP to compare and assess the relationship between 36 spectral indices (parameters of burnt boreal forest recovery in the Great Xing’an Mountain, China. Six Landsat images were acquired in the same month 0, 1, 4, 14, 16, and 20 years after a fire, and 39,380 fixed-location samples were then extracted to calculate the effectiveness of the 36 parameters. Consequently, the proposed method was applied to find correlations between the forest recovery indices. The experiment showed that the proposed method is suitable for explaining the efficacy of those spectral indices in terms of discrimination and trend analysis, and for showing the satellite data and forest succession dynamics when applied in a time series. The results suggest that the tasseled cap transformation wetness, brightness, and the shortwave infrared bands (both 1 and 2 perform better than other indices for both classification and monitoring.

Climate variability and climate change

International Nuclear Information System (INIS)

Rind, D.

1991-01-01

Changes of variability with climate change are likely to have a substantial impact on vegetation and society, rivaling the importance of changes in the mean values themselves. A variety of paleoclimate and future climate simulations performed with the GISS global climate model is used to assess how the variabilities of temperature and precipitation are altered as climate warms or cools. In general, as climate warms, temperature variability decreases due to reductions in the latitudinal temperature gradient and precipitation variability increases together with the intensity of the hydrologic cycle. If future climate projections are accurate, the reduction in temperature variability will be minimized by the rapid change in mean temperatures, but the hydrologic variability will be amplified by increased evapotranspiration. Greater hydrologic variability would appear to pose a potentially severe problem for the next century. 19 refs.; 3 figs.; 2 tabs

Brown Dwarf Variability: What's Varying and Why?

Science.gov (United States)

Marley, Mark Scott

2014-01-01

Surveys by ground based telescopes, HST, and Spitzer have revealed that brown dwarfs of most spectral classes exhibit variability. The spectral and temporal signatures of the variability are complex and apparently defy simplistic classification which complicates efforts to model the changes. Important questions include understanding if clearings are forming in an otherwise uniform cloud deck or if thermal perturbations, perhaps associated with breaking gravity waves, are responsible. If clouds are responsible how long does it take for the atmospheric thermal profile to relax from a hot cloudy to a cooler cloudless state? If thermal perturbations are responsible then what atmospheric layers are varying? How do the observed variability timescales compare to atmospheric radiative, chemical, and dynamical timescales? I will address such questions by presenting modeling results for time-varying partly cloudy atmospheres and explore the importance of various atmospheric processes over the relevant timescales for brown dwarfs of a range of effective temperatures. Regardless of the origin of the observed variability, the complexity seen in the atmospheres of the field dwarfs hints at the variability that we may encounter in the next few years in directly imaged young Jupiters. Thus understanding the nature of variability in the field dwarfs, including sensitivity to gravity and metallicity, is of particular importance for exoplanet characterization.

Educational gains in cause-specific mortality: Accounting for cognitive ability and family-level confounders using propensity score weighting.

Science.gov (United States)

Bijwaard, Govert E; Myrskylä, Mikko; Tynelius, Per; Rasmussen, Finn

2017-07-01

A negative educational gradient has been found for many causes of death. This association may be partly explained by confounding factors that affect both educational attainment and mortality. We correct the cause-specific educational gradient for observed individual background and unobserved family factors using an innovative method based on months lost due to a specific cause of death re-weighted by the probability of attaining a higher educational level. We use data on men with brothers from the Swedish Military Conscription Registry (1951-1983), linked to administrative registers. This dataset of some 700,000 men allows us to distinguish between five education levels and many causes of death. The empirical results reveal that raising the educational level from primary to tertiary would result in an additional 20 months of survival between ages 18 and 63. This improvement in mortality is mainly attributable to fewer deaths from external causes. The highly educated gain more than nine months due to the reduction in deaths from external causes, but gain only two months due to the reduction in cancer mortality and four months due to the reduction in cardiovascular mortality. Ignoring confounding would lead to an underestimation of the gains by educational attainment, especially for the less educated. Our results imply that if the education distribution of 50,000 Swedish men from the 1951 cohort were replaced with that of the corresponding 1983 cohort, 22% of the person-years that were lost to death between ages 18 and 63 would have been saved for this cohort. Copyright © 2017 Elsevier Ltd. All rights reserved.

Alongshore variability of nourished and natural beaches

NARCIS (Netherlands)

De Schipper, M.A.

2014-01-01

Alongshore variability in topography (i.e. height differences in bed level along the coast) can exist on both natural and nourished beaches. An important question prior to implementation of a nourishment project is how alongshore variability is going to evolve and, related to this variability, the

Software Testing Requires Variability

DEFF Research Database (Denmark)

Christensen, Henrik Bærbak

2003-01-01

Software variability is the ability of a software system or artefact to be changed, customized or configured for use in a particular context. Variability in software systems is important from a number of perspectives. Some perspectives rightly receive much attention due to their direct economic...... impact in software production. As is also apparent from the call for papers these perspectives focus on qualities such as reuse, adaptability, and maintainability....

Suspended graphene variable capacitor

OpenAIRE

AbdelGhany, M.; Mahvash, F.; Mukhopadhyay, M.; Favron, A.; Martel, R.; Siaj, M.; Szkopek, T.

2016-01-01

The tuning of electrical circuit resonance with a variable capacitor, or varactor, finds wide application with the most important being wireless telecommunication. We demonstrate an electromechanical graphene varactor, a variable capacitor wherein the capacitance is tuned by voltage controlled deflection of a dense array of suspended graphene membranes. The low flexural rigidity of graphene monolayers is exploited to achieve low actuation voltage in an ultra-thin structure. Large arrays compr...

Walking speed-related changes in stride time variability: effects of decreased speed

Directory of Open Access Journals (Sweden)

Dubost Veronique

2009-08-01

Full Text Available Abstract Background Conflicting results have been reported regarding the relationship between stride time variability (STV and walking speed. While some studies failed to establish any relationship, others reported either a linear or a non-linear relationship. We therefore sought to determine the extent to which decrease in self-selected walking speed influenced STV among healthy young adults. Methods The mean value, the standard deviation and the coefficient of variation of stride time, as well as the mean value of stride velocity were recorded while steady-state walking using the GAITRite® system in 29 healthy young adults who walked consecutively at 88%, 79%, 71%, 64%, 58%, 53%, 46% and 39% of their preferred walking speed. Results The decrease in stride velocity increased significantly mean values, SD and CoV of stride time (p Conclusion The results support the assumption that gait variability increases while walking speed decreases and, thus, gait might be more unstable when healthy subjects walk slower compared with their preferred walking speed. Furthermore, these results highlight that a decrease in walking speed can be a potential confounder while evaluating STV.

Accounting for genetic and environmental confounds in associations between parent and child characteristics : a systematic review of children-of-twins studies

OpenAIRE

McAdams, Tom A; Neiderhiser, Jenae M; Rijsdijk, Fruhling V; Narusyte, Jurgita; Lichtenstein, Paul; Eley, Thalia C

2014-01-01

Parental psychopathology, parenting style, and the quality of intrafamilial relationships are all associated with child mental health outcomes. However, most research can say little about the causal pathways underlying these associations. This is because most studies are not genetically informative and are therefore not able to account for the possibility that associations are confounded by gene-environment correlation. That is, biological parents not only provide a rearing environment for th...

Excess Mortality in Hyperthyroidism: The Influence of Preexisting Comorbidity and Genetic Confounding: A Danish Nationwide Register-Based Cohort Study of Twins and Singletons

Science.gov (United States)

Brandt, Frans; Almind, Dorthe; Christensen, Kaare; Green, Anders; Brix, Thomas Heiberg

2012-01-01

Context: Hyperthyroidism is associated with severe comorbidity, such as stroke, and seems to confer increased mortality. However, it is unknown whether this increased mortality is explained by hyperthyroidism per se, comorbidity, and/or genetic confounding. Objective: The objective of the study was to investigate whether hyperthyroidism is associated with an increased mortality and, if so, whether the association is influenced by comorbidity and/or genetic confounding. Methods: This was an observational cohort study using record-linkage data from nationwide Danish health registers. We identified 4850 singletons and 926 twins from same-sex pairs diagnosed with hyperthyroidism. Each case was matched with four controls for age and gender. The Charlson score was calculated from discharge diagnoses on an individual level to measure comorbidity. Cases and controls were followed up for a mean of 10 yr (range 0–31 yr), and the hazard ratio (HR) for mortality was calculated using Cox regression analyses. Results: In singletons there was a significantly higher mortality in individuals diagnosed with hyperthyroidism than in controls [HR 1.37; 95% confidence interval (CI) 1.30–1.46]. This persisted after adjustment for preexisting comorbidity (HR 1,28; 95% CI 1.21–1.36). In twin pairs discordant for hyperthyroidism (625 pairs), the twin with hyperthyroidism had an increased mortality compared with the corresponding cotwin (HR 1.43; 95% CI 1.09–1.88). However, this was found only in dizygotic pairs (HR 1.80; 95% CI 1.27–2.55) but not in monozygotic pairs (HR 0.95; 95% CI 0.60–1.50). Conclusions: Hyperthyroidism is associated with an increased mortality independent of preexisting comorbidity. The study of twin pairs discordant for hyperthyroidism suggests that genetic confounding influences the association between hyperthyroidism and mortality. PMID:22930783

Análisis de las variables de marketing que afectan al valor del cliente. La permanencia como variable controlable

OpenAIRE

Pedreño Santos, Ana

2015-01-01

To know how marketing variables affect customer value is essential for a company in order to be market and customer oriented, and to improve investment efficiency in both attracting and retaining customers. Thus, the assessment of the influence of marketing variables in customer value is of prime importance. This is recognized in many empirical studies of these variables, which address the impact of a single variable (or sets of a few variables) on customer value. A comprehensive, integrated ...

Benchmarking Variable Selection in QSAR.

Science.gov (United States)

Eklund, Martin; Norinder, Ulf; Boyer, Scott; Carlsson, Lars

2012-02-01

Variable selection is important in QSAR modeling since it can improve model performance and transparency, as well as reduce the computational cost of model fitting and predictions. Which variable selection methods that perform well in QSAR settings is largely unknown. To address this question we, in a total of 1728 benchmarking experiments, rigorously investigated how eight variable selection methods affect the predictive performance and transparency of random forest models fitted to seven QSAR datasets covering different endpoints, descriptors sets, types of response variables, and number of chemical compounds. The results show that univariate variable selection methods are suboptimal and that the number of variables in the benchmarked datasets can be reduced with about 60 % without significant loss in model performance when using multivariate adaptive regression splines MARS and forward selection. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Association of Body Mass Index with Depression, Anxiety and Suicide-An Instrumental Variable Analysis of the HUNT Study.

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Johan Håkon Bjørngaard

Full Text Available While high body mass index is associated with an increased risk of depression and anxiety, cumulative evidence indicates that it is a protective factor for suicide. The associations from conventional observational studies of body mass index with mental health outcomes are likely to be influenced by reverse causality or confounding by ill-health. In the present study, we investigated the associations between offspring body mass index and parental anxiety, depression and suicide in order to avoid problems with reverse causality and confounding by ill-health.We used data from 32,457 mother-offspring and 27,753 father-offspring pairs from the Norwegian HUNT-study. Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale and suicide death from national registers. Associations between offspring and own body mass index and symptoms of anxiety and depression and suicide mortality were estimated using logistic and Cox regression. Causal effect estimates were estimated with a two sample instrument variable approach using offspring body mass index as an instrument for parental body mass index.Both own and offspring body mass index were positively associated with depression, while the results did not indicate any substantial association between body mass index and anxiety. Although precision was low, suicide mortality was inversely associated with own body mass index and the results from the analysis using offspring body mass index supported these results. Adjusted odds ratios per standard deviation body mass index from the instrumental variable analysis were 1.22 (95% CI: 1.05, 1.43 for depression, 1.10 (95% CI: 0.95, 1.27 for anxiety, and the instrumental variable estimated hazard ratios for suicide was 0.69 (95% CI: 0.30, 1.63.The present study's results indicate that suicide mortality is inversely associated with body mass index. We also found support for a positive association between body mass index and depression, but not

Climate Classification is an Important Factor in ­Assessing Hospital Performance Metrics

Science.gov (United States)

Boland, M. R.; Parhi, P.; Gentine, P.; Tatonetti, N. P.

2017-12-01

Context/Purpose: Climate is a known modulator of disease, but its impact on hospital performance metrics remains unstudied. Methods: We assess the relationship between Köppen-Geiger climate classification and hospital performance metrics, specifically 30-day mortality, as reported in Hospital Compare, and collected for the period July 2013 through June 2014 (7/1/2013 - 06/30/2014). A hospital-level multivariate linear regression analysis was performed while controlling for known socioeconomic factors to explore the relationship between all-cause mortality and climate. Hospital performance scores were obtained from 4,524 hospitals belonging to 15 distinct Köppen-Geiger climates and 2,373 unique counties. Results: Model results revealed that hospital performance metrics for mortality showed significant climate dependence (psocioeconomic factors. Interpretation: Currently, hospitals are reimbursed by Governmental agencies using 30-day mortality rates along with 30-day readmission rates. These metrics allow Government agencies to rank hospitals according to their `performance' along these metrics. Various socioeconomic factors are taken into consideration when determining individual hospitals performance. However, no climate-based adjustment is made within the existing framework. Our results indicate that climate-based variability in 30-day mortality rates does exist even after socioeconomic confounder adjustment. Use of standardized high-level climate classification systems (such as Koppen-Geiger) would be useful to incorporate in future metrics. Conclusion: Climate is a significant factor in evaluating hospital 30-day mortality rates. These results demonstrate that climate classification is an important factor when comparing hospital performance across the United States.

Handling stress may confound murine gut microbiota studies

Directory of Open Access Journals (Sweden)

Cary R. Allen-Blevins

2017-01-01

Full Text Available Background Accumulating evidence indicates interactions between human milk composition, particularly sugars (human milk oligosaccharides or HMO, the gut microbiota of human infants, and behavioral effects. Some HMO secreted in human milk are unable to be endogenously digested by the human infant but are able to be metabolized by certain species of gut microbiota, including Bifidobacterium longum subsp. infantis (B. infantis, a species sensitive to host stress (Bailey & Coe, 2004. Exposure to gut bacteria like B. infantisduring critical neurodevelopment windows in early life appears to have behavioral consequences; however, environmental, physical, and social stress during this period can also have behavioral and microbial consequences. While rodent models are a useful method for determining causal relationships between HMO, gut microbiota, and behavior, murine studies of gut microbiota usually employ oral gavage, a technique stressful to the mouse. Our aim was to develop a less-invasive technique for HMO administration to remove the potential confound of gavage stress. Under the hypothesis that stress affects gut microbiota, particularly B. infantis, we predicted the pups receiving a prebiotic solution in a less-invasive manner would have the highest amount of Bifidobacteria in their gut. Methods This study was designed to test two methods, active and passive, of solution administration to mice and the effects on their gut microbiome. Neonatal C57BL/6J mice housed in a specific-pathogen free facility received increasing doses of fructooligosaccharide (FOS solution or deionized, distilled water. Gastrointestinal (GI tracts were collected from five dams, six sires, and 41 pups over four time points. Seven fecal pellets from unhandled pups and two pellets from unhandled dams were also collected. Qualitative real-time polymerase chain reaction (qRT-PCR was used to quantify and compare the amount of Bifidobacterium, Bacteroides, Bacteroidetes, and

Climate Variability Structures Plant Community Dynamics in Mediterranean Restored and Reference Tidal Wetlands

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Dylan E. Chapple

2017-03-01

Full Text Available In Mediterranean regions and other areas with variable climates, interannual weather variability may impact ecosystem dynamics, and by extension ecological restoration projects. Conditions at reference sites, which are often used to evaluate restoration projects, may also be influenced by weather variability, confounding interpretations of restoration outcomes. To better understand the influence of weather variability on plant community dynamics, we explore change in a vegetation dataset collected between 1990 and 2005 at a historic tidal wetland reference site and a nearby tidal wetland restoration project initiated in 1976 in California’s San Francisco (SF Bay. To determine the factors influencing reference and restoration trajectories, we examine changes in plant community identity in relation to annual salinity levels in the SF Bay, annual rainfall, and tidal channel structure. Over the entire study period, both sites experienced significant directional change away from the 1990 community. Community change was accelerated following low salinity conditions that resulted from strong El Niño events in 1994–1995 and 1997–1998. Overall rates of change were greater at the restoration site and driven by a combination of dominant and sub-dominant species, whereas change at the reference site was driven by sub-dominant species. Sub-dominant species first appeared at the restoration site in 1996 and incrementally increased during each subsequent year, whereas sub-dominant species cover at the reference site peaked in 1999 and subsequently declined. Our results show that frequent, long-term monitoring is needed to adequately capture plant community dynamics in variable Mediterranean ecosystems and demonstrate the need for expanding restoration monitoring and timing restoration actions to match weather conditions.

Protecting chips against hold time violations due to variability

CERN Document Server

Neuberger, Gustavo; Reis, Ricardo

2013-01-01

With the development of Very-Deep Sub-Micron technologies, process variability is becoming increasingly important and is a very important issue in the design of complex circuits. Process variability is the statistical variation of process parameters, meaning that these parameters do not have always the same value, but become a random variable, with a given mean value and standard deviation. This effect can lead to several issues in digital circuit design.The logical consequence of this parameter variation is that circuit characteristics, as delay and power, also become random variables. Becaus

Confounding Problems in Multifactor AOV When Using Several Organismic Variables of Limited Reliability

Science.gov (United States)

Games, Paul A.

1975-01-01

A brief introduction is presented on how multiple regression and linear model techniques can handle data analysis situations that most educators and psychologists think of as appropriate for analysis of variance. (Author/BJG)

Monitoring waterbird abundance in wetlands: The importance of controlling results for variation in water depth

Science.gov (United States)

Bolduc, F.; Afton, A.D.

2008-01-01

Wetland use by waterbirds is highly dependent on water depth, and depth requirements generally vary among species. Furthermore, water depth within wetlands often varies greatly over time due to unpredictable hydrological events, making comparisons of waterbird abundance among wetlands difficult as effects of habitat variables and water depth are confounded. Species-specific relationships between bird abundance and water depth necessarily are non-linear; thus, we developed a methodology to correct waterbird abundance for variation in water depth, based on the non-parametric regression of these two variables. Accordingly, we used the difference between observed and predicted abundances from non-parametric regression (analogous to parametric residuals) as an estimate of bird abundance at equivalent water depths. We scaled this difference to levels of observed and predicted abundances using the formula: ((observed - predicted abundance)/(observed + predicted abundance)) ?? 100. This estimate also corresponds to the observed:predicted abundance ratio, which allows easy interpretation of results. We illustrated this methodology using two hypothetical species that differed in water depth and wetland preferences. Comparisons of wetlands, using both observed and relative corrected abundances, indicated that relative corrected abundance adequately separates the effect of water depth from the effect of wetlands. ?? 2008 Elsevier B.V.

River classification is important for reporting ecological status and ...

African Journals Online (AJOL)

River classification is important for reporting ecological status and for the general ecological management of river systems by partitioning natural variability. A priori river classification by abiotic variables and validation of classifications obtained.

Association between prolonged breast-feeding and early childhood caries: a hierarchical approach.

Science.gov (United States)

Nunes, Ana Margarida Melo; Alves, Claudia Maria Coelho; Borba de Araújo, Fernando; Ortiz, Tânia Mara Lopes; Ribeiro, Marizélia Rodrigues Costa; Silva, Antônio Augusto Moura da; Ribeiro, Cecília Claudia Costa

2012-12-01

This study was conducted to investigate the association between prolonged breastfeeding and early childhood caries(ECC) with adjustment for important confounders, using hieraschical approach. This retrospective cohort study involved 260 low-income children (18-42 months). The number of decayed teeth was used as a measure of caries. Following a theoretical framework, the hierarchical model was built in a forward fashion, by adding the following levels in succession: level 1: age; level 2: social variables; level 3: health variables; level 4: behavioral variables; level 5: oral hygiene-related variables; level 6: oral hygiene quality measured by visible plaque; and level 7: contamination by mutans streptococci. Sequential forward multiple Poisson regression analysis was employed. Breast-feeding was not a risk factor for ECC after adjustment for some confounders (incidence density ratio, 1.15; 95% confidence interval, 0.84-1.59, P = 0.363). Prolonged breast-feeding was not a risk factor for ECC while age, high sucrose comption between main meals and the quality of oral higiene were associated with disease in children. © 2012 John Wiley & Sons A/S.

Flow variability and hillslope hydrology

Energy Technology Data Exchange (ETDEWEB)

Huff, D D; O' Neill, R V; Emanuel, W R; Elwood, J W; Newbold, J D

1982-01-01

Examination of spatial variability of streamflow in headwater areas can provide important insight about factors that influence hillslope hydrology. Detailed observations of variations in stream channel input, based on a tracer experiment, indicate that topography alone cannot explain flow variability. However, determination of changes in channel input on a small spatial scale can provide valuable clues to factors, such as structural geology that control subsurface flows.

The active liquid Earth - importance of temporal and spatial variability

Science.gov (United States)

Arheimer, Berit

2016-04-01

The Planet Earth is indeed liquid and active - 71 percent of its surface is water-covered and this water never rests. Thanks to the water cycle, our planet's water supply is constantly moving from one place to another and from one form to another. Only 2.5% of the water is freshwater and it exists in the air as water vapor; it hits the ground as rain and snow; it flows on the surface from higher to lower altitudes in rivers, lakes, and glaciers; and it flows in the ground in soil, aquifers, and in all living organisms until it reaches the sea. On its way over the Earth's crust, some returns quickly to vapor again, while some is trapped and exposed to many "fill and spill" situations for a long journey. The variability in the water balance is crucial for hydrological understanding and modelling. The water cycle may appear simple, but magnitudes and rates in fluxes are very different from one place to another, resulting from variable drivers such as solar energy, precipitation and gravity in co-evolution with geology, soil, vegetation and fauna. The historical evolution, the temporal fluxes and diversity in space continue to fascinate hydrological scientists. Specific physical processes may be well known, but their boundary conditions, interactions and rate often remain unknown at a specific site and are difficult to monitor in nature. This results in mysterious features where trends in drivers do not match runoff, like the Sahelian Paradox or discharge to the Arctic Ocean. Humans have always interfered with the water cycle and engineering is fundamental for water regulation and re-allocation. Some 80% of the river flow from the northern part of the Earth is affected by fragmentation of the river channels by dams. In water management, there is always a tradeoff between upstream and downstream activities, not only regarding total water quantities but also for temporal patterns and water quality aspects. Sharing a water resource can generate conflicts but geopolitical

Detecting correlation between allele frequencies and environmental variables as a signature of selection. A fast computational approach for genome-wide studies

DEFF Research Database (Denmark)

Guillot, Gilles; Vitalis, Renaud; Rouzic, Arnaud le

2014-01-01

to disentangle the potential effect of environmental variables from the confounding effect of population history. For the routine analysis of genome-wide datasets, one also needs fast inference and model selection algorithms. We propose a method based on an explicit spatial model which is an instance of spatial...... for the most common types of genetic markers, obtained either at the individual or at the population level. Analyzing the simulated data produced under a geostatistical model then under an explicit model of selection, we show that the method is efficient. We also re-analyze a dataset relative to nineteen pine...

Sternal wound complications after primary isolated myocardial revascularization: the importance of the post-operative variables.

NARCIS (Netherlands)

Noyez, L.; Druten, J.A.M. van; Mulder, J.; Schroen, A.M.; Skotnicki, S.H.; Brouwer, R.

2001-01-01

OBJECTIVE: Select pre-, peri-, and post-operative variables, predictive for sternal wound complications (SWC), in a clinical setting. METHODS: We analyzed pre-, peri-, and post-operative data of 3815 patients who underwent a primary isolated bypass grafting. 100 patients (2.6%) had post-operative

Is social isolation/alienation confounded with, and non-independent of, emotional distress in its association with early onset of coronary artery disease?

Science.gov (United States)

Ketterer, Mark; Rose, Benjamin; Knysz, Walter; Farha, Amjad; Deveshwar, Sangita; Schairer, John; Keteyian, Steven J

2011-03-01

Both emotional distress (ED) and social isolation/alienation (SI/A) have been found to prospectively predict adverse cardiac events, but few studies have tested the confounding/redundancy of these measures as correlates/predictors of outcomes. In this study, 163 patients with documented coronary artery disease (CAD) were interviewed for multiple indices of SI/A and administered the Symptom Checklist 90 - Revised (SCL90R). A spouse or friend provided an independent rating of ED using the spouse/friend version of the Ketterer Stress Symptom Frequency Checklist (KSSFC). The measures of ED and SI/A covaried. All three scales from the KSSFC (depression, anxiety, and "AIAI" - aggravation, irritation, anger, and impatience), and three scales from the SCL90R (anxiety, depression, and psychoticism), were associated with early Age at Initial Diagnosis (AAID) of CAD. Neither three scales derived from the SCL90R (shyness, feeling abused, and feeling lonely) nor the interview indices of SI/A (married, living alone, having a confidant, self description as a lone wolf, and self-description as lonely) were associated with early AAID. Thus, it is concluded that the present results indicate that ED and SI/A are confounded and that, even when tested head-to-head in a multivariate analysis, only ED is associated with AAID.

The Effect of Birth Weight on Academic Performance: Instrumental Variable Analysis.

Science.gov (United States)

Lin, Shi Lin; Leung, Gabriel Matthew; Schooling, C Mary

2017-05-01

Observationally, lower birth weight is usually associated with poorer academic performance; whether this association is causal or the result of confounding is unknown. To investigate this question, we obtained an effect estimate, which can have a causal interpretation under specific assumptions, of birth weight on educational attainment using instrumental variable analysis based on single nucleotide polymorphisms determining birth weight combined with results from the Social Science Genetic Association Consortium study of 126,559 Caucasians. We similarly obtained an estimate of the effect of birth weight on academic performance in 4,067 adolescents from Hong Kong's (Chinese) Children of 1997 birth cohort (1997-2016), using twin status as an instrumental variable. Birth weight was not associated with years of schooling (per 100-g increase in birth weight, -0.006 years, 95% confidence interval (CI): -0.02, 0.01) or college completion (odds ratio = 1.00, 95% CI: 0.96, 1.03). Birth weight was also unrelated to academic performance in adolescents (per 100-g increase in birth weight, -0.004 grade, 95% CI: -0.04, 0.04) using instrumental variable analysis, although conventional regression gave a small positive association (0.02 higher grade, 95% CI: 0.01, 0.03). Observed associations of birth weight with academic performance may not be causal, suggesting that interventions should focus on the contextual factors generating this correlation. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

High SNR Acquisitions Improve the Repeatability of Liver Fat Quantification Using Confounder-corrected Chemical Shift-encoded MR Imaging

Science.gov (United States)

Motosugi, Utaroh; Hernando, Diego; Wiens, Curtis; Bannas, Peter; Reeder, Scott. B

2017-01-01

Purpose: To determine whether high signal-to-noise ratio (SNR) acquisitions improve the repeatability of liver proton density fat fraction (PDFF) measurements using confounder-corrected chemical shift-encoded magnetic resonance (MR) imaging (CSE-MRI). Materials and Methods: Eleven fat-water phantoms were scanned with 8 different protocols with varying SNR. After repositioning the phantoms, the same scans were repeated to evaluate the test-retest repeatability. Next, an in vivo study was performed with 20 volunteers and 28 patients scheduled for liver magnetic resonance imaging (MRI). Two CSE-MRI protocols with standard- and high-SNR were repeated to assess test-retest repeatability. MR spectroscopy (MRS)-based PDFF was acquired as a standard of reference. The standard deviation (SD) of the difference (Δ) of PDFF measured in the two repeated scans was defined to ascertain repeatability. The correlation between PDFF of CSE-MRI and MRS was calculated to assess accuracy. The SD of Δ and correlation coefficients of the two protocols (standard- and high-SNR) were compared using F-test and t-test, respectively. Two reconstruction algorithms (complex-based and magnitude-based) were used for both the phantom and in vivo experiments. Results: The phantom study demonstrated that higher SNR improved the repeatability for both complex- and magnitude-based reconstruction. Similarly, the in vivo study demonstrated that the repeatability of the high-SNR protocol (SD of Δ = 0.53 for complex- and = 0.85 for magnitude-based fit) was significantly higher than using the standard-SNR protocol (0.77 for complex, P magnitude-based fit, P = 0.003). No significant difference was observed in the accuracy between standard- and high-SNR protocols. Conclusion: Higher SNR improves the repeatability of fat quantification using confounder-corrected CSE-MRI. PMID:28190853

Importance of the variability of hydrographic preconditioning for deep convection in the Gulf of Lion, NW Mediterranean

Directory of Open Access Journals (Sweden)

L. Grignon

2010-06-01

Full Text Available We study the variability of hydrographic preconditioning defined as the heat and salt contents in the Ligurian Sea before convection. The stratification is found to reach a maximum in the intermediate layer in December, whose causes and consequences for the interannual variability of convection are investigated. Further study of the interannual variability and correlation tests between the properties of the deep water formed and the winter surface fluxes support the description of convection as a process that transfers the heat and salt contents from the top and intermediate layers to the deep layer. A proxy for the rate of transfer is given by the final convective mixed layer depth, that is shown to depend equally on the surface fluxes and on the preconditioning. In particular, it is found that deep convection in winter 2004–2005 would have happened even with normal winter conditions, due to low pre-winter stratification.

Variability of BL Lacertae type object

Energy Technology Data Exchange (ETDEWEB)

Cayatte, V

1987-10-01

This object is among the brightest and the most violently variable of this galaxy class with active nuclei. It has been studied in many wavelength domains and in polarimetry. Some important results are reported here and more particularly on its variability. These observations bring some elements for a better knowledge of the inner source.

Hydrothermal activity at slow-spreading ridges: variability and importance of magmatic controls

Science.gov (United States)

Escartin, Javier

2016-04-01

Hydrothermal activity along mid-ocean ridge axes is ubiquitous, associated with mass, chemical, and heat exchanges between the deep lithosphere and the overlying envelopes, and sustaining chemiosynthetic ecosystems at the seafloor. Compared with hydrothermal fields at fast-spreading ridges, those at slow spreading ones show a large variability as their location and nature is controlled or influenced by several parameters that are inter-related: a) tectonic setting, ranging from 'volcanic systems' (along the rift valley floor, volcanic ridges, seamounts), to 'tectonic' ones (rift-bounding faults, oceanic detachment faults); b) the nature of the host rock, owing to compositional heterogeneity of slow-spreading lithosphere (basalt, gabbro, peridotite); c) the type of heat source (magmatic bodies at depth, hot lithosphere, serpentinization reactions); d) and the associated temperature of outflow fluids (high- vs.- low temperature venting and their relative proportion). A systematic review of the distribution and characteristics of hydrothermal fields along the slow-spreading Mid-Atlantic Ridge suggests that long-lived hydrothermal activity is concentrated either at oceanic detachment faults, or along volcanic segments with evidence of robust magma supply to the axis. A detailed study of the magmatically robust Lucky Strike segment suggests that all present and past hydrothermal activity is found at the center of the segment. The association of these fields to central volcanos, and the absence of indicators of hydrothermal activity along the remaining of the ridge segment, suggests that long-lived hydrothermal activity in these volcanic systems is maintained by the enhanced melt supply and the associated magma chamber(s) required to build these volcanic edifices. In this setting, hydrothermal outflow zones at the seafloor are systematically controlled by faults, indicating that hydrothermal fluids in the shallow crust exploit permeable fault zones to circulate. While

Neuroticism explains unwanted variance in Implicit Association Tests of personality: Possible evidence for an affective valence confound

Directory of Open Access Journals (Sweden)

Monika eFleischhauer

2013-09-01

Full Text Available Meta-analytic data highlight the value of the Implicit Association Test (IAT as an indirect measure of personality. Based on evidence suggesting that confounding factors such as cognitive abilities contribute to the IAT effect, this study provides a first investigation of whether basic personality traits explain unwanted variance in the IAT. In a gender-balanced sample of 204 volunteers, the Big-Five dimensions were assessed via self-report, peer-report, and IAT. By means of structural equation modeling, latent Big-Five personality factors (based on self- and peer-report were estimated and their predictive value for unwanted variance in the IAT was examined. In a first analysis, unwanted variance was defined in the sense of method-specific variance which may result from differences in task demands between the two IAT block conditions and which can be mirrored by the absolute size of the IAT effects. In a second analysis, unwanted variance was examined in a broader sense defined as those systematic variance components in the raw IAT scores that are not explained by the latent implicit personality factors. In contrast to the absolute IAT scores, this also considers biases associated with the direction of IAT effects (i.e., whether they are positive or negative in sign, biases that might result, for example, from the IAT’s stimulus or category features. None of the explicit Big-Five factors was predictive for method-specific variance in the IATs (first analysis. However, when considering unwanted variance that goes beyond pure method-specific variance (second analysis, a substantial effect of neuroticism occurred that may have been driven by the affective valence of IAT attribute categories and the facilitated processing of negative stimuli, typically associated with neuroticism. The findings thus point to the necessity of using attribute category labels and stimuli of similar affective valence in personality IATs to avoid confounding due to

Is temperature an important variable in recovery after mild traumatic brain injury? [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

Coleen M. Atkins

2017-11-01

Full Text Available With nearly 42 million mild traumatic brain injuries (mTBIs occurring worldwide every year, understanding the factors that may adversely influence recovery after mTBI is important for developing guidelines in mTBI management. Extensive clinical evidence exists documenting the detrimental effects of elevated temperature levels on recovery after moderate to severe TBI. However, whether elevated temperature alters recovery after mTBI or concussion is an active area of investigation. Individuals engaged in exercise and competitive sports regularly experience body and brain temperature increases to hyperthermic levels and these temperature increases are prolonged in hot and humid ambient environments. Thus, there is a strong potential for hyperthermia to alter recovery after mTBI in a subset of individuals at risk for mTBI. Preclinical mTBI studies have found that elevating brain temperature to 39°C before mTBI significantly increases neuronal death within the cortex and hippocampus and also worsens cognitive deficits. This review summarizes the pathology and behavioral problems of mTBI that are exacerbated by hyperthermia and discusses whether hyperthermia is a variable that should be considered after concussion and mTBI. Finally, underlying pathophysiological mechanisms responsible for hyperthermia-induced altered responses to mTBI and potential gender considerations are discussed.

Identification of key aromatic compounds in Congou black tea by PLSR with variable importance of projection scores and gas chromatography-mass spectrometry/gas chromatography-olfactometry.

Science.gov (United States)

Mao, Shihong; Lu, Changqi; Li, Meifeng; Ye, Yulong; Wei, Xu; Tong, Huarong

2018-04-13

Gas chromatography-olfactometry (GC-O) is the most frequently used method to estimate the sensory contribution of single odorant, but disregards the interactions between volatiles. In order to select the key volatiles responsible for the aroma attributes of Congou black tea (Camellia sinensis), instrumental, sensory and multivariate statistical approaches were applied. By sensory analysis, nine panelists developed 8 descriptors, namely, floral, sweet, fruity, green, roasted, oil, spicy, and off-odor. Linalool, (E)-furan linalool oxide, (Z)-pyran linalool oxide, methyl salicylate, β-myrcene, phenylethyl alcohol which identified from the most representative samples by GC-O procedure, were the essential aroma-active compounds in the formation of basic Congou black tea aroma. In addition, 136 volatiles were identified by gas chromatography-mass spectrometry (GC-MS), among which 55 compounds were determined as the key factors for the six sensory attributes by partial least-square regression (PLSR) with variable importance of projection (VIP) scores. Our results demonstrated that HS-SPME/GC-MS/GC-O was a fast approach for isolation and quantification aroma-active compounds. PLSR method was also considered to be a useful tool in selecting important variables for sensory attributes. These two strategies allowed us to comprehensively evaluate the sensorial contribution of single volatile from different perspectives, can be applied to related products for comprehensive quality control. This article is protected by copyright. All rights reserved.

Mildly elevated serum total bilirubin is negatively associated with hemoglobin A1c independently of confounding factors among community-dwelling middle-aged and elderly persons

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Ryuichi Kawamoto

2017-08-01

Full Text Available Abnormally high glycated hemoglobin (Hb (HbA1c is significantly associated with oxidative stress and an increased risk of cardiovascular disease (CVD. Serum total bilirubin (T-B may have a beneficial role in preventing oxidative changes and be a negative risk factor of CVD. Limited information is available on whether serum T-B is an independent confounding factor of HbA1c. The study subjects were 633 men aged 70 ± 9 (mean ± standard deviation (SD years and 878 women aged 70 ± 8 years who were enrolled consecutively from among patients aged ≥40 years through a community-based annual check-up process. We evaluated the relationship between various confounding factors including serum T-B and HbA1c in each gender. Multiple linear regression analysis pertaining to HbA1c showed that in men, serum T-B ( β = −0.139 as well as waist circumference ( β = 0.099, exercise habit ( β = 0.137, systolic blood pressure (SBP ( β = 0.076, triglycerides ( β = 0.087, and uric acid ( β = −0.123 were significantly and independently associated with HbA1c, and in women, serum T-B ( β = −0.084 as well as body mass index ( β = 0.090, smoking status ( β = −0.077, SBP ( β = 0.117, diastolic blood pressure (DBP ( β = −0.155, low-density lipoprotein cholesterol ( β = 0.074, prevalence of antidyslipidemic medication ( β = 0.174, and uric acid ( β = 0.090 were also significantly and independently associated with HbA1c. Multivariate-adjusted serum HbA1c levels were significantly high in subjects with the lowest serum T-B levels in both genders. Serum T-B is an independent confounding factor for HbA1c among community-dwelling middle-aged and elderly persons.

Bank Credit and Aggregate Import Demand in Nigeria: A Cointegration Analysis

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Philip Chimobi Omoke

2012-06-01

Full Text Available This study reformulated the aggregate import demand for Nigeria by including a financial variable (bank credit into the traditional import demand function for the period 1970-2009. The Johansen Multivariate cointegration analysis was used to estimate the function. The result obtained from the study shows no evidence of the existence of cointegrating relations between bank credit and import demand. This shows that bank credit is found to be insufficient as a policy instrument for long term import demand in Nigeria. Thus, the financial variable should not be included in modelling the aggregate import demand for Nigeria.

Imaging Variable Stars with HST

Science.gov (United States)

Karovska, M.

2012-06-01

(Abstract only) The Hubble Space Telescope (HST) observations of astronomical sources, ranging from objects in our solar system to objects in the early Universe, have revolutionized our knowledge of the Universe its origins and contents. I highlight results from HST observations of variable stars obtained during the past twenty or so years. Multiwavelength observations of numerous variable stars and stellar systems were obtained using the superb HST imaging capabilities and its unprecedented angular resolution, especially in the UV and optical. The HST provided the first detailed images probing the structure of variable stars including their atmospheres and circumstellar environments. AAVSO observations and light curves have been critical for scheduling of many of these observations and provided important information and context for understanding of the imaging results of many variable sources. I describe the scientific results from the imaging observations of variable stars including AGBs, Miras, Cepheids, semiregular variables (including supergiants and giants), YSOs and interacting stellar systems with a variable stellar components. These results have led to an unprecedented understanding of the spatial and temporal characteristics of these objects and their place in the stellar evolutionary chains, and in the larger context of the dynamic evolving Universe.

Comorbidity and confounding factors in attention-deficit/hyperactivity disorder and sleep disorders in children

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Huang YS

2011-09-01

Full Text Available Ya-Wen Jan1,2, Chien-Ming Yang1,3, Yu-Shu Huang4,51Department of Psychology, National Cheng-Chi University, Taipei; 2Sleep Center of Taipei Medical University Hospital, Taipei; 3The Research Center for Mind Brain and Learning, National Cheng-Chi University, Taipei; 4Department of Child Psychiatry and Sleep Center, Chang Gung Memorial Hospital, Taoyuan; 5College of Medicine, Chang Gung University, Taoyuan, TaiwanAbstract: Sleep problems are commonly reported in children with attention-deficit/hyperactivity disorder (ADHD symptoms. Research data regarding the complex and reciprocal relationship between ADHD and sleep disturbances has now accumulated. This paper is focused on the types of sleep problems that are associated with ADHD symptomatology, and attempts to untangle confounding factors and overlapping symptoms. The goal is also to present an updated overview of the pathophysiology of and treatment strategies for sleep problems in children with ADHD. The review also points out that future research will be needed to clarify further the other psychiatric comorbidities and side effects of medication in order to improve treatment outcomes and prevent misdiagnosis in clinical practice.Keywords: attention-deficit/hyperactivity disorder, sleep, children 

Influence of variables on the consolidation and unconfined compressive strength of crushed salt: Technical report

International Nuclear Information System (INIS)

Pfeifle, T.W.; Senseny, P.E.; Mellegard, K.D.

1987-01-01

Eight hydrostatic compression creep tests were performed on crushed salt specimens fabricated from Avery Island dome salt. Following the creep test, each specimen was tested in unconfined compression. The experiments were performed to assess the influence of the following four variables on the consolidation and unconfined strength of crushed salt: grain size distribution, temperature, time, and moisture content. The experiment design comprised a half-fraction factorial matrix at two levels. The levels of each variable investigated were grain size distribution, uniform-graded and well-graded (coefficient of uniformity of 1 and 8); temperature 25 0 C and 100 0 C; time, 3.5 x 10 3 s and 950 x 10 3 s (approximately 60 minutes and 11 days, respectively); and moisture content, dry and wet (85% relative humidity for 24 hours). The hydrostatic creep stress was 10 MPa. The unconfined compression tests were performed at an axial strain rate of 1 x 10 -5 s -1 . Results show that the variables time and moisture content have the greatest influence on creep consolidation, while grain size distribution and, to a somewhat lesser degree, temperature have the greatest influence on total consolidation. Time and moisture content and the confounded two-factor interactions between either grain size distribution and time or temperature and moisture content have the greatest influence on unconfined strength. 7 refs., 7 figs., 11 tabs

Pelagic fish, particularly clupeoids, form the basis of many important ...

African Journals Online (AJOL)

spamer

identified and related to anchovy recruitment by way of an expert system approach. These two ... mental and biological variables thought to be important in controlling ... and environmental variables/processes in the spawning, transport and ...

Climate variability and temporal trends of persistent organic pollutants in the arctic: a study of glaucous gulls.

Science.gov (United States)

Bustnes, Jan O; Gabrielsen, Geir W; Verreault, Jonathan

2010-04-15

The impact of climate variability on temporal trends (1997-2006) of persistent organic pollutants (POPs; polychlorinated biphenyls [PCB], hexachlorobenzene [HCB], and oxychlordane) was assessed in glaucous gulls (Larus hyperboreus) breeding in the Norwegian Arctic (n = 240). The Arctic Oscillation (AO: an index of sea-level pressure variability in the Northern Hemisphere above 20 degrees N) with different time lags was used as a climate proxy. The estimated concentrations of POPs in glaucous gull blood/plasma declined substantially (16-60%) over the time period. Multiple regression analyses showed that the rates of decline for POPs were correlated to climate variation when controlling for potential confounding variables (sex and body condition). More specifically AO in the current winter showed negative associations with POP concentrations, whereas the relationships with AO measurements from the year preceding POP measurements (AO preceding summer and AO preceding winter) were positive. Hence, gulls had relatively higher POP concentrations in breeding seasons following years with high air transport toward the Arctic. Furthermore, the impact of AO appeared to be stronger for HCB, a relatively volatile compound with high transport potential, compared to heavy chlorinated PCB congeners. This study thus suggests that predicted climate change should be considered in assessments of future temporal trends of POPs in Arctic wildlife.

Air pollution and heart rate variability: effect modification by chronic lead exposure.

Science.gov (United States)

Park, Sung Kyun; O'Neill, Marie S; Vokonas, Pantel S; Sparrow, David; Wright, Robert O; Coull, Brent; Nie, Huiling; Hu, Howard; Schwartz, Joel

2008-01-01

Outdoor air pollution and lead exposure can disturb cardiac autonomic function, but the effects of both these exposures together have not been studied. We examined whether higher cumulative lead exposures, as measured by bone lead, modified cross-sectional associations between air pollution and heart rate variability among 384 elderly men from the Normative Aging Study. We used linear regression, controlling for clinical, demographic, and environmental covariates. We found graded, significant reductions in both high-frequency and low-frequency powers of heart rate variability in relation to ozone and sulfate across the quartiles of tibia lead. Interquartile range increases in ozone and sulfate were associated respectively, with 38% decrease (95% confidence interval = -54.6% to -14.9%) and 22% decrease (-40.4% to 1.6%) in high frequency, and 38% decrease (-51.9% to -20.4%) and 12% decrease (-28.6% to 9.3%) in low frequency, in the highest quartile of tibia lead after controlling for potential confounders. We observed similar but weaker effect modification by tibia lead adjusted for education and cumulative traffic (residuals of the regression of tibia lead on education and cumulative traffic). Patella lead modified only the ozone effect on heart rate variability. People with long-term exposure to higher levels of lead may be more sensitive to cardiac autonomic dysfunction on high air pollution days. Efforts to understand how environmental exposures affect the health of an aging population should consider both current levels of pollution and history of lead exposure as susceptibility factors.

Daily affect variability and context-specific alcohol consumption.

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Mohr, Cynthia D; Arpin, Sarah; McCabe, Cameron T

2015-11-01

Research explored the effects of variability in negative and positive affect on alcohol consumption, specifying daily fluctuation in affect as a critical form of emotion dysregulation. Using daily process methodology allows for a more objective calculation of affect variability relative to traditional self-reports. The present study models within-person negative and positive affect variabilities as predictors of context-specific consumption (i.e. solitary vs. social drinking), controlling for mean levels of affect. A community sample of moderate-to-heavy drinkers (n = 47; 49% women) from a US metropolitan area reported on affect and alcohol consumption thrice daily for 30 days via a handheld electronic interviewer. Within-person affect variability was calculated using daily standard deviations in positive and negative affect. Within person, greater negative and positive variabilities are related to greater daily solitary and social consumption. Across study days, mean levels of negative and positive affect variabilities related to greater social consumption between persons; yet, aggregated negative affect variability was related to less solitary consumption. Results affirm affect variability as a unique predictor of alcohol consumption, independent of mean affect levels. Yet, it is important to differentiate social context of consumption, as well as type of affect variability, particularly at the between-person level. These distinctions help clarify inconsistencies in the self-medication literature regarding associations between average levels of affect and consumption. Importantly, consistent within-person relationships for both variabilities support arguments that both negative and positive affect variabilities are detrimental and reflect an inability to regulate emotional experience. © 2015 Australasian Professional Society on Alcohol and other Drugs.

Impact of Molecular Diagnostics for Tuberculosis on Patient-Important Outcomes: A Systematic Review of Study Methodologies.

Directory of Open Access Journals (Sweden)

Samuel G Schumacher

Full Text Available Several reviews on the accuracy of Tuberculosis (TB Nucleic Acid Amplification Tests (NAATs have been performed but the evidence on their impact on patient-important outcomes has not been systematically reviewed. Given the recent increase in research evaluating such outcomes and the growing list of TB NAATs that will reach the market over the coming years, there is a need to bring together the existing evidence on impact, rather than accuracy. We aimed to assess the approaches that have been employed to measure the impact of TB NAATs on patient-important outcomes in adults with possible pulmonary TB and/or drug-resistant TB.We first develop a conceptual framework to clarify through which mechanisms the improved technical performance of a novel TB test may lead to improved patient outcomes and outline which designs may be used to measure them. We then systematically review the literature on studies attempting to assess the impact of molecular TB diagnostics on such outcomes and provide a narrative synthesis of designs used, outcomes assessed and risk of bias across different study designs.We found 25 eligible studies that assessed a wide range of outcomes and utilized a variety of experimental and observational study designs. Many potentially strong design options have never been used. We found that much of the available evidence on patient-important outcomes comes from a small number of settings with particular epidemiological and operational context and that confounding, time trends and incomplete outcome data receive insufficient attention.A broader range of designs should be considered when designing studies to assess the impact of TB diagnostics on patient outcomes and more attention needs to be paid to the analysis as concerns about confounding and selection bias become relevant in addition to those on measurement that are of greatest concern in accuracy studies.

The Independent Importance of Pre-pregnancy Weight and Gestational Weight Gain for the Prevention of Large-for Gestational Age Brazilian Newborns.

Science.gov (United States)

Mastroeni, Marco F; Czarnobay, Sandra A; Kroll, Caroline; Figueirêdo, Katherinne B W; Mastroeni, Silmara S B S; Silva, Jean C; Khan, Mohammad K A; Loehr, Sarah; Veugelers, Paul J

2017-04-01

Objectives To study the independent effect of pre-pregnancy weight, gestational weight gain (GWG), and other important risk factors on newborn birth weight. Methods Baseline data of 435 adult women and their singletons born between January and February 2012 at a public hospital in Brazil were used. Logistic regression was applied to determine the independent importance of pre-pregnancy weight and GWG for large for gestational age (LGA) newborns. Results Among all mothers, 37.9 % were overweight and obese before pregnancy and 45.3 % experienced excessive GWG. Among the newborns, 24.4 % were classified as LGA. Univariate analysis showed an association of family income, GWG, pre-pregnancy BMI and excessive GWG with LGA newborns. Smoking before and during pregnancy was associated with a decreased likelihood of giving birth to an LGA newborn compared to mothers who did not smoke. After adjustment for confounding variables, age at birth of first child, GWG, HbA1c and pre-pregnancy weight-GWG were significant and independent determinants of giving birth to an LGA newborn. Mothers with pre-pregnancy overweight and excessive GWG were more likely to deliver an LGA newborn (OR 2.54, P weight and experienced adequate GWG. Conclusions for Practice Age at first birth of child, GWG, HbA1c and pre-pregnancy overweight combined with excessive GWG are independent determinants of LGA newborns. The results of this study suggest that both primary prevention of overweight in women of childbearing age and management of GWG may be important strategies to reduce the number of LGA newborns and, consequently, the long-term public health burden of obesity.

Psychological and Educational Variables in University Dropout

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Bethencourt, Jose Tomas; Cabrera, Lidia; Hernandez, Juan Andres; Alvarez-Perez, Pedro; Gonzalez-Afonso, Miriam

2008-01-01

Introduction: The purpose of this research is to demonstrate that on the perceptions of university students, the student variables are seen as most important than the context variables to dropout their university studies. Method: The used methodology was cross-sectional or of cut, of retrospective type. 558 undergraduates were interviewed by…

The History of Variable Stars: A Fresh Look

Science.gov (United States)

Hatch, R. A.

2012-06-01

(Abstract only) For historians of astronomy, variable stars are important for a simple reason - stars change. But good evidence suggests this is a very modern idea. Over the millennia, our species has viewed stars as eternal and unchanging, forever fixed in time and space - indeed, the Celestial Dance was a celebration of order, reason, and stability. But everything changed in the period between Copernicus and Newton. According to tradition, two New Stars announced the birth of the New Science. Blazing across the celestial stage, Tycho's Star (1572) and Kepler's Star (1604) appeared dramatically - and just as unexpectedly - disappeared forever. But variable stars were different. Mira Ceti, the oldest, brightest, and most controversial variable star, was important because it appeared and disappeared again and again. Mira was important because it did not go away. The purpose of this essay is to take a fresh look at the history of variable stars. In re-thinking the traditional narrative, I begin with the first sightings of David Fabricius (1596) and his contemporaries - particularly Hevelius (1662) and Boulliau (1667) - to new traditions that unfolded from Newton and Maupertuis to Herschel (1780) and Pigott (1805). The essay concludes with important 19th-century developments, particularly by Argelander (1838), Pickering (1888), and Lockyer (1890). Across three centuries, variable stars prompted astronomers to re-think all the ways that stars were no longer "fixed." New strategies were needed. Astronomers needed to organize, to make continuous observations, to track changing magnitudes, and to explain stellar phases. Importantly - as Mira suggested from the outset - these challenges called for an army of observers with the discipline of Spartans. But recruiting that army required a strategy, a set of theories with shared expectations. Observation and theory worked hand-in-hand. In presenting new historical evidence from neglected printed sources and unpublished

Discovering human germ cell mutagens with whole genome sequencing: Insights from power calculations reveal the importance of controlling for between-family variability.

Science.gov (United States)

Webster, R J; Williams, A; Marchetti, F; Yauk, C L

2018-07-01

Mutations in germ cells pose potential genetic risks to offspring. However, de novo mutations are rare events that are spread across the genome and are difficult to detect. Thus, studies in this area have generally been under-powered, and no human germ cell mutagen has been identified. Whole Genome Sequencing (WGS) of human pedigrees has been proposed as an approach to overcome these technical and statistical challenges. WGS enables analysis of a much wider breadth of the genome than traditional approaches. Here, we performed power analyses to determine the feasibility of using WGS in human families to identify germ cell mutagens. Different statistical models were compared in the power analyses (ANOVA and multiple regression for one-child families, and mixed effect model sampling between two to four siblings per family). Assumptions were made based on parameters from the existing literature, such as the mutation-by-paternal age effect. We explored two scenarios: a constant effect due to an exposure that occurred in the past, and an accumulating effect where the exposure is continuing. Our analysis revealed the importance of modeling inter-family variability of the mutation-by-paternal age effect. Statistical power was improved by models accounting for the family-to-family variability. Our power analyses suggest that sufficient statistical power can be attained with 4-28 four-sibling families per treatment group, when the increase in mutations ranges from 40 to 10% respectively. Modeling family variability using mixed effect models provided a reduction in sample size compared to a multiple regression approach. Much larger sample sizes were required to detect an interaction effect between environmental exposures and paternal age. These findings inform study design and statistical modeling approaches to improve power and reduce sequencing costs for future studies in this area. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

The use of aquatic bioconcentration factors in ecological risk assessments: Confounding issues, laboratory v/s modeled results

International Nuclear Information System (INIS)

Brandt, C.; Blanton, M.L.; Dirkes, R.

1995-01-01

Bioconcentration in aquatic systems is generally taken to refer to contaminant uptake through non-ingestion pathways (i.e., dermal and respiration uptake). Ecological risk assessments performed on aquatic systems often rely on published data on bioconcentration factors to calibrate models of exposure. However, many published BCFs, especially those from in situ studies, are confounded by uptake from ingestion of prey. As part of exposure assessment and risk analysis of the Columbia River's Hanford Reach, the authors tested a methodology to estimate radionuclide BCFs for several aquatic species in the Hanford Reach of the Columbia River. The iterative methodology solves for BCFs from known body burdens and environmental media concentrations. This paper provides BCF methodology description comparisons of BCF from literature and modeled values and how they were used in the exposure assessment and risk analysis of the Columbia River's Hanford Reach

Role of environmental variables on radon concentration in soil

International Nuclear Information System (INIS)

Climent, H.; Bakalowicz, M.; Monnin, M.

1998-01-01

In the frame of an European project, radon concentrations in soil and measurements of environmental variables such as the nature of the soil or climatic variables were monitored. The data have been analysed by time-series analysis methods, i.e. Correlation and Spectrum Analysis, to point out relations between radon concentrations and some environmental variables. This approach is a compromise between direct observation and modelling. The observation of the rough time series is unable to point out the relation between radon concentrations and an environmental variable because of the overlapping of the influences of several variables, and the time delay induced by the medium. The Cross Spectrum function between the time series of radon and of an environmental variable describes the nature of the relation and gives the response time in the case of a cause to effect relation. It requires the only hypothesis that the environmental variable is the input function and radon concentration the output function. This analysis is an important preliminary study for modelling. By that way the importance of soil nature has been pointed out. The internal variables of the medium (permeability, porosity) appear to restrain the influence of the environmental variables such as humidity, temperature or atmospheric pressure. (author)

Dissociating variability and effort as determinants of coordination.

Directory of Open Access Journals (Sweden)

Ian O'Sullivan

2009-04-01

Full Text Available When coordinating movements, the nervous system often has to decide how to distribute work across a number of redundant effectors. Here, we show that humans solve this problem by trying to minimize both the variability of motor output and the effort involved. In previous studies that investigated the temporal shape of movements, these two selective pressures, despite having very different theoretical implications, could not be distinguished; because noise in the motor system increases with the motor commands, minimization of effort or variability leads to very similar predictions. When multiple effectors with different noise and effort characteristics have to be combined, however, these two cost terms can be dissociated. Here, we measure the importance of variability and effort in coordination by studying how humans share force production between two fingers. To capture variability, we identified the coefficient of variation of the index and little fingers. For effort, we used the sum of squared forces and the sum of squared forces normalized by the maximum strength of each effector. These terms were then used to predict the optimal force distribution for a task in which participants had to produce a target total force of 4-16 N, by pressing onto two isometric transducers using different combinations of fingers. By comparing the predicted distribution across fingers to the actual distribution chosen by participants, we were able to estimate the relative importance of variability and effort of 1:7, with the unnormalized effort being most important. Our results indicate that the nervous system uses multi-effector redundancy to minimize both the variability of the produced output and effort, although effort costs clearly outweighed variability costs.

For the Love of Nature: Exploring the Importance of Species Diversity and Micro-Variables Associated with Favorite Outdoor Places.

Science.gov (United States)

Schebella, Morgan F; Weber, Delene; Lindsey, Kiera; Daniels, Christopher B

2017-01-01

Although the restorative benefits of nature are widely acknowledged, there is a limited understanding of the attributes of natural environments that are fundamental to restorative experiences. Faced with growing human populations and a greater awareness of the wellbeing benefits natural environments provide, park agencies and planners are increasingly challenged with balancing human and ecological outcomes in natural areas. This study examines the physical and experiential qualities of natural environments people referred to when describing their connection to their most valued natural environments in an online questionnaire. Recruited primarily via a public radio program, respondents were asked to identify their favorite places and explain what they loved about those places. Favorite places are considered exemplars of restorative environments and were classified based on an existing park typology. Reasons people liked particular sites were classified into three domains: setting, activity, or benefit. Content analysis was used to identify the attributes most commonly associated with favorite places. These attributes were then related to the four components of restorative environments according to Attention Restoration Theory. In contrast to previous research, we found that "fascination" was the most important component of favorite places. Possible reasons for this contrast, namely, respondents' median age, and the likelihood of a high degree of ecological literacy amongst the study population are discussed. South Australians' favorite environments comprise primarily hilly, wooded nature parks, and botanical gardens, in stark contrast to the vast arid areas that dominate the state. Micro-variables such as birds, plants, wildlife, native species, and biodiversity appear particularly important elements used to explain people's love of these sites. We discuss the implications of these findings and their potential value as an anchor for marketing campaigns seeking to

For the Love of Nature: Exploring the Importance of Species Diversity and Micro-Variables Associated with Favorite Outdoor Places

Directory of Open Access Journals (Sweden)

Morgan F. Schebella

2017-12-01

Full Text Available Although the restorative benefits of nature are widely acknowledged, there is a limited understanding of the attributes of natural environments that are fundamental to restorative experiences. Faced with growing human populations and a greater awareness of the wellbeing benefits natural environments provide, park agencies and planners are increasingly challenged with balancing human and ecological outcomes in natural areas. This study examines the physical and experiential qualities of natural environments people referred to when describing their connection to their most valued natural environments in an online questionnaire. Recruited primarily via a public radio program, respondents were asked to identify their favorite places and explain what they loved about those places. Favorite places are considered exemplars of restorative environments and were classified based on an existing park typology. Reasons people liked particular sites were classified into three domains: setting, activity, or benefit. Content analysis was used to identify the attributes most commonly associated with favorite places. These attributes were then related to the four components of restorative environments according to Attention Restoration Theory. In contrast to previous research, we found that “fascination” was the most important component of favorite places. Possible reasons for this contrast, namely, respondents' median age, and the likelihood of a high degree of ecological literacy amongst the study population are discussed. South Australians' favorite environments comprise primarily hilly, wooded nature parks, and botanical gardens, in stark contrast to the vast arid areas that dominate the state. Micro-variables such as birds, plants, wildlife, native species, and biodiversity appear particularly important elements used to explain people's love of these sites. We discuss the implications of these findings and their potential value as an anchor for marketing

Using propensity scores to estimate the effects of insecticides on stream invertebrates from observational data

Science.gov (United States)

Lester L. Yuan,; Amina I. Pollard,; Carlisle, Daren M.

2009-01-01

Analyses of observational data can provide insights into relationships between environmental conditions and biological responses across a broader range of natural conditions than experimental studies, potentially complementing insights gained from experiments. However, observational data must be analyzed carefully to minimize the likelihood that confounding variables bias observed relationships. Propensity scores provide a robust approach for controlling for the effects of measured confounding variables when analyzing observational data. Here, we use propensity scores to estimate changes in mean invertebrate taxon richness in streams that have experienced insecticide concentrations that exceed aquatic life use benchmark concentrations. A simple comparison of richness in sites exposed to elevated insecticides with those that were not exposed suggests that exposed sites had on average 6.8 fewer taxa compared to unexposed sites. The presence of potential confounding variables makes it difficult to assert a causal relationship from this simple comparison. After controlling for confounding factors using propensity scores, the difference in richness between exposed and unexposed sites was reduced to 4.1 taxa, a difference that was still statistically significant. Because the propensity score analysis controlled for the effects of a wide variety of possible confounding variables, we infer that the change in richness observed in the propensity score analysis was likely caused by insecticide exposure.

A causal examination of the effects of confounding factors on multimetric indices

Science.gov (United States)

Schoolmaster, Donald R.; Grace, James B.; Schweiger, E. William; Mitchell, Brian R.; Guntenspergen, Glenn R.

2013-01-01

The development of multimetric indices (MMIs) as a means of providing integrative measures of ecosystem condition is becoming widespread. An increasingly recognized problem for the interpretability of MMIs is controlling for the potentially confounding influences of environmental covariates. Most common approaches to handling covariates are based on simple notions of statistical control, leaving the causal implications of covariates and their adjustment unstated. In this paper, we use graphical models to examine some of the potential impacts of environmental covariates on the observed signals between human disturbance and potential response metrics. Using simulations based on various causal networks, we show how environmental covariates can both obscure and exaggerate the effects of human disturbance on individual metrics. We then examine from a causal interpretation standpoint the common practice of adjusting ecological metrics for environmental influences using only the set of sites deemed to be in reference condition. We present and examine the performance of an alternative approach to metric adjustment that uses the whole set of sites and models both environmental and human disturbance effects simultaneously. The findings from our analyses indicate that failing to model and adjust metrics can result in a systematic bias towards those metrics in which environmental covariates function to artificially strengthen the metric–disturbance relationship resulting in MMIs that do not accurately measure impacts of human disturbance. We also find that a “whole-set modeling approach” requires fewer assumptions and is more efficient with the given information than the more commonly applied “reference-set” approach.

Variable selection in Logistic regression model with genetic algorithm.

Science.gov (United States)

Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

2018-02-01

Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

Why is seed production so variable among individuals? A ten-year study with oaks reveals the importance of soil environment.

Science.gov (United States)

Pérez-Ramos, Ignacio M; Aponte, Cristina; García, Luis V; Padilla-Díaz, Carmen M; Marañón, Teodoro

2014-01-01

Mast-seeding species exhibit not only a large inter-annual variability in seed production but also considerable variability among individuals within the same year. However, very little is known about the causes and consequences for population dynamics of this potentially large between-individual variability. Here, we quantified seed production over ten consecutive years in two Mediterranean oak species - the deciduous Quercus canariensis and the evergreen Q. suber - that coexist in forests of southern Spain. First, we calibrated likelihood models to identify which abiotic and biotic variables best explain the magnitude (hereafter seed productivity) and temporal variation of seed production at the individual level (hereafter CVi), and infer whether reproductive effort results from the available soil resources for the plant or is primarily determined by selectively favoured strategies. Second, we explored the contribution of between-individual variability in seed production as a potential mechanism of satiation for predispersal seed predators. We found that Q. canariensis trees inhabiting moister and more fertile soils were more productive than those growing in more resource-limited sites. Regarding temporal variation, individuals of the two studied oak species inhabiting these resource-rich environments also exhibited larger values of CVi. Interestingly, we detected a satiating effect on granivorous insects at the tree level in Q. suber, which was evident in those years where between-individual variability in acorn production was higher. These findings suggest that individual seed production (both in terms of seed productivity and inter-annual variability) is strongly dependent on soil resource heterogeneity (at least for one of the two studied oak species) with potential repercussions for recruitment and population dynamics. However, other external factors (such as soil heterogeneity in pathogen abundance) or certain inherent characteristics of the tree might be

Variability of nitrate and phosphate

Digital Repository Service at National Institute of Oceanography (India)

Sardessai, S.; Sundar, D.

Nitrate and phosphate are important elements of the biogeochemical system of an estuary. Observations carried out during the dry season April-May 2002, and March 2003 and wet season September 2002, show temporal and spatial variability of these two...

Typing Speed as a Confounding Variable and the Measurement of Quality in Divergent Thinking

Science.gov (United States)

Forthmann, Boris; Holling, Heinz; Çelik, Pinar; Storme, Martin; Lubart, Todd

2017-01-01

The need to control for writing or typing speed when assessing divergent-thinking performance has been recognized since the early '90s. An even longer tradition in divergent-thinking research has the issue of scoring the responses for quality. This research addressed both issues within structural equation modeling. Three dimensions of…

Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies

DEFF Research Database (Denmark)

Liston, A. D.; Ellegaard Lund, Torben; Salek-Haddadi, A

2006-01-01

effects to be modelled, as effects of no interest. Our model is based on an over-complete basis set covering a linear relationship between cardiac-related MR signal and the phase of the cardiac cycle or time after pulse (TAP). This method showed that, on average, 24.6 +/- 10.9% of grey matter voxels......Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance Imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet...... to take it into account in routine fMRI analysis. This paper reports the development of a general and robust technique to improve the reliability of EEG-fMRI studies to BOLD signal correlated with interictal epileptiform discharges (IEDs). In these studies, ECG is routinely recorded, enabling cardiac...

Abnormal mineral metabolism and mortality in hemodialysis patients with secondary hyperparathyroidism: evidence from marginal structural models used to adjust for time-dependent confounding.

Science.gov (United States)

Fukagawa, Masafumi; Kido, Ryo; Komaba, Hirotaka; Onishi, Yoshihiro; Yamaguchi, Takuhiro; Hasegawa, Takeshi; Kurita, Noriaki; Fukuma, Shingo; Akizawa, Tadao; Fukuhara, Shunichi

2014-06-01

Hemodialysis patients with mineral and bone disorders (MBDs) have an abnormally high relative risk of death, but their absolute risk of death is unknown. Further, previous studies have not accounted for possible time-dependent confounding of the association between MBD markers and death due to the effect of markers of MBD on treatments, which subsequently may affect MBD markers. Multicenter, 3-year, prospective, case-cohort study. 8,229 hemodialysis patients with secondary hyperparathyroidism (parathyroid hormone level ≥180 pg/mL and/or receiving vitamin D receptor activators) at 86 facilities in Japan. Serum phosphorus, calcium, and parathyroid hormone levels. All-cause mortality. Marginal structural models were used to compute absolute differences in all-cause mortality associated with different levels of predictors while accounting for time-dependent confounding. The association between phosphorus level and mortality appeared U-shaped, although only higher phosphorus level categories reached statistical significance: compared to those with phosphorus levels of 5.0-5.9 mg/dL (1.61-1.93 mmol/L), patients with the highest (≥9.0 mg/dL [≥2.90 mmol/L]) phosphorus levels had 9.4 excess deaths/100 person-years (rate ratio, 2.79 [95% CI, 1.26-6.15]), whereas no association was found for the lowest phosphorus category (secondary hyperparathyroidism. Copyright © 2014 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

The comparative role of independent and intervening variables on ...

African Journals Online (AJOL)

The comparative role of independent and intervening variables on ... forced this study to investigate variables that are most important in determining the adoption behaviour. A cross sectional research design was used to collect data from 113 ...

Variability in Antibiotic Use Across PICUs.

Science.gov (United States)

Brogan, Thomas V; Thurm, Cary; Hersh, Adam L; Gerber, Jeffrey S; Smith, Michael J; Shah, Samir S; Courter, Joshua D; Patel, Sameer J; Parker, Sarah K; Kronman, Matthew P; Lee, Brian R; Newland, Jason G

2018-03-10

To characterize and compare antibiotic prescribing across PICUs to evaluate the degree of variability. Retrospective analysis from 2010 through 2014 of the Pediatric Health Information System. Forty-one freestanding children's hospital. Children aged 30 days to 18 years admitted to a PICU in children's hospitals contributing data to Pediatric Health Information System. To normalize for potential differences in disease severity and case mix across centers, a subanalysis was performed of children admitted with one of the 20 All Patient Refined-Diagnosis Related Groups and the seven All Patient Refined-Diagnosis Related Groups shared by all PICUs with the highest antibiotic use. The study included 3,101,201 hospital discharges from 41 institutions with 386,914 PICU patients. All antibiotic use declined during the study period. The median-adjusted antibiotic use among PICU patients was 1,043 days of therapy/1,000 patient-days (interquartile range, 977-1,147 days of therapy/1,000 patient-days) compared with 893 among non-ICU children (interquartile range, 805-968 days of therapy/1,000 patient-days). For PICU patients, the median adjusted use of broad-spectrum antibiotics was 176 days of therapy/1,000 patient-days (interquartile range, 152-217 days of therapy/1,000 patient-days) and was 302 days of therapy/1,000 patient-days (interquartile range, 220-351 days of therapy/1,000 patient-days) for antimethicillin-resistant Staphylococcus aureus agents, compared with 153 days of therapy/1,000 patient-days (interquartile range, 130-182 days of therapy/1,000 patient-days) and 244 days of therapy/1,000 patient-days (interquartile range, 203-270 days of therapy/1,000 patient-days) for non-ICU children. After adjusting for potential confounders, significant institutional variability existed in antibiotic use in PICU patients, in the 20 All Patient Refined-Diagnosis Related Groups with the highest antibiotic usage and in the seven All Patient Refined-Diagnosis Related Groups shared

Variables influencing the frictional behaviour of in vivo human skin

NARCIS (Netherlands)

Veijgen, N.K.; Masen, Marc Arthur; van der Heide, Emile

2013-01-01

In the past decades, skin friction research has focused on determining which variables are important to affect the frictional behaviour of in vivo human skin. Until now, there is still limited knowledge on these variables. This study has used a large dataset to identify the effect of variables on

Imported dengue cases, weather variation and autochthonous dengue incidence in Cairns, Australia.

Directory of Open Access Journals (Sweden)

Xiaodong Huang

Full Text Available BACKGROUND: Dengue fever (DF outbreaks often arise from imported DF cases in Cairns, Australia. Few studies have incorporated imported DF cases in the estimation of the relationship between weather variability and incidence of autochthonous DF. The study aimed to examine the impact of weather variability on autochthonous DF infection after accounting for imported DF cases and then to explore the possibility of developing an empirical forecast system. METHODOLOGY/PRINCIPAL FINDS: Data on weather variables, notified DF cases (including those acquired locally and overseas, and population size in Cairns were supplied by the Australian Bureau of Meteorology, Queensland Health, and Australian Bureau of Statistics. A time-series negative-binomial hurdle model was used to assess the effects of imported DF cases and weather variability on autochthonous DF incidence. Our results showed that monthly autochthonous DF incidences were significantly associated with monthly imported DF cases (Relative Risk (RR:1.52; 95% confidence interval (CI: 1.01-2.28, monthly minimum temperature ((oC (RR: 2.28; 95% CI: 1.77-2.93, monthly relative humidity (% (RR: 1.21; 95% CI: 1.06-1.37, monthly rainfall (mm (RR: 0.50; 95% CI: 0.31-0.81 and monthly standard deviation of daily relative humidity (% (RR: 1.27; 95% CI: 1.08-1.50. In the zero hurdle component, the occurrence of monthly autochthonous DF cases was significantly associated with monthly minimum temperature (Odds Ratio (OR: 1.64; 95% CI: 1.01-2.67. CONCLUSIONS/SIGNIFICANCE: Our research suggested that incidences of monthly autochthonous DF were strongly positively associated with monthly imported DF cases, local minimum temperature and inter-month relative humidity variability in Cairns. Moreover, DF outbreak in Cairns was driven by imported DF cases only under favourable seasons and weather conditions in the study.

Metabolic equivalents of task are confounded by adiposity, which disturbs objective measurement of physical activity

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Tuomo T Tompuri

2015-08-01

Full Text Available Physical activity refers any bodily movements produced by skeletal muscles that expends energy. Hence the amount and the intensity of physical activity can be assessed by energy expenditure. Metabolic equivalents of task (MET are multiplies of the resting metabolism reflecting metabolic rate during exercise. The standard MET is defined as 3.5 ml/min/kg. However, the expression of energy expenditure by body weight to normalize the size differences between subjects causes analytical hazards: scaling by body weight does not have a physiological, mathematical, or physical rationale. This review demonstrates by examples that false methodology may cause paradoxical observations if physical activity would be assessed by body weight scaled values such as standard METs. While standard METs are confounded by adiposity, lean mass proportional measures of energy expenditure would enable a more truthful choice to assess physical activity. While physical activity as a behavior and cardiorespiratory fitness or adiposity as a state represents major determinants of public health, specific measurements of health determinants must be understood to enable a truthful evaluation of the interactions and their independent role as a health predictor.

Comorbidity of intellectual disability confounds ascertainment of autism: implications for genetic diagnosis.

Science.gov (United States)

Polyak, Andrew; Kubina, Richard M; Girirajan, Santhosh

2015-10-01

While recent studies suggest a converging role for genetic factors towards risk for nosologically distinct disorders including autism, intellectual disability (ID), and epilepsy, current estimates of autism prevalence fail to take into account the impact of comorbidity of these disorders on autism diagnosis. We aimed to assess the effect of comorbidity on the diagnosis and prevalence of autism by analyzing 11 years (2000-2010) of special education enrollment data on approximately 6.2 million children per year. We found a 331% increase in the prevalence of autism from 2000 to 2010 within special education, potentially due to a diagnostic recategorization from frequently comorbid features such as ID. The decrease in ID prevalence equaled an average of 64.2% of the increase of autism prevalence for children aged 3-18 years. The proportion of ID cases potentially undergoing recategorization to autism was higher (P = 0.007) among older children (75%) than younger children (48%). Some US states showed significant negative correlations between the prevalence of autism compared to that of ID while others did not, suggesting state-specific health policy to be a major factor in categorizing autism. Further, a high frequency of autistic features was observed when individuals with classically defined genetic syndromes were evaluated for autism using standardized instruments. Our results suggest that current ascertainment practices are based on a single facet of autism-specific clinical features and do not consider associated comorbidities that may confound diagnosis. Longitudinal studies with detailed phenotyping and deep molecular genetic analyses are necessary to completely understand the cause of this complex disorder. © 2015 Wiley Periodicals, Inc.

Two methods for studying the X-ray variability

NARCIS (Netherlands)

Yan, Shu-Ping; Ji, Li; Méndez, Mariano; Wang, Na; Liu, Siming; Li, Xiang-Dong

2016-01-01

The X-ray aperiodic variability and quasi-periodic oscillation (QPO) are the important tools to study the structure of the accretion flow of X-ray binaries. However, the origin of the complex X-ray variability from X-ray binaries remains yet unsolved. We proposed two methods for studying the X-ray

Predicting the importance of current papers.

Energy Technology Data Exchange (ETDEWEB)

Klavans, Richard (SciTech Strategies, Inc., Berwyn, PA); Boyack, Kevin W.

2005-01-01

This article examines how well one can predict the importance of a current paper (a paper that is recently published in the literature). We look at three factors--journal importance, reference importance and author reputation. Citation-based measures of importance are used for all variables. We find that journal importance is the best predictor (explaining 22.3% out of a potential 29.1% of the variance in the data), and that this correlation value varies significantly by discipline. Journal importance is a better predictor of citation in Computer Science than in any other discipline. While the finding supports the present policy of using journal impact statistics as a surrogate for the importance of current papers, it calls into question the present policy of equally weighting current documents in text-based analyses. We suggest that future researchers take into account the expected importance of a document when attempting to describe the cognitive structure of a field.

Dynamics of Variable Mass Systems

Science.gov (United States)

Eke, Fidelis O.

1998-01-01

This report presents the results of an investigation of the effects of mass loss on the attitude behavior of spinning bodies in flight. The principal goal is to determine whether there are circumstances under which the motion of variable mass systems can become unstable in the sense that their transverse angular velocities become unbounded. Obviously, results from a study of this kind would find immediate application in the aerospace field. The first part of this study features a complete and mathematically rigorous derivation of a set of equations that govern both the translational and rotational motions of general variable mass systems. The remainder of the study is then devoted to the application of the equations obtained to a systematic investigation of the effect of various mass loss scenarios on the dynamics of increasingly complex models of variable mass systems. It is found that mass loss can have a major impact on the dynamics of mechanical systems, including a possible change in the systems stability picture. Factors such as nozzle geometry, combustion chamber geometry, propellant's initial shape, size and relative mass, and propellant location can all have important influences on the system's dynamic behavior. The relative importance of these parameters on-system motion are quantified in a way that is useful for design purposes.

Variables influencing the frictional behaviour of in vivo human skin

NARCIS (Netherlands)

Veijgen, N.K.; Masen, M.A.; Heide, E. van der

2013-01-01

In the past decades, skin friction research has focused on determining which variables are important to affect the frictional behaviour of in vivo human skin. Until now, there is still limited knowledge on these variables.This study has used a large dataset to identify the effect of variables on the

Smokers' increased risk for disability pension: social confounding or health-mediated effects? Gender-specific analyses of the Hordaland Health Study cohort.

Science.gov (United States)

Haukenes, Inger; Riise, Trond; Haug, Kjell; Farbu, Erlend; Maeland, John Gunnar

2013-09-01

Studies indicate that cigarette smokers have an increased risk for disability pension, presumably mediated by adverse health effects. However, smoking is also related to socioeconomic status. The current study examined the association between smoking and subsequent disability pension, and whether the association is explained by social confounding and/or health-related mediation. A subsample of 7934 men and 8488 women, aged 40-46, from the Hordaland Health Study, Norway (1997-1999), provided baseline information on smoking status, self-reported health measures and socioeconomic status. Outcome was register-based disability pension from 12 months after baseline to end of 2004. Gender stratified Cox regression analyses were used adjusted for socioeconomic status, physical activity, self-reported health and musculoskeletal pain sites. A total of 155 (2%) men and 333 (3.9%) women were granted disability pension during follow-up. The unadjusted disability risk associated with heavy smoking versus non-smoking was 1.88 (95% CI 1.23 to 2.89) among men and 3.06 (95% CI 2.23 to 4.20) among women. In multivariate analyses, adjusting for socioeconomic status, HRs were 1.33 (95% CI 0.84 to 2.11) among men and 2.22 (95% CI 1.58 to 3.13) among women. Final adjustment for physical activity, self-reported health and musculoskeletal pain further reduced the effect of heavy smoking in women (HR=1.53, 95% CI 1.09 to 2.16). Socioeconomic status confounded the smoking-related risk for disability pension; for female heavy smokers, however, a significant increased risk persisted after adjustment. Women may be particularly vulnerable to heavy smoking and to its sociomedical consequences, such as disability pension.

Air temperature variability in a high-elevation Himalayan catchment

NARCIS (Netherlands)

Heynen, Martin; Miles, Evan; Ragettli, Silvan; Buri, Pascal; Immerzeel, Walter W.; Pellicciotti, Francesca

2016-01-01

Air temperature is a key control of processes affecting snow and glaciers in high-elevation catchments, including melt, snowfall and sublimation. It is therefore a key input variable to models of land-surface-atmosphere interaction. Despite this importance, its spatial variability is poorly

Risk variables in evaluation of transport projects

Science.gov (United States)

Vařbuchta, Petr; Kovářová, Hana; Hromádka, Vít; Vítková, Eva

2017-09-01

Depending on the constantly increasing demands on assessment of investment projects, especially assessment of large-scale projects in transport and important European projects with wide impacts, there is constantly increasing focus on risk management, whether to find mitigations, creating corrective measures or their implementation in assessment, especially in the context of Cost-Benefit analysis. To project assessment is often used implementation of certain risk variables, which can generate negative impacts of project outputs in framework of assess. Especially in case of transportation infrastructure projects is taken much emphasis on the influence of risk variables. However, currently in case of assessment of transportation projects is in Czech Republic used a few risk variables, which occur in the most projects. This leads to certain limitation in framework of impact assessment of risk variables. This papers aims to specify a new risk variables and process of applying them to already executed project assessment. Based on changes generated by new risk variables will be evaluated differences between original and adapted assessment.

Common characterization of variability and forecast errors of variable energy sources and their mitigation using reserves in power system integration studies

Energy Technology Data Exchange (ETDEWEB)

Menemenlis, N.; Huneault, M. [IREQ, Varennes, QC (Canada); Robitaille, A. [Dir. Plantif. de la Production Eolienne, Montreal, QC (Canada). HQ Production; Holttinen, H. [VTT Technical Research Centre of Finland, VTT (Finland)

2012-07-01

This In this paper we define and characterize the two random variables, variability and forecast error, over which uncertainty in power systems operations is characterized and mitigated. We show that the characterization of both these variables can be carried out with the same mathematical tools. Furthermore, this common characterization of random variables lends itself to a common methodology for the calculation of non-contingency reserves required to mitigate their effects. A parallel comparison of these two variables demonstrates similar inherent statistical properties. They depend on imminent conditions, evolve with time and can be asymmetric. Correlation is an important factor when aggregating individual wind farm characteristics in forming the distribution of the total wind generation for imminent conditions. (orig.)

Who are private alcohol importers in the Nordic countries?

Directory of Open Access Journals (Sweden)

Grittner Ulrike

2014-04-01

Full Text Available Aims - The high price of alcohol in the Nordic countries has been a long-standing policy to curb consumption, which has led consumers to importing alcohol from countries with lower prices. This paper seeks to develop a profile of alcohol importers in four Nordic countries. Methods - Cross-sectional data from general population surveys in Denmark (2003-2006, Norway (2004, Sweden (2003-2006 and Finland (2005-2006 were analysed by multiple logistic and linear regression. Independent variables included region, socio-demographics, drinking indicators and alcohol-related problems. Outcome variables were importer status and amount of imported alcohol. Results - People living in regions close to countries with lower alcohol prices were more often importers and imported higher amounts than people living in other regions. Higher educated persons were more likely to be importers, but the amounts imported were smaller than those by people with lower education. Persons with higher incomes were also more likely to be importers and they also imported larger amounts than people with lower incomes. In Sweden and Denmark regional differences of importer rates were more pronounced for persons of lower incomes. Age, risky single-occasion drinking, risky drinking and alcohol problems were positively related to the amounts of imported alcohol. Conclusions - Private importers in the Nordic countries are an integrated yet heavy drinking segment of society and do not appear to be located on the fringes of society

Identification and Sensitivity Analysis for Average Causal Mediation Effects with Time-Varying Treatments and Mediators: Investigating the Underlying Mechanisms of Kindergarten Retention Policy.

Science.gov (United States)

Park, Soojin; Steiner, Peter M; Kaplan, David

2018-06-01

Considering that causal mechanisms unfold over time, it is important to investigate the mechanisms over time, taking into account the time-varying features of treatments and mediators. However, identification of the average causal mediation effect in the presence of time-varying treatments and mediators is often complicated by time-varying confounding. This article aims to provide a novel approach to uncovering causal mechanisms in time-varying treatments and mediators in the presence of time-varying confounding. We provide different strategies for identification and sensitivity analysis under homogeneous and heterogeneous effects. Homogeneous effects are those in which each individual experiences the same effect, and heterogeneous effects are those in which the effects vary over individuals. Most importantly, we provide an alternative definition of average causal mediation effects that evaluates a partial mediation effect; the effect that is mediated by paths other than through an intermediate confounding variable. We argue that this alternative definition allows us to better assess at least a part of the mediated effect and provides meaningful and unique interpretations. A case study using ECLS-K data that evaluates kindergarten retention policy is offered to illustrate our proposed approach.

Variable Selection via Partial Correlation.

Science.gov (United States)

Li, Runze; Liu, Jingyuan; Lou, Lejia

2017-07-01

Partial correlation based variable selection method was proposed for normal linear regression models by Bühlmann, Kalisch and Maathuis (2010) as a comparable alternative method to regularization methods for variable selection. This paper addresses two important issues related to partial correlation based variable selection method: (a) whether this method is sensitive to normality assumption, and (b) whether this method is valid when the dimension of predictor increases in an exponential rate of the sample size. To address issue (a), we systematically study this method for elliptical linear regression models. Our finding indicates that the original proposal may lead to inferior performance when the marginal kurtosis of predictor is not close to that of normal distribution. Our simulation results further confirm this finding. To ensure the superior performance of partial correlation based variable selection procedure, we propose a thresholded partial correlation (TPC) approach to select significant variables in linear regression models. We establish the selection consistency of the TPC in the presence of ultrahigh dimensional predictors. Since the TPC procedure includes the original proposal as a special case, our theoretical results address the issue (b) directly. As a by-product, the sure screening property of the first step of TPC was obtained. The numerical examples also illustrate that the TPC is competitively comparable to the commonly-used regularization methods for variable selection.

Correlated Temporal and Spectral Variability

Science.gov (United States)

Swank, Jean H.

2007-01-01

The variability of neutron star and black hole X-ray sources has several dimensions, because of the roles played by different important time-scales. The variations on time scales of hours, weeks, and months, ranging from 50% to orders of magnitude, arise out of changes in the flow in the disk. The most important driving forces for those changes are probably various possible instabilities in the disk, though there may be effects with other dominant causes. The changes in the rate of flow appear to be associated with changes in the flow's configuration, as the accreting material approaches the compact object, for there are generally correlated changes in both the Xray spectra and the character of the faster temporal variability. There has been a lot of progress in tracking these correlations, both for Z and Atoll neutron star low-mass X-ray binaries, and for black hole binaries. I will discuss these correlations and review briefly what they tell us about the physical states of the systems.

Long-Term Variability of Surface Albedo and Its Correlation with Climatic Variables over Antarctica

Directory of Open Access Journals (Sweden)

Minji Seo

2016-11-01

Full Text Available The cryosphere is an essential part of the earth system for understanding climate change. Components of the cryosphere, such as ice sheets and sea ice, are generally decreasing over time. However, previous studies have indicated differing trends between the Antarctic and the Arctic. The South Pole also shows internal differences in trends. These phenomena indicate the importance of continuous observation of the Polar Regions. Albedo is a main indicator for analyzing Antarctic climate change and is an important variable with regard to the radiation budget because it can provide positive feedback on polar warming and is related to net radiation and atmospheric heating in the mainly snow- and ice-covered Antarctic. Therefore, in this study, we analyzed long-term temporal and spatial variability of albedo and investigated the interrelationships between albedo and climatic variables over Antarctica. We used broadband surface albedo data from the Satellite Application Facility on Climate Monitoring and data for several climatic variables such as temperature and Antarctic oscillation index (AAO during the period of 1983 to 2009. Time series analysis and correlation analysis were performed through linear regression using albedo and climatic variables. The results of this research indicated that albedo shows two trends, west trend and an east trend, over Antarctica. Most of the western side of Antarctica showed a negative trend of albedo (about −0.0007 to −0.0015 year−1, but the other side showed a positive trend (about 0.0006 year−1. In addition, albedo and surface temperature had a negative correlation, but this relationship was weaker in west Antarctica than in east Antarctica. The correlation between albedo and AAO revealed different relationships in the two regions; west Antarctica had a negative correlation and east Antarctica showed a positive correlation. In addition, the correlation between albedo and AAO was weaker in the west. This

Precipitation variability increases in a warmer climate.

Science.gov (United States)

Pendergrass, Angeline G; Knutti, Reto; Lehner, Flavio; Deser, Clara; Sanderson, Benjamin M

2017-12-21

Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle's response to warming and its impacts. While changes in mean and extreme precipitation have been studied intensively, precipitation variability has received less attention, despite its theoretical and practical importance. Here, we show that precipitation variability in most climate models increases over a majority of global land area in response to warming (66% of land has a robust increase in variability of seasonal-mean precipitation). Comparing recent decades to RCP8.5 projections for the end of the 21 st century, we find that in the global, multi-model mean, precipitation variability increases 3-4% K -1 globally, 4-5% K -1 over land and 2-4% K -1 over ocean, and is remarkably robust on a range of timescales from daily to decadal. Precipitation variability increases by at least as much as mean precipitation and less than moisture and extreme precipitation for most models, regions, and timescales. We interpret this as being related to an increase in moisture which is partially mitigated by weakening circulation. We show that changes in observed daily variability in station data are consistent with increased variability.

The prognostic importance of lung function in patients admitted with heart failure

DEFF Research Database (Denmark)

Iversen, Kasper Karmark; Kjaergaard, Jesper; Akkan, Dilek

2010-01-01

The purpose of the present study was to determine the prognostic importance for all-cause mortality of lung function variables obtained by spirometry in an unselected group of patients admitted with heart failure (HF).......The purpose of the present study was to determine the prognostic importance for all-cause mortality of lung function variables obtained by spirometry in an unselected group of patients admitted with heart failure (HF)....

The Marketplace Variables in Successful and Unsuccessful NPD Projects in Technology Intensive Companies

Directory of Open Access Journals (Sweden)

Matti J. Haverila

2010-12-01

Our findings indicate that managers perceive the marketplace in multiple ways during the NPD process and also that differences exist in metric equivalence across successful and unsuccessful NPD projects. Also, although half of the marketplace variables are positively related to NPD success, managers in Finnish technology companies appear to attach higher relative importance to market attractiveness rather than market competitiveness variables. Marketplace variables appear to be less important than in the Korean and Chinese samples, and much more important than  in the Canadian sample in the Mishra et all study (1996, and similarly much more important than in the Cooper study (1979b.

Statistical identification of effective input variables

International Nuclear Information System (INIS)

Vaurio, J.K.

1982-09-01

A statistical sensitivity analysis procedure has been developed for ranking the input data of large computer codes in the order of sensitivity-importance. The method is economical for large codes with many input variables, since it uses a relatively small number of computer runs. No prior judgemental elimination of input variables is needed. The sceening method is based on stagewise correlation and extensive regression analysis of output values calculated with selected input value combinations. The regression process deals with multivariate nonlinear functions, and statistical tests are also available for identifying input variables that contribute to threshold effects, i.e., discontinuities in the output variables. A computer code SCREEN has been developed for implementing the screening techniques. The efficiency has been demonstrated by several examples and applied to a fast reactor safety analysis code (Venus-II). However, the methods and the coding are general and not limited to such applications

Egg number-egg size: an important trade-off in parasite life history strategies.

Science.gov (United States)

Cavaleiro, Francisca I; Santos, Maria J

2014-03-01

Parasites produce from just a few to many eggs of variable size, but our understanding of the factors driving variation in these two life history traits at the intraspecific level is still very fragmentary. This study evaluates the importance of performing multilevel analyses on egg number and egg size, while characterising parasite life history strategies. A total of 120 ovigerous females of Octopicola superba (Copepoda: Octopicolidae) (one sample (n=30) per season) were characterised with respect to different body dimensions (total length; genital somite length) and measures of reproductive effort (fecundity; mean egg diameter; total reproductive effort; mean egg sac length). While endoparasites are suggested to follow both an r- and K-strategy simultaneously, the evidence found in this and other studies suggests that environmental conditions force ectoparasites into one of the two alternatives. The positive and negative skewness of the distributions of fecundity and mean egg diameter, respectively, suggest that O. superba is mainly a K-strategist (i.e. produces a relatively small number of large, well provisioned eggs). Significant sample differences were recorded concomitantly for all body dimensions and measures of reproductive effort, while a general linear model detected a significant influence of season*parasite total length in both egg number and size. This evidence suggests adaptive phenotypic plasticity in body dimensions and size-mediated changes in egg production. Seasonal changes in partitioning of resources between egg number and size resulted in significant differences in egg sac length but not in total reproductive effort. Evidence for a trade-off between egg number and size was found while controlling for a potential confounding effect of parasite total length. However, this trade-off became apparent only at high fecundity levels, suggesting a state of physiological exhaustion. Copyright © 2014 Australian Society for Parasitology Inc. Published

Complex variables

CERN Document Server

Flanigan, Francis J

2010-01-01

A caution to mathematics professors: Complex Variables does not follow conventional outlines of course material. One reviewer noting its originality wrote: ""A standard text is often preferred [to a superior text like this] because the professor knows the order of topics and the problems, and doesn't really have to pay attention to the text. He can go to class without preparation."" Not so here-Dr. Flanigan treats this most important field of contemporary mathematics in a most unusual way. While all the material for an advanced undergraduate or first-year graduate course is covered, discussion

Ecological and evolutionary impacts of changing climatic variability.

Science.gov (United States)

Vázquez, Diego P; Gianoli, Ernesto; Morris, William F; Bozinovic, Francisco

2017-02-01

While average temperature is likely to increase in most locations on Earth, many places will simultaneously experience higher variability in temperature, precipitation, and other climate variables. Although ecologists and evolutionary biologists widely recognize the potential impacts of changes in average climatic conditions, relatively little attention has been paid to the potential impacts of changes in climatic variability and extremes. We review the evidence on the impacts of increased climatic variability and extremes on physiological, ecological and evolutionary processes at multiple levels of biological organization, from individuals to populations and communities. Our review indicates that climatic variability can have profound influences on biological processes at multiple scales of organization. Responses to increased climatic variability and extremes are likely to be complex and cannot always be generalized, although our conceptual and methodological toolboxes allow us to make informed predictions about the likely consequences of such climatic changes. We conclude that climatic variability represents an important component of climate that deserves further attention. © 2015 Cambridge Philosophical Society.

Identifying the important factors in simulation models with many factors

NARCIS (Netherlands)

Bettonvil, B.; Kleijnen, J.P.C.

1994-01-01

Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The

Visualization of Variation and Variability

NARCIS (Netherlands)

Busking, S.

2014-01-01

As datasets grow in size and complexity, the importance of comparison as a tool for analysis is growing. We define comparison as the act of analyzing variation or variability based on two or more specific instances of the data. This thesis explores a number of cases spread across the range of

Long-Term Variability in o Ceti and Other Mira Variables: Signs of Supergranular Convection?

Science.gov (United States)

Templeton, Matthew R.; Karovska, Margarita

2009-09-01

We describe our study of long-term variability of o Ceti (Mira A), the prototype of the Mira-type pulsating stars. Our study was originally undertaken to search for coherent long-period variability, but the results of our analysis didn't uncover this. However, we detected a low-frequency ``red noise'' in the Fourier spectrum of the o Ceti century-long light curve. We have since found similar behavior in other Miras and pulsating giant stars and have begun a study of a large sample of Mira variables. Similar red noise has been previously detected in red supergiants and attributed to supergranular convection. Its presence in Miras suggests the phenomenon may be ubiquitous in cool giant pulsators. These results support high-angular resolution observations of Miras and supergiants showing asymmetries in their surface brightness distributions, which may be due to large supergranular convection cells. Theoretical modeling, and numerical simulations of pulsation processes in late-type giants and supergiants should therefore take into account the effects of deep convection and large supergranular structures, which in turn may provide important insights into the behavior of Miras and other giant and supergiant pulsators. In this work, we summarize our results for o Ceti, present preliminary results of our broader study of Mira variables, and discuss how the results of this study may be used by future studies of AGB variables.

Evaluation to the aspen for the air pollution monitoring

International Nuclear Information System (INIS)

De La Rosa, D.; Lima, L.; Santana, J.L.; Olivares, S.; Martin, R.; Garcia, M.

2003-01-01

Aspen is not often used in bio monitoring programs, but when it is, several interacting and confounding variables have to be considered. Biomass of leaves, and height changes are not easy linked with air pollution, whereas dry weight and leaf abscission are. Visible injury diagnosis and crown thinning are useful records for bio monitoring programs to consider, but skill and understanding of air pollution effects versus seasonal effects are very important. Understanding of actual air pollution symptoms and elemental ratios are especially important. Clonal response and heritability is discuses below, and has to be considered in any bio monitoring program. Above all, integration of aspen response with other key variables is key

Handbook of latent variable and related models

CERN Document Server

Lee, Sik-Yum

2011-01-01

This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.- Covers a wide class of important models- Models and statistical methods described provide tools for analyzing a wide spectrum of complicated data- Includes illustrative examples with real data sets from business, education, medicine, public health and sociology.- Demonstrates the use of a wide variety of statistical, computational, and mathematical techniques.

Nonalcoholic fatty liver disease and sarcopenia in a Western population (NHANES III): The importance of sarcopenia definition.

Science.gov (United States)

Peng, Tao-Chun; Wu, Li-Wei; Chen, Wei-Liang; Liaw, Fang-Yih; Chang, Yaw-Wen; Kao, Tung-Wei

2017-12-08

Recent epidemiological studies have shown that sarcopenia is associated with non-alcoholic fatty liver disease (NAFLD) and advanced fibrosis in an Asian population. We investigated whether NAFLD is associated with a higher risk of sarcopenia using a different definition in elderly patients. A population-based cross-sectional survey of US patients was conducted, involving 2551 participants aged 60-75 years. NAFLD was measured by ultrasound. Sarcopenia was defined by both a low muscle mass and poor muscle function. In addition, the skeletal muscle index (SMI) was calculated as the absolute muscle mass (kilograms) divided by height 2 (meters) or total body mass (kilograms). A multivariable logistic regression was conducted to estimate the relationship between sarcopenia and NAFLD in the elderly. After adjusting for age, sex, and race/ethnicity, severe hepatic steatosis was associated with a decreased risk of sarcopenia as defined by the height-adjusted SMI (odds ratio (OR) 0.63; 95% confidence interval (CI) 0.46-0.87). In contrast, severe hepatic steatosis was associated with an increased risk of sarcopenia as defined by the weight-adjusted SMI (OR 1.73; 95% CI 1.31-2.28). These significant associations remained after further adjustments for other potential confounding variables. NAFLD is associated with a lower risk of sarcopenia when using the height-adjusted SMI. In contrast, it showed the opposite result when using the weight-adjusted SMI. The definition of sarcopenia may be an important factor when examining its relationship with NAFLD. Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Distance to High-Voltage Power Lines and Risk of Childhood Leukemia – an Analysis of Confounding by and Interaction with Other Potential Risk Factors

DEFF Research Database (Denmark)

Pedersen, Camilla; Bräuner, Elvira V; Rod, Naja Hulvej

2014-01-01

. We used geographical information systems to determine the distance between residence at birth and the nearest 132-400 kV overhead power line. Concentrations of domestic radon and traffic-related air pollution (NOx at the front door) were estimated using validated models. We found a statistically......We investigated whether there is an interaction between distance from residence at birth to nearest power line and domestic radon and traffic-related air pollution, respectively, in relation to childhood leukemia risk. Further, we investigated whether adjusting for potential confounders alters...

Variable ordering structures in vector optimization

CERN Document Server

Eichfelder, Gabriele

2014-01-01

This book provides an introduction to vector optimization with variable ordering structures, i.e., to optimization problems with a vector-valued objective function where the elements in the objective space are compared based on a variable ordering structure: instead of a partial ordering defined by a convex cone, we see a whole family of convex cones, one attached to each element of the objective space. The book starts by presenting several applications that have recently sparked new interest in these optimization problems, and goes on to discuss fundamentals and important results on a wide ra

Importance and variability in processes relevant to environmental tritium ingestion dose models

International Nuclear Information System (INIS)

Raskob, W.; Barry, P.

1997-01-01

The Aiken List was devised in 1990 to help decide which transport processes should be investigated experimentally so as to derive the greatest improvement in performance of environmental tritium assessment models. Each process was rated high, medium and low on each of two criteria. These were ''Importance'', which rated processes by how much each contributed to ingestion doses, and ''State of Modelling'', which rated the adequacy of the knowledge base on which models were built. Ratings, though unanimous, were, nevertheless, qualitative and subjective opinions. This paper describes how we have tried to quantify the ratings. To do this, we use, as measures of ''Importance'', sensitivities of predicted ingestion doses to changes in values of parameters in mathematical descriptions of individual processes. Measures of ''ModellinStatus'' were taken from a recently completed BIOMOVS study of HTO transport model performance and based either on by how much predicted transport by individual processes differed amongst participating modellers or by the variety of different ways that modellers chose to describe individual processes. The tritium transport model UFOTRI was used, and because environmental transport of HTO varies according to the weather at and after release time, sensitivities were measured in a sample of all conditions likely to arise in central Europe. (Author)

Important aspects of Eastern Mediterranean large-scale variability revealed from data of three fixed observatories

Science.gov (United States)

Bensi, Manuel; Velaoras, Dimitris; Cardin, Vanessa; Perivoliotis, Leonidas; Pethiakis, George

2015-04-01

Long-term variations of temperature and salinity observed in the Adriatic and Aegean Seas seem to be regulated by larger-scale circulation modes of the Eastern Mediterranean (EMed) Sea, such as the recently discovered feedback mechanisms, namely the BiOS (Bimodal Oscillating System) and the internal thermohaline pump theories. These theories are the results of interpretation of many years' observations, highlighting possible interactions between two key regions of the EMed. Although repeated oceanographic cruises carried out in the past or planned for the future are a very useful tool for understanding the interaction between the two basins (e.g. alternating dense water formation, salt ingressions), recent long time-series of high frequency (up to 1h) sampling have added valuable information to the interpretation of internal mechanisms for both areas (i.e. mesoscale eddies, evolution of fast internal processes, etc.). During the last 10 years, three deep observatories were deployed and maintained in the Adriatic, Ionian, and Aegean Seas: they are respectively, the E2-M3A, the Pylos, and the E1-M3A. All are part of the largest European network of Fixed Point Open Ocean Observatories (FixO3, http://www.fixo3.eu/). Herein, from the analysis of temperature and salinity, and potential density time series collected at the three sites from the surface down to the intermediate and deep layers, we will discuss the almost perfect anti-correlated behavior between the Adriatic and the Aegean Seas. Our data, collected almost continuously since 2006, reveal that these observatories well represent the thermohaline variability of their own areas. Interestingly, temperature and salinity in the intermediate layer suddenly increased in the South Adriatic from the end of 2011, exactly when they started decreasing in the Aegean Sea. Moreover, Pylos data used together with additional ones (e.g. Absolute dynamic topography, temperature and salinity data from other platforms) collected

Quantum teleportation for continuous variables and related quantum information processing

International Nuclear Information System (INIS)

Furusawa, Akira; Takei, Nobuyuki

2007-01-01

Quantum teleportation is one of the most important subjects in quantum information science. This is because quantum teleportation can be regarded as not only quantum information transfer but also a building block for universal quantum information processing. Furthermore, deterministic quantum information processing is very important for efficient processing and it can be realized with continuous-variable quantum information processing. In this review, quantum teleportation for continuous variables and related quantum information processing are reviewed from these points of view

Disparities in lifestyle habits and health related factors of Montreal immigrants: is immigration an important exposure variable in public health?

Science.gov (United States)

Meshefedjian, Garbis A; Leaune, Viviane; Simoneau, Marie-Ève; Drouin, Mylène

2014-10-01

Study disparities in lifestyle habits and health characteristics of Canadian born population and immigrants with different duration of residence. Data are extracted from 2009 to 2010 public use micro-data files of Canadian Community Health Survey representing about 1.5 million people. Sixty-one percent of the study sample was born in Canada; 49 % males and 59 % below age 50. Amongst lifestyle habits, recent immigrants were less likely to be regular smokers, RR (95 % CI) 0.56 (0.36-0.88) and frequent consumers of alcohol 0.49 (0.27-0.89), but more likely to consume less fruits and vegetables 1.26 (1.04-1.53) than those born in Canada. Amongst health related factors, recent immigrants were less likely to be overweight 0.79 (0.62-0.99) and suffer from chronic diseases 0.59 (0.44-0.80), but more likely to have limited access to family medicine 1.24 (1.04-1.47) than Canada-born population. Immigration status is an important population characteristic which influenced distribution of health indicators. Prevention and promotion strategies should consider immigration status as an exposure variable in the development and implementation of public health programs.

Cartesian integration of Grassmann variables over invariant functions

Energy Technology Data Exchange (ETDEWEB)

Kieburg, Mario; Kohler, Heiner; Guhr, Thomas [Universitaet Duisburg-Essen, Duisburg (Germany)

2009-07-01

Supersymmetry plays an important role in field theory as well as in random matrix theory and mesoscopic physics. Anticommuting variables are the fundamental objects of supersymmetry. The integration over these variables is equivalent to the derivative. Recently[arxiv:0809.2674v1[math-ph] (2008)], we constructed a differential operator which only acts on the ordinary part of the superspace consisting of ordinary and anticommuting variables. This operator is equivalent to the integration over all anticommuting variables of an invariant function. We present this operator and its applications for functions which are rotation invariant under the supergroups U(k{sub 1}/k{sub 2}) and UOSp(k{sub 1}/k{sub 2}).

Risks and rewards of variable-rate debt.

Science.gov (United States)

Jordahl, Eric A

2012-05-01

Hospital and health system finance leaders should position their organizations to participate in the variable-rate market. To this end, one important step is to establish the right baseline variable-rate exposure target for the organization based on its credit and risk profile. Leaders also should be thoroughly familiar with the available products and understand the circumstances (pricing, terms, and embedded risk) under which the organization would be willing to deploy them within the overall capital structure.

Pattern classification of brain activation during emotional processing in subclinical depression: psychosis proneness as potential confounding factor.

Science.gov (United States)

Modinos, Gemma; Mechelli, Andrea; Pettersson-Yeo, William; Allen, Paul; McGuire, Philip; Aleman, Andre

2013-01-01

We used Support Vector Machine (SVM) to perform multivariate pattern classification based on brain activation during emotional processing in healthy participants with subclinical depressive symptoms. Six-hundred undergraduate students completed the Beck Depression Inventory II (BDI-II). Two groups were subsequently formed: (i) subclinical (mild) mood disturbance (n = 17) and (ii) no mood disturbance (n = 17). Participants also completed a self-report questionnaire on subclinical psychotic symptoms, the Community Assessment of Psychic Experiences Questionnaire (CAPE) positive subscale. The functional magnetic resonance imaging (fMRI) paradigm entailed passive viewing of negative emotional and neutral scenes. The pattern of brain activity during emotional processing allowed correct group classification with an overall accuracy of 77% (p = 0.002), within a network of regions including the amygdala, insula, anterior cingulate cortex and medial prefrontal cortex. However, further analysis suggested that the classification accuracy could also be explained by subclinical psychotic symptom scores (correlation with SVM weights r = 0.459, p = 0.006). Psychosis proneness may thus be a confounding factor for neuroimaging studies in subclinical depression.

Invited Commentary: Using Financial Credits as Instrumental Variables for Estimating the Causal Relationship Between Income and Health.

Science.gov (United States)

Pega, Frank

2016-05-01

Social epidemiologists are interested in determining the causal relationship between income and health. Natural experiments in which individuals or groups receive income randomly or quasi-randomly from financial credits (e.g., tax credits or cash transfers) are increasingly being analyzed using instrumental variable analysis. For example, in this issue of the Journal, Hamad and Rehkopf (Am J Epidemiol. 2016;183(9):775-784) used an in-work tax credit called the Earned Income Tax Credit as an instrument to estimate the association between income and child development. However, under certain conditions, the use of financial credits as instruments could violate 2 key instrumental variable analytic assumptions. First, some financial credits may directly influence health, for example, through increasing a psychological sense of welfare security. Second, financial credits and health may have several unmeasured common causes, such as politics, other social policies, and the motivation to maximize the credit. If epidemiologists pursue such instrumental variable analyses, using the amount of an unconditional, universal credit that an individual or group has received as the instrument may produce the most conceptually convincing and generalizable evidence. However, other natural income experiments (e.g., lottery winnings) and other methods that allow better adjustment for confounding might be more promising approaches for estimating the causal relationship between income and health. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Nonlinear Predictive Models for Multiple Mediation Analysis: With an Application to Explore Ethnic Disparities in Anxiety and Depression Among Cancer Survivors.

Science.gov (United States)

Yu, Qingzhao; Medeiros, Kaelen L; Wu, Xiaocheng; Jensen, Roxanne E

2018-04-02

Mediation analysis allows the examination of effects of a third variable (mediator/confounder) in the causal pathway between an exposure and an outcome. The general multiple mediation analysis method (MMA), proposed by Yu et al., improves traditional methods (e.g., estimation of natural and controlled direct effects) to enable consideration of multiple mediators/confounders simultaneously and the use of linear and nonlinear predictive models for estimating mediation/confounding effects. Previous studies find that compared with non-Hispanic cancer survivors, Hispanic survivors are more likely to endure anxiety and depression after cancer diagnoses. In this paper, we applied MMA on MY-Health study to identify mediators/confounders and quantify the indirect effect of each identified mediator/confounder in explaining ethnic disparities in anxiety and depression among cancer survivors who enrolled in the study. We considered a number of socio-demographic variables, tumor characteristics, and treatment factors as potential mediators/confounders and found that most of the ethnic differences in anxiety or depression between Hispanic and non-Hispanic white cancer survivors were explained by younger diagnosis age, lower education level, lower proportions of employment, less likely of being born in the USA, less insurance, and less social support among Hispanic patients.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering.

Science.gov (United States)

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor; Essex, M

2015-05-01

To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System

Science.gov (United States)

Turksoy, Kamuran; Monforti, Colleen; Park, Minsun; Griffith, Garett; Quinn, Laurie; Cinar, Ali

2017-01-01

An artificial pancreas (AP) computes the optimal insulin dose to be infused through an insulin pump in people with Type 1 Diabetes (T1D) based on information received from a continuous glucose monitoring (CGM) sensor. It has been recognized that exercise is a major challenge in the development of an AP system. The use of biometric physiological variables in an AP system may be beneficial for prevention of exercise-induced challenges and better glucose regulation. The goal of the present study is to find a correlation between biometric variables such as heart rate (HR), heat flux (HF), skin temperature (ST), near-body temperature (NBT), galvanic skin response (GSR), and energy expenditure (EE), 2D acceleration-mean of absolute difference (MAD) and changes in glucose concentrations during exercise via partial least squares (PLS) regression and variable importance in projection (VIP) in order to determine which variables would be most useful to include in a future artificial pancreas. PLS and VIP analyses were performed on data sets that included seven different types of exercises. Data were collected from 26 clinical experiments. Clinical results indicate ST to be the most consistently important (important for six out of seven tested exercises) variable over all different exercises tested. EE and HR are also found to be important variables over several types of exercise. We also found that the importance of GSR and NBT observed in our experiments might be related to stress and the effect of changes in environmental temperature on glucose concentrations. The use of the biometric measurements in an AP system may provide better control of glucose concentration. PMID:28272368

Glacier variability in the conterminous United States during the twentieth century

Science.gov (United States)

McCabe, Gregory J.; Fountain, Andrew G.

2013-01-01

Glaciers of the conterminous United States have been receding for the past century. Since 1900 the recession has varied from a 24 % loss in area (Mt. Rainier, Washington) to a 66 % loss in the Lewis Range of Montana. The rates of retreat are generally similar with a rapid loss in the early decades of the 20th century, slowing in the 1950s–1970s, and a resumption of rapid retreat starting in the 1990s. Decadal estimates of changes in glacier area for a subset of 31 glaciers from 1900 to 2000 are used to test a snow water equivalent model that is subsequently employed to examine the effects of temperature and precipitation variability on annual glacier area changes for these glaciers. Model results indicate that both winter precipitation and winter temperature have been important climatic factors affecting the variability of glacier variability during the 20th Century. Most of the glaciers analyzed appear to be more sensitive to temperature variability than to precipitation variability. However, precipitation variability is important, especially for high elevation glaciers. Additionally, glaciers with areas greater than 1 km2 are highly sensitive to variability in temperature.

Bilingualism delays age at onset of dementia, independent of education and immigration status.

Science.gov (United States)

Mortimer, James A

2014-05-27

Editors' Note: Mortimer argues that important confounding variables may have biased the conclusion by Alladi et al. on the role of bilingualism in delaying the onset of dementia. Following Mortimer’s comments, Alladi et al. conducted additional analysis of their data to support their conclusion. The attitude of "close enough" is not appropriate when determining brain death. Stadlan comments and supports Frank’s call for action regarding this sensitive issue.

Variable screening and ranking using sampling-based sensitivity measures

International Nuclear Information System (INIS)

Wu, Y-T.; Mohanty, Sitakanta

2006-01-01

This paper presents a methodology for screening insignificant random variables and ranking significant important random variables using sensitivity measures including two cumulative distribution function (CDF)-based and two mean-response based measures. The methodology features (1) using random samples to compute sensitivities and (2) using acceptance limits, derived from the test-of-hypothesis, to classify significant and insignificant random variables. Because no approximation is needed in either the form of the performance functions or the type of continuous distribution functions representing input variables, the sampling-based approach can handle highly nonlinear functions with non-normal variables. The main characteristics and effectiveness of the sampling-based sensitivity measures are investigated using both simple and complex examples. Because the number of samples needed does not depend on the number of variables, the methodology appears to be particularly suitable for problems with large, complex models that have large numbers of random variables but relatively few numbers of significant random variables

MetabR: an R script for linear model analysis of quantitative metabolomic data

Directory of Open Access Journals (Sweden)

Ernest Ben

2012-10-01

Full Text Available Abstract Background Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings Here we present a simple menu-driven program, “MetabR”, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/.

On heart rate variability and autonomic activity in homeostasis and in systemic inflammation.

Science.gov (United States)

Scheff, Jeremy D; Griffel, Benjamin; Corbett, Siobhan A; Calvano, Steve E; Androulakis, Ioannis P

2014-06-01

Analysis of heart rate variability (HRV) is a promising diagnostic technique due to the noninvasive nature of the measurements involved and established correlations with disease severity, particularly in inflammation-linked disorders. However, the complexities underlying the interpretation of HRV complicate understanding the mechanisms that cause variability. Despite this, such interpretations are often found in literature. In this paper we explored mathematical modeling of the relationship between the autonomic nervous system and the heart, incorporating basic mechanisms such as perturbing mean values of oscillating autonomic activities and saturating signal transduction pathways to explore their impacts on HRV. We focused our analysis on human endotoxemia, a well-established, controlled experimental model of systemic inflammation that provokes changes in HRV representative of acute stress. By contrasting modeling results with published experimental data and analyses, we found that even a simple model linking the autonomic nervous system and the heart confound the interpretation of HRV changes in human endotoxemia. Multiple plausible alternative hypotheses, encoded in a model-based framework, equally reconciled experimental results. In total, our work illustrates how conventional assumptions about the relationships between autonomic activity and frequency-domain HRV metrics break down, even in a simple model. This underscores the need for further experimental work towards unraveling the underlying mechanisms of autonomic dysfunction and HRV changes in systemic inflammation. Understanding the extent of information encoded in HRV signals is critical in appropriately analyzing prior and future studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Exploratory regression analysis: a tool for selecting models and determining predictor importance.

Science.gov (United States)

Braun, Michael T; Oswald, Frederick L

2011-06-01

Linear regression analysis is one of the most important tools in a researcher's toolbox for creating and testing predictive models. Although linear regression analysis indicates how strongly a set of predictor variables, taken together, will predict a relevant criterion (i.e., the multiple R), the analysis cannot indicate which predictors are the most important. Although there is no definitive or unambiguous method for establishing predictor variable importance, there are several accepted methods. This article reviews those methods for establishing predictor importance and provides a program (in Excel) for implementing them (available for direct download at http://dl.dropbox.com/u/2480715/ERA.xlsm?dl=1) . The program investigates all 2(p) - 1 submodels and produces several indices of predictor importance. This exploratory approach to linear regression, similar to other exploratory data analysis techniques, has the potential to yield both theoretical and practical benefits.

Statistical Metadata Analysis of the Variability of Latency, Device Transfer Time, and Coordinate Position from Smartphone-Recorded Infrasound Data

Science.gov (United States)

Garces, E. L.; Garces, M. A.; Christe, A.

2017-12-01

The RedVox infrasound recorder app uses microphones and barometers in smartphones to record infrasound, low-frequency sound below the threshold of human hearing. We study a device's metadata, which includes position, latency time, the differences between the device's internal times and the server times, and the machine time, searching for patterns and possible errors or discontinuities in these scaled parameters. We highlight metadata variability through scaled multivariate displays (histograms, distribution curves, scatter plots), all created and organized through software development in Python. This project is helpful in ascertaining variability and honing the accuracy of smartphones, aiding the emergence of portable devices as viable geophysical data collection instruments. It can also improve the app and cloud service by increasing efficiency and accuracy, allowing to better document and foresee drastic natural movements like tsunamis, earthquakes, volcanic eruptions, storms, rocket launches, and meteor impacts; recorded data can later be used for studies and analysis by a variety of professions. We expect our final results to produce insight on how to counteract problematic issues in data mining and improve accuracy in smartphone data-collection. By eliminating lurking variables and minimizing the effect of confounding variables, we hope to discover efficient processes to reduce superfluous precision, unnecessary errors, and data artifacts. These methods should conceivably be transferable to other areas of software development, data analytics, and statistics-based experiments, contributing a precedent of smartphone metadata studies from geophysical rather than societal data. The results should facilitate the rise of civilian-accessible, hand-held, data-gathering mobile sensor networks and yield more straightforward data mining techniques.

Variables in full-body ultraviolet B treatment of skin diseases

DEFF Research Database (Denmark)

Wulf, Hans Christian; Heydenreich, Jakob; Philipsen, Peter A

2010-01-01

Ultraviolet B (UVB) treatment is most often performed according to a fixed schedule, not necessarily considering important variables such as UV intensity, type of UVB source and skin pigmentation. These variables can rather easily be taken into consideration by the right choice of dosing unit...... burning....

Variability in Labrador Sea Water formation

NARCIS (Netherlands)

Gelderloos, R.

2012-01-01

The Atlantic Meridional Overturning Circulation (AMOC) transports of a large amount of heat towards the North Atlantic region. Since this circulation is considered to have shown pronounced variability in the past, and a weakening is projected for the 21st century, it is very important to understand

Controlling for unmeasured confounding and spatial misalignment in long-term air pollution and health studies.

Science.gov (United States)

Lee, Duncan; Sarran, Christophe

2015-11-01

The health impact of long-term exposure to air pollution is now routinely estimated using spatial ecological studies, owing to the recent widespread availability of spatial referenced pollution and disease data. However, this areal unit study design presents a number of statistical challenges, which if ignored have the potential to bias the estimated pollution-health relationship. One such challenge is how to control for the spatial autocorrelation present in the data after accounting for the known covariates, which is caused by unmeasured confounding. A second challenge is how to adjust the functional form of the model to account for the spatial misalignment between the pollution and disease data, which causes within-area variation in the pollution data. These challenges have largely been ignored in existing long-term spatial air pollution and health studies, so here we propose a novel Bayesian hierarchical model that addresses both challenges and provide software to allow others to apply our model to their own data. The effectiveness of the proposed model is compared by simulation against a number of state-of-the-art alternatives proposed in the literature and is then used to estimate the impact of nitrogen dioxide and particulate matter concentrations on respiratory hospital admissions in a new epidemiological study in England in 2010 at the local authority level. © 2015 The Authors. Environmetrics published by John Wiley & Sons Ltd.

Do digestive contents confound body mass as a measure of relative condition in nestling songbirds?

Science.gov (United States)

Streby, Henry M.; Peterson, Sean M.; Lehman, Justin A.; Kramer, Gunnar R.; Vernasco, Ben J.; Andersen, David E.

2014-01-01

Relative nestling condition, typically measured as nestling mass or as an index including nestling mass, is commonly purported to correlate with fledgling songbird survival. However, most studies directly investigating fledgling survival have found no such relationship. We weighed feces and stomach contents of nestling golden-winged warblers (Vermivora chrysoptera) to investigate the potential contribution of variation in digestive contents to differences in nestling mass. We estimated that the mass of a seventh-day (near fledging) nestling golden-winged warbler varies by 0.65 g (approx. 9% of mean nestling mass) depending on the contents of the nestling's digestive system at the time of weighing, and that digestive contents are dissimilar among nestlings at any moment the brood is removed from the nest for weighing. Our conservative estimate of within-individual variation in digestive contents equals 72% and 24% of the mean within-brood and population-wide range in nestling mass, respectively. Based on our results, a substantive but typically unknown amount of the variation in body mass among nestlings is confounded by differences in digestive contents. We conclude that short-term variation in digestive contents likely precludes the use of body mass, and therefore any mass-dependent index, as a measure of relative nestling condition or as a predictor of survival in golden-winged warblers and likely in many other songbirds of similar size.

Bayesian Multiresolution Variable Selection for Ultra-High Dimensional Neuroimaging Data.

Science.gov (United States)

Zhao, Yize; Kang, Jian; Long, Qi

2018-01-01

Ultra-high dimensional variable selection has become increasingly important in analysis of neuroimaging data. For example, in the Autism Brain Imaging Data Exchange (ABIDE) study, neuroscientists are interested in identifying important biomarkers for early detection of the autism spectrum disorder (ASD) using high resolution brain images that include hundreds of thousands voxels. However, most existing methods are not feasible for solving this problem due to their extensive computational costs. In this work, we propose a novel multiresolution variable selection procedure under a Bayesian probit regression framework. It recursively uses posterior samples for coarser-scale variable selection to guide the posterior inference on finer-scale variable selection, leading to very efficient Markov chain Monte Carlo (MCMC) algorithms. The proposed algorithms are computationally feasible for ultra-high dimensional data. Also, our model incorporates two levels of structural information into variable selection using Ising priors: the spatial dependence between voxels and the functional connectivity between anatomical brain regions. Applied to the resting state functional magnetic resonance imaging (R-fMRI) data in the ABIDE study, our methods identify voxel-level imaging biomarkers highly predictive of the ASD, which are biologically meaningful and interpretable. Extensive simulations also show that our methods achieve better performance in variable selection compared to existing methods.

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

Science.gov (United States)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall

Scalable conditional induction variables (CIV) analysis

DEFF Research Database (Denmark)

Oancea, Cosmin Eugen; Rauchwerger, Lawrence

2015-01-01

parallelizing compiler and evaluated its impact on five Fortran benchmarks. We have found that that there are many important loops using CIV subscripts and that our analysis can lead to their scalable parallelization. This in turn has led to the parallelization of the benchmark programs they appear in.......Subscripts using induction variables that cannot be expressed as a formula in terms of the enclosing-loop indices appear in the low-level implementation of common programming abstractions such as filter, or stack operations and pose significant challenges to automatic parallelization. Because...... the complexity of such induction variables is often due to their conditional evaluation across the iteration space of loops we name them Conditional Induction Variables (CIV). This paper presents a flow-sensitive technique that summarizes both such CIV-based and affine subscripts to program level, using the same...

The Bayesian group lasso for confounded spatial data

Science.gov (United States)

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.

2017-01-01

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

Developing a spatial-statistical model and map of historical malaria prevalence in Botswana using a staged variable selection procedure

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Mabaso Musawenkosi LH

2007-09-01

Full Text Available Abstract Background Several malaria risk maps have been developed in recent years, many from the prevalence of infection data collated by the MARA (Mapping Malaria Risk in Africa project, and using various environmental data sets as predictors. Variable selection is a major obstacle due to analytical problems caused by over-fitting, confounding and non-independence in the data. Testing and comparing every combination of explanatory variables in a Bayesian spatial framework remains unfeasible for most researchers. The aim of this study was to develop a malaria risk map using a systematic and practicable variable selection process for spatial analysis and mapping of historical malaria risk in Botswana. Results Of 50 potential explanatory variables from eight environmental data themes, 42 were significantly associated with malaria prevalence in univariate logistic regression and were ranked by the Akaike Information Criterion. Those correlated with higher-ranking relatives of the same environmental theme, were temporarily excluded. The remaining 14 candidates were ranked by selection frequency after running automated step-wise selection procedures on 1000 bootstrap samples drawn from the data. A non-spatial multiple-variable model was developed through step-wise inclusion in order of selection frequency. Previously excluded variables were then re-evaluated for inclusion, using further step-wise bootstrap procedures, resulting in the exclusion of another variable. Finally a Bayesian geo-statistical model using Markov Chain Monte Carlo simulation was fitted to the data, resulting in a final model of three predictor variables, namely summer rainfall, mean annual temperature and altitude. Each was independently and significantly associated with malaria prevalence after allowing for spatial correlation. This model was used to predict malaria prevalence at unobserved locations, producing a smooth risk map for the whole country. Conclusion We have

Lumbar disc degeneration was not related to spine and hip bone mineral densities in Chinese: facet joint osteoarthritis may confound the association.

Science.gov (United States)

Pan, Jianjiang; Lu, Xuan; Yang, Ge; Han, Yongmei; Tong, Xiang; Wang, Yue

2017-12-01

A sample of 512 Chinese was studied and we observed that greater disc degeneration on MRI was associated with greater spine DXA BMD. Yet, this association may be confounded by facet joint osteoarthritis. BMD may not be a risk factor for lumbar disc degeneration in Chinese. Evidence suggested that lumbar vertebral bone and intervertebral disc interact with each other in multiple ways. The current paper aims to determine the association between bone mineral density (BMD) and lumbar disc degeneration using a sample of Chinese. We studied 165 patients with back disorders and 347 general subjects from China. All subjects had lumbar spine magnetic resonance (MR) imaging and dual- energy X-ray absorptiometry (DXA) spine BMD studies, and a subset of general subjects had additional hip BMD measurements. On T2-weighted MR images, Pfirrmann score was used to evaluate the degree of lumbar disc degeneration and facet joint osteoarthritis was assessed as none, slight-moderate, and severe. Regression analyses were used to examine the associations between lumbar and hip BMD and disc degeneration, adjusting for age, gender, body mass index (BMI), lumbar region, and facet joint osteoarthritis. Greater facet joint osteoarthritis was associated with greater spine BMD (P osteoarthritis entered the regression model, however, greater spine BMD was associated with greater facet joint osteoarthritis (P  0.05). No statistical association was observed between spine BMD and lumbar disc degeneration in patients with back disorders (P > 0.05), and between hip BMD and disc degeneration in general subjects (P > 0.05). BMD may not be a risk factor for lumbar disc degeneration in Chinese. Facet joint osteoarthritis inflates DXA spine BMD measurements and therefore, may confound the association between spine BMD and disc degeneration.

Psychosocial variables of sexual satisfaction in Chile.

Science.gov (United States)

Barrientos, Jaime E; Páez, Dario

2006-01-01

This study analyzed psychosocial variables of sexual satisfaction in Chile using data from the COSECON survey. Participants were 5,407 subjects (2,244 min and 3,163 women, aged 18-69 years). We used a cross-sectional questionnaire with a national probability sample. Data were collected using a thorough sexual behavior questionnaire consisting of 190 face-to-face questions and 24 self-reported questions. A single item included in the COSECON questionnaire assessed sexual satisfaction. Results showed that high education level, marital status, and high socioeconomic levels were associated with sexual satisfaction in women but not in men. The results also showed important gender differences and sustain the idea that sexuality changes may be more present in middle and high social classes. The proximal variables typically used for measuring sexual satisfaction, such as the frequency of sexual intercourse and orgasm, showed a positive but smaller association with sexual satisfaction. Other important variables related to sexual satisfaction were being in love with the partner and having a steady partner. The results confirmed previous findings and are discussed in the frame of approaches like the exchange, equity, and sexual scripts theories.

Thermal barriers constrain microbial elevational range size via climate variability.

Science.gov (United States)

Wang, Jianjun; Soininen, Janne

2017-08-01

Range size is invariably limited and understanding range size variation is an important objective in ecology. However, microbial range size across geographical gradients remains understudied, especially on mountainsides. Here, the patterns of range size of stream microbes (i.e., bacteria and diatoms) and macroorganisms (i.e., macroinvertebrates) along elevational gradients in Asia and Europe were examined. In bacteria, elevational range size showed non-significant phylogenetic signals. In all taxa, there was a positive relationship between niche breadth and species elevational range size, driven by local environmental and climatic variables. No taxa followed the elevational Rapoport's rule. Climate variability explained the most variation in microbial mean elevational range size, whereas local environmental variables were more important for macroinvertebrates. Seasonal and annual climate variation showed negative effects, while daily climate variation had positive effects on community mean elevational range size for all taxa. The negative correlation between range size and species richness suggests that understanding the drivers of range is key for revealing the processes underlying diversity. The results advance the understanding of microbial species thermal barriers by revealing the importance of seasonal and diurnal climate variation, and highlight that aquatic and terrestrial biota may differ in their response to short- and long-term climate variability. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

[Economic determinants of the demand for importation of pharmacochemical and pharmaceutical products].

Science.gov (United States)

Santos, Anderson Moreira Aristides Dos; Tejada, César Augusto Oviedo; Jacinto, Paulo de Andrade

2017-09-28

: This article analyzes the relationship between the demand for importation of pharmacochemical and pharmaceutical products and economic variables (exchange rate, import prices, and aggregate income) in Brazil, using monthly data from 1997-2014. The main results showed that increases in aggregate income and price reductions in imports have a positive and significant impact (elastic and inelastic, respectively) on imports. Exchange rate was only significant in the more aggregate model. Thus, aggregate income was a robust variable with strong impact on the importation of pharmacochemical and pharmaceutical products. The arguments in the literature that this industry's international trade deficit is related to a deficit in knowledge and technology and the current study's results provide evidence that as economic activity grows, there is a greater demand for this type of product. Additionally, if domestic production is insufficient, there is a need for imports, which can generate pressure on the trade deficit in the industry and contribute to Brazil's dependence on other countries.

Overlap between autistic and schizotypal personality traits is not accounted for by anxiety and depression.

Science.gov (United States)

Mealey, Alex; Abbott, Gavin; Byrne, Linda K; McGillivray, Jane

2014-10-30

Autism spectrum and schizophrenia spectrum disorders are classified separately in the DSM-5, yet research indicates that these two disorders share overlapping features. The aim of the present study was to examine the overlap between autistic and schizotypal personality traits and whether anxiety and depression act as confounding variables in this relationship within a non-clinical population. One hundred and forty-four adults completed the Autism Spectrum Quotient and the Schizotypal Personality Questionnaire and the Depression Anxiety Stress Scales-21. A number of associations were seen between autistic and schizotypal personality traits. However, negative traits were the only schizotypal feature to uniquely predict global autistic traits, thus highlighting the importance of interpersonal qualities in the overlap of autistic and schizotypal characteristics. The inclusion of anxiety and depression did not alter relationships between autistic and schizotypal traits, indicating that anxiety and depression are not confounders of this relationship. These findings have important implications for the conceptualisation of both disorders. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Travel time variability and airport accessibility

NARCIS (Netherlands)

Koster, P.R.; Kroes, E.P.; Verhoef, E.T.

2011-01-01

We analyze the cost of access travel time variability for air travelers. Reliable access to airports is important since the cost of missing a flight is likely to be high. First, the determinants of the preferred arrival times at airports are analyzed. Second, the willingness to pay (WTP) for

Genetic Influence on Slope Variability in a Childhood Reflexive Attention Task.

Directory of Open Access Journals (Sweden)

Rebecca A Lundwall

Full Text Available Individuals are not perfectly consistent, and interindividual variability is a common feature in all varieties of human behavior. Some individuals respond more variably than others, however, and this difference may be important to understanding how the brain works. In this paper, we explore genetic contributions to response time (RT slope variability on a reflexive attention task. We are interested in such variability because we believe it is an important part of the overall picture of attention that, if understood, has the potential to improve intervention for those with attentional deficits. Genetic association studies are valuable in discovering biological pathways of variability and several studies have found such associations with a sustained attention task. Here, we expand our knowledge to include a reflexive attention task. We ask whether specific candidate genes are associated with interindividual variability on a childhood reflexive attention task in 9-16 year olds. The genetic makers considered are on 11 genes: APOE, BDNF, CHRNA4, COMT, DRD4, HTR4, IGF2, MAOA, SLC5A7, SLC6A3, and SNAP25. We find significant associations with variability with markers on nine and we discuss the results in terms of neurotransmitters associated with each gene and the characteristics of the associated measures from the reflexive attention task.

Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa

Directory of Open Access Journals (Sweden)

Thandi Kapwata

2016-11-01

Full Text Available Malaria is an environmentally driven disease. In order to quantify the spatial variability of malaria transmission, it is imperative to understand the interactions between environmental variables and malaria epidemiology at a micro-geographic level using a novel statistical approach. The random forest (RF statistical learning method, a relatively new variable-importance ranking method, measures the variable importance of potentially influential parameters through the percent increase of the mean squared error. As this value increases, so does the relative importance of the associated variable. The principal aim of this study was to create predictive malaria maps generated using the selected variables based on the RF algorithm in the Ehlanzeni District of Mpumalanga Province, South Africa. From the seven environmental variables used [temperature, lag temperature, rainfall, lag rainfall, humidity, altitude, and the normalized difference vegetation index (NDVI], altitude was identified as the most influential predictor variable due its high selection frequency. It was selected as the top predictor for 4 out of 12 months of the year, followed by NDVI, temperature and lag rainfall, which were each selected twice. The combination of climatic variables that produced the highest prediction accuracy was altitude, NDVI, and temperature. This suggests that these three variables have high predictive capabilities in relation to malaria transmission. Furthermore, it is anticipated that the predictive maps generated from predictions made by the RF algorithm could be used to monitor the progression of malaria and assist in intervention and prevention efforts with respect to malaria.

Variability Bugs:

DEFF Research Database (Denmark)

Melo, Jean

. Although many researchers suggest that preprocessor-based variability amplifies maintenance problems, there is little to no hard evidence on how actually variability affects programs and programmers. Specifically, how does variability affect programmers during maintenance tasks (bug finding in particular......)? How much harder is it to debug a program as variability increases? How do developers debug programs with variability? In what ways does variability affect bugs? In this Ph.D. thesis, I set off to address such issues through different perspectives using empirical research (based on controlled...... experiments) in order to understand quantitatively and qualitatively the impact of variability on programmers at bug finding and on buggy programs. From the program (and bug) perspective, the results show that variability is ubiquitous. There appears to be no specific nature of variability bugs that could...

Climate variability from isotope records in precipitation

International Nuclear Information System (INIS)

Grassl, H.; Latif, M.; Schotterer, U.; Gourcy, L.

2002-01-01

Selected time series from the Global Network for Isotopes in Precipitation (GNIP) revealed a close relationship to climate variability phenomena like El Nino - Southern Oscillation (ENSO) or the North Atlantic Oscillation (NAO) although the precipitation anomaly in the case studies of Manaus (Brazil) and Groningen (The Netherlands) is rather weak. For a sound understanding of this relationship especially in the case of Manaus, the data should include major events like the 1997/98 El Nino, however, the time series are interrupted frequently or important stations are even closed. Improvements are only possible if existing key stations and new ones (placed at 'hot spots' derived from model experiments) are supported continuously. A close link of GNIP to important scientific programmes like CLIVAR, the Climate Variability and Predictability Programme seems to be indispensable for a successful continuation. (author)

Marked EEG worsening following Levetiracetam overdose: How a pharmacological issue can confound coma prognosis.

Science.gov (United States)

Bouchier, Baptiste; Demarquay, Geneviève; Guérin, Claude; André-Obadia, Nathalie; Gobert, Florent

2017-01-01

Levetiracetam is an anti-epileptic drug commonly used in intensive care when seizure is suspected as a possible cause of coma. We propose to question the cofounding effect of Levetiracetam during the prognostication process in a case of anoxic coma. We report the story of a young woman presenting a comatose state following a hypoxic cardiac arrest. After a first EEG presenting an intermediate EEG pattern, a seizure suspicion led to prescribe Levetiracetam. The EEG showed then the appearance of burst suppression, which was compatible with a very severe pattern of post-anoxic coma. This aggravation was in fact related to an overdose of Levetiracetam (the only medication introduced recently) and was reversible after Levetiracetam cessation. The increased plasmatic dosages of Levetiracetam confirming this overdose could have been favoured by a moderate reduction of renal clearance, previously underestimated because of a low body-weight. This EEG dynamic was unexpected under Levetiracetam and could sign a functional instability after anoxia. Burst suppression is classically observed with high doses of anaesthetics, but is not expected after a minor anti-epileptic drug. This report proposes that Levetiracetam tolerance might not be straightforward after brain lesions and engages us to avoid confounding factors during the awakening prognostication, which is mainly based on the severity of the EEG. Hence, prognosis should not be decided on an isolated parameter, especially if the dynamic is atypical after a new prescription, even for well-known drugs. For any suspicion, the drug's dosage and replacement should be managed before any premature care's withdrawal. Copyright © 2016 Elsevier B.V. All rights reserved.

The associations between serum brain-derived neurotrophic factor, potential confounders, and cognitive decline: a longitudinal study.

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Jasmine Nettiksimmons

Full Text Available Brain-derived neurotrophic factor (BDNF plays a role in the maintenance and function of neurons. Although persons with Alzheimer's disease have lower cortical levels of BDNF, evidence regarding the association between circulating BDNF and cognitive function is conflicting. We sought to determine the correlates of BDNF level and whether BDNF level was prospectively associated with cognitive decline in healthy older adults. We measured serum BDNF near baseline in 912 individuals. Cognitive status was assessed repeatedly with the modified Mini-Mental Status Examination and the Digit Symbol Substitution test over the next 10 years. We evaluated the association between BDNF and cognitive decline with longitudinal models. We also assessed the association between BDNF level and demographics, comorbidities and health behaviors. We found an association between serum BDNF and several characteristics that are also associated with dementia (race and depression, suggesting that future studies should control for these potential confounders. We did not find evidence of a longitudinal association between serum BDNF and subsequent cognitive test trajectories in older adults, although we did identify a potential trend toward a cross-sectional association. Our results suggest that serum BDNF may have limited utility as a biomarker of prospective cognitive decline.

The importance of personality and parental styles on optimism in adolescents.

Science.gov (United States)

Zanon, Cristian; Bastianello, Micheline Roat; Pacico, Juliana Cerentini; Hutz, Claudio Simon

2014-01-01

Some studies have suggested that personality factors are important to optimism development. Others have emphasized that family relations are relevant variables to optimism. This study aimed to evaluate the importance of parenting styles to optimism controlling for the variance accounted for by personality factors. Participants were 344 Brazilian high school students (44% male) with mean age of 16.2 years (SD = 1) who answered personality, optimism, responsiveness and demandingness scales. Hierarchical regression analyses were conducted having personality factors (in the first step) and maternal and paternal parenting styles, and demandingness and responsiveness (in the second step) as predictive variables and optimism as the criterion. Personality factors, especially neuroticism (β = -.34, p parental styles (1%). These findings suggest that personality is more important to optimism development than parental styles.

A Non-Gaussian Spatial Generalized Linear Latent Variable Model

KAUST Repository

Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.

2012-01-01

We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

A Non-Gaussian Spatial Generalized Linear Latent Variable Model

KAUST Repository

Irincheeva, Irina

2012-08-03

We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

Risk assessment of groundwater level variability using variable Kriging methods

Science.gov (United States)

Spanoudaki, Katerina; Kampanis, Nikolaos A.

2015-04-01

Assessment of the water table level spatial variability in aquifers provides useful information regarding optimal groundwater management. This information becomes more important in basins where the water table level has fallen significantly. The spatial variability of the water table level in this work is estimated based on hydraulic head measured during the wet period of the hydrological year 2007-2008, in a sparsely monitored basin in Crete, Greece, which is of high socioeconomic and agricultural interest. Three Kriging-based methodologies are elaborated in Matlab environment to estimate the spatial variability of the water table level in the basin. The first methodology is based on the Ordinary Kriging approach, the second involves auxiliary information from a Digital Elevation Model in terms of Residual Kriging and the third methodology calculates the probability of the groundwater level to fall below a predefined minimum value that could cause significant problems in groundwater resources availability, by means of Indicator Kriging. The Box-Cox methodology is applied to normalize both the data and the residuals for improved prediction results. In addition, various classical variogram models are applied to determine the spatial dependence of the measurements. The Matérn model proves to be the optimal, which in combination with Kriging methodologies provides the most accurate cross validation estimations. Groundwater level and probability maps are constructed to examine the spatial variability of the groundwater level in the basin and the associated risk that certain locations exhibit regarding a predefined minimum value that has been set for the sustainability of the basin's groundwater resources. Acknowledgement The work presented in this paper has been funded by the Greek State Scholarships Foundation (IKY), Fellowships of Excellence for Postdoctoral Studies (Siemens Program), 'A simulation-optimization model for assessing the best practices for the

THE CHANDRA VARIABLE GUIDE STAR CATALOG

International Nuclear Information System (INIS)

Nichols, Joy S.; Lauer, Jennifer L.; Morgan, Douglas L.; Sundheim, Beth A.; Henden, Arne A.; Huenemoerder, David P.; Martin, Eric

2010-01-01

Variable stars have been identified among the optical-wavelength light curves of guide stars used for pointing control of the Chandra X-ray Observatory. We present a catalog of these variable stars along with their light curves and ancillary data. Variability was detected to a lower limit of 0.02 mag amplitude in the 4000-10000 A range using the photometrically stable Aspect Camera on board the Chandra spacecraft. The Chandra Variable Guide Star Catalog (VGUIDE) contains 827 stars, of which 586 are classified as definitely variable and 241 are identified as possibly variable. Of the 586 definite variable stars, we believe 319 are new variable star identifications. Types of variables in the catalog include eclipsing binaries, pulsating stars, and rotating stars. The variability was detected during the course of normal verification of each Chandra pointing and results from analysis of over 75,000 guide star light curves from the Chandra mission. The VGUIDE catalog represents data from only about 9 years of the Chandra mission. Future releases of VGUIDE will include newly identified variable guide stars as the mission proceeds. An important advantage of the use of space data to identify and analyze variable stars is the relatively long observations that are available. The Chandra orbit allows for observations up to 2 days in length. Also, guide stars were often used multiple times for Chandra observations, so many of the stars in the VGUIDE catalog have multiple light curves available from various times in the mission. The catalog is presented as both online data associated with this paper and as a public Web interface. Light curves with data at the instrumental time resolution of about 2 s, overplotted with the data binned at 1 ks, can be viewed on the public Web interface and downloaded for further analysis. VGUIDE is a unique project using data collected during the mission that would otherwise be ignored. The stars available for use as Chandra guide stars are

Chaos resulting from nonlinear relations between different variables

International Nuclear Information System (INIS)

Dohtani, Akitaka

2011-01-01

Research highlights: → We prove a general result on the existence of chaos. → We focus on the cyclic composites of interdependent relations between different variables. → By considering several examples, we conclude that the cyclic composites play an important role in detecting chaotic dynamics. - Abstract: In this study, we further develop the perturbation method of Marotto and investigate the general mechanisms responsible for nonlinear dynamics, which are typical of multidimensional systems. We focus on the composites of interdependent relations between different variables. First, we prove a general result on chaos, which shows that the cyclic composites of nonlinear interdependent relations are sources of chaotic dynamics in multidimensional systems. By considering several examples, we conclude that the cyclic composites play an important role in detecting chaotic dynamics.

Age at immigration and crime in Stockholm using sibling comparisons.

Science.gov (United States)

Beckley, Amber L

2015-09-01

Past Swedish research has shown that immigrants arriving in the receiving country at an older age are less likely to commit crime than immigrants arriving at a younger age. Segmented assimilation theory argues that the family and neighborhood may be important factors affecting how age at immigration and crime are related to one another. This study used population-based register data on foreign-background males from Stockholm to test the effect of age at immigration on crime. Potential confounding from the family and neighborhood was addressed using variables and modeling strategies. Initial results, using variables to control for confounding, showed that people who immigrated around age 4 were the most likely to be suspected of a crime. When controlling for unmeasured family characteristics, it seemed that a later age at immigration was tied to a lower likelihood of crime, which does not corroborate past research findings. The effect of age at immigration, however, was not statistically significant. The results imply that future research on entire families may be a worthwhile endeavor. Copyright © 2015 Elsevier Inc. All rights reserved.

Time variability of C-reactive protein: implications for clinical risk stratification.

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Peter Bogaty

Full Text Available C-reactive protein (CRP is proposed as a screening test for predicting risk and guiding preventive approaches in coronary artery disease (CAD. However, the stability of repeated CRP measurements over time in subjects with and without CAD is not well defined. We sought to determine the stability of serial CRP measurements in stable subjects with distinct CAD manifestations and a group without CAD while carefully controlling for known confounders.We prospectively studied 4 groups of 25 stable subjects each 1 a history of recurrent acute coronary events; 2 a single myocardial infarction ≥7 years ago; 3 longstanding CAD (≥7 years that had never been unstable; 4 no CAD. Fifteen measurements of CRP were obtained to cover 21 time-points: 3 times during one day; 5 consecutive days; 4 consecutive weeks; 4 consecutive months; and every 3 months over the year. CRP risk threshold was set at 2.0 mg/L. We estimated variance across time-points using standard descriptive statistics and Bayesian hierarchical models.Median CRP values of the 4 groups and their pattern of variability did not differ substantially so all subjects were analyzed together. The median individual standard deviation (SD CRP values within-day, within-week, between-weeks and between-months were 0.07, 0.19, 0.36 and 0.63 mg/L, respectively. Forty-six percent of subjects changed CRP risk category at least once and 21% had ≥4 weekly and monthly CRP values in both low and high-risk categories.Considering its large intra-individual variability, it may be problematic to rely on CRP values for CAD risk prediction and therapeutic decision-making in individual subjects.

Does social trust increase willingness to pay taxes to improve public healthcare? Cross-sectional cross-country instrumental variable analysis.

Science.gov (United States)

Habibov, Nazim; Cheung, Alex; Auchynnikava, Alena

2017-09-01

The purpose of this paper is to investigate the effect of social trust on the willingness to pay more taxes to improve public healthcare in post-communist countries. The well-documented association between higher levels of social trust and better health has traditionally been assumed to reflect the notion that social trust is positively associated with support for public healthcare system through its encouragement of cooperative behaviour, social cohesion, social solidarity, and collective action. Hence, in this paper, we have explicitly tested the notion that social trust contributes to an increase in willingness to financially support public healthcare. We use micro data from the 2010 Life-in-Transition survey (N = 29,526). Classic binomial probit and instrumental variables ivprobit regressions are estimated to model the relationship between social trust and paying more taxes to improve public healthcare. We found that an increase in social trust is associated with a greater willingness to pay more taxes to improve public healthcare. From the perspective of policy-making, healthcare administrators, policy-makers, and international donors should be aware that social trust is an important factor in determining the willingness of the population to provide much-needed financial resources to supporting public healthcare. From a theoretical perspective, we found that estimating the effect of trust on support for healthcare without taking confounding and measurement error problems into consideration will likely lead to an underestimation of the true effect of trust. Copyright © 2017 Elsevier Ltd. All rights reserved.

Acclimatization of the crustose coralline alga Porolithon onkodes to variable pCO₂.

Science.gov (United States)

Johnson, Maggie D; Moriarty, Vincent W; Carpenter, Robert C

2014-01-01

Ocean acidification (OA) has important implications for the persistence of coral reef ecosystems, due to potentially negative effects on biomineralization. Many coral reefs are dynamic with respect to carbonate chemistry, and experience fluctuations in pCO₂ that exceed OA projections for the near future. To understand the influence of dynamic pCO₂ on an important reef calcifier, we tested the response of the crustose coralline alga Porolithon onkodes to oscillating pCO₂. Individuals were exposed to ambient (400 µatm), high (660 µatm), or variable pCO₂ (oscillating between 400/660 µatm) treatments for 14 days. To explore the potential for coralline acclimatization, we collected individuals from low and high pCO₂ variability sites (upstream and downstream respectively) on a back reef characterized by unidirectional water flow in Moorea, French Polynesia. We quantified the effects of treatment on algal calcification by measuring the change in buoyant weight, and on algal metabolism by conducting sealed incubations to measure rates of photosynthesis and respiration. Net photosynthesis was higher in the ambient treatment than the variable treatment, regardless of habitat origin, and there was no effect on respiration or gross photosynthesis. Exposure to high pCO₂ decreased P. onkodes calcification by >70%, regardless of the original habitat. In the variable treatment, corallines from the high variability habitat calcified 42% more than corallines from the low variability habitat. The significance of the original habitat for the coralline calcification response to variable, high pCO₂ indicates that individuals existing in dynamic pCO₂ habitats may be acclimatized to OA within the scope of in situ variability. These results highlight the importance of accounting for natural pCO₂ variability in OA manipulations, and provide insight into the potential for plasticity in habitat and species-specific responses to changing ocean chemistry.

Acclimatization of the crustose coralline alga Porolithon onkodes to variable pCO₂.

Directory of Open Access Journals (Sweden)

Maggie D Johnson

Full Text Available Ocean acidification (OA has important implications for the persistence of coral reef ecosystems, due to potentially negative effects on biomineralization. Many coral reefs are dynamic with respect to carbonate chemistry, and experience fluctuations in pCO₂ that exceed OA projections for the near future. To understand the influence of dynamic pCO₂ on an important reef calcifier, we tested the response of the crustose coralline alga Porolithon onkodes to oscillating pCO₂. Individuals were exposed to ambient (400 µatm, high (660 µatm, or variable pCO₂ (oscillating between 400/660 µatm treatments for 14 days. To explore the potential for coralline acclimatization, we collected individuals from low and high pCO₂ variability sites (upstream and downstream respectively on a back reef characterized by unidirectional water flow in Moorea, French Polynesia. We quantified the effects of treatment on algal calcification by measuring the change in buoyant weight, and on algal metabolism by conducting sealed incubations to measure rates of photosynthesis and respiration. Net photosynthesis was higher in the ambient treatment than the variable treatment, regardless of habitat origin, and there was no effect on respiration or gross photosynthesis. Exposure to high pCO₂ decreased P. onkodes calcification by >70%, regardless of the original habitat. In the variable treatment, corallines from the high variability habitat calcified 42% more than corallines from the low variability habitat. The significance of the original habitat for the coralline calcification response to variable, high pCO₂ indicates that individuals existing in dynamic pCO₂ habitats may be acclimatized to OA within the scope of in situ variability. These results highlight the importance of accounting for natural pCO₂ variability in OA manipulations, and provide insight into the potential for plasticity in habitat and species-specific responses to changing ocean chemistry.

Lectures on counterexamples in several complex variables

CERN Document Server

Fornæss, John Erik

2007-01-01

Counterexamples are remarkably effective for understanding the meaning, and the limitations, of mathematical results. Fornæss and Stensønes look at some of the major ideas of several complex variables by considering counterexamples to what might seem like reasonable variations or generalizations. The first part of the book reviews some of the basics of the theory, in a self-contained introduction to several complex variables. The counterexamples cover a variety of important topics: the Levi problem, plurisubharmonic functions, Monge-Ampère equations, CR geometry, function theory, and the \\bar\\

Gaussian Mixture Model of Heart Rate Variability

Science.gov (United States)

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

Important Characteristics in an MBA Program: The Perceptions of Online MBA Students

Science.gov (United States)

Rydzewski, Danielle N.; Eastman, Jacqueline K.; Bocchi, Joseph

2010-01-01

This study examines characteristics important to online MBA students and alumni. The study looks at what characteristics are important in an online MBA Program and if the level of importance of these characteristics varies by demographic variables. The study focuses on availability, program quality, program length, cost, and courses in the…

Climatology and variability in the ECHO coupled GCM

International Nuclear Information System (INIS)

Latif, M.; Stockdale, T.; Wolff, J.; Burgers, G.; Maier-Reimer, E.; Junge, M.M.; Arpe, K.; Bengtsson, L.

1993-01-01

ECHO is a new global coupled ocean-atmosphere general circulation model (GCM), consisting of the Hamburg version of the European Centre atmospheric GCM (ECHAM) and the Hamburg Primitive Equation ocean GCM (HOPE). We performed a twenty year integration with ECHO. Climate drift is significant, but typical in the open oceans. Near the boundaries, however, SST errors are considerably larger. The coupled model simulates an irregular ENSO cycle in the tropical Pacific, with spatial patterns similar to those observed. The mechanism behind the model ENSO is related to the subsurface memory of the system, but stochastic forcing by the atmosphere seems to be also important. The variability, however, is somewhat weaker relative to observations. ECHO also simulates significant interannual variability in midlatitudes. Consistent with observations, variability over the North Pacific can be partly attributed to remote forcing from the tropics. In contract, the interannual variability over the North Atlantic appears to be generated locally. Indications for decadal-scale variability are also found over the North Atlantic. (orig.)

Protein construct storage: Bayesian variable selection and prediction with mixtures.

Science.gov (United States)

Clyde, M A; Parmigiani, G

1998-07-01

Determining optimal conditions for protein storage while maintaining a high level of protein activity is an important question in pharmaceutical research. A designed experiment based on a space-filling design was conducted to understand the effects of factors affecting protein storage and to establish optimal storage conditions. Different model-selection strategies to identify important factors may lead to very different answers about optimal conditions. Uncertainty about which factors are important, or model uncertainty, can be a critical issue in decision-making. We use Bayesian variable selection methods for linear models to identify important variables in the protein storage data, while accounting for model uncertainty. We also use the Bayesian framework to build predictions based on a large family of models, rather than an individual model, and to evaluate the probability that certain candidate storage conditions are optimal.

The importance of distance to resources in the spatial modelling of bat foraging habitat.

Directory of Open Access Journals (Sweden)

Ana Rainho

Full Text Available Many bats are threatened by habitat loss, but opportunities to manage their habitats are now increasing. Success of management depends greatly on the capacity to determine where and how interventions should take place, so models predicting how animals use landscapes are important to plan them. Bats are quite distinctive in the way they use space for foraging because (i most are colonial central-place foragers and (ii exploit scattered and distant resources, although this increases flying costs. To evaluate how important distances to resources are in modelling foraging bat habitat suitability, we radio-tracked two cave-dwelling species of conservation concern (Rhinolophus mehelyi and Miniopterus schreibersii in a Mediterranean landscape. Habitat and distance variables were evaluated using logistic regression modelling. Distance variables greatly increased the performance of models, and distance to roost and to drinking water could alone explain 86 and 73% of the use of space by M. schreibersii and R. mehelyi, respectively. Land-cover and soil productivity also provided a significant contribution to the final models. Habitat suitability maps generated by models with and without distance variables differed substantially, confirming the shortcomings of maps generated without distance variables. Indeed, areas shown as highly suitable in maps generated without distance variables proved poorly suitable when distance variables were also considered. We concluded that distances to resources are determinant in the way bats forage across the landscape, and that using distance variables substantially improves the accuracy of suitability maps generated with spatially explicit models. Consequently, modelling with these variables is important to guide habitat management in bats and similarly mobile animals, particularly if they are central-place foragers or depend on spatially scarce resources.

Pattern classification of brain activation during emotional processing in subclinical depression: psychosis proneness as potential confounding factor

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Gemma Modinos

2013-02-01

Full Text Available We used Support Vector Machine (SVM to perform multivariate pattern classification based on brain activation during emotional processing in healthy participants with subclinical depressive symptoms. Six-hundred undergraduate students completed the Beck Depression Inventory II (BDI-II. Two groups were subsequently formed: (i subclinical (mild mood disturbance (n = 17 and (ii no mood disturbance (n = 17. Participants also completed a self-report questionnaire on subclinical psychotic symptoms, the Community Assessment of Psychic Experiences Questionnaire (CAPE positive subscale. The functional magnetic resonance imaging (fMRI paradigm entailed passive viewing of negative emotional and neutral scenes. The pattern of brain activity during emotional processing allowed correct group classification with an overall accuracy of 77% (p = 0.002, within a network of regions including the amygdala, insula, anterior cingulate cortex and medial prefrontal cortex. However, further analysis suggested that the classification accuracy could also be explained by subclinical psychotic symptom scores (correlation with SVM weights r = 0.459, p = 0.006. Psychosis proneness may thus be a confounding factor for neuroimaging studies in subclinical depression.

Uncovering noisy social signals : Using optimization methods from experimental physics to study social phenomena

NARCIS (Netherlands)

Kaptein, Maurits; Van Emden, Robin; Iannuzzi, Davide

2017-01-01

Due to the ubiquitous presence of treatment heterogeneity, measurement error, and contextual confounders, numerous social phenomena are hard to study. Precise control of treatment variables and possible confounders is often key to the success of studies in the social sciences, yet often proves out

Uncovering noisy social signals: Using optimization methods from experimental physics to study social phenomena

NARCIS (Netherlands)

Kaptein, M.C.; Emden, R. van; Iannuzzi, D.

2017-01-01

Due to the ubiquitous presence of treatment heterogeneity, measurement error, and contextual confounders, numerous social phenomena are hard to study. Precise control of treatment variables and possible confounders is often key to the success of studies in the social sciences, yet often proves out

Variable Bandwidth Analog Channel Filters for Software Defined Radio

NARCIS (Netherlands)

Arkesteijn, V.J.; Klumperink, Eric A.M.; Nauta, Bram

2001-01-01

An important aspect of Software Defined Radio is the ability to define the bandwidth of the filter that selects the desired channel. This paper first explains the importance of channel filtering. Then the advantage of analog channel filtering with a variable bandwidth in a Software Defined Radio is

Forecasting on the total volumes of Malaysia's imports and exports by multiple linear regression

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Beh, W. L.; Yong, M. K. Au

2017-04-01

This study is to give an insight on the doubt of the important of macroeconomic variables that affecting the total volumes of Malaysia's imports and exports by using multiple linear regression (MLR) analysis. The time frame for this study will be determined by using quarterly data of the total volumes of Malaysia's imports and exports covering the period between 2000-2015. The macroeconomic variables will be limited to eleven variables which are the exchange rate of US Dollar with Malaysia Ringgit (USD-MYR), exchange rate of China Yuan with Malaysia Ringgit (RMB-MYR), exchange rate of European Euro with Malaysia Ringgit (EUR-MYR), exchange rate of Singapore Dollar with Malaysia Ringgit (SGD-MYR), crude oil prices, gold prices, producer price index (PPI), interest rate, consumer price index (CPI), industrial production index (IPI) and gross domestic product (GDP). This study has applied the Johansen Co-integration test to investigate the relationship among the total volumes to Malaysia's imports and exports. The result shows that crude oil prices, RMB-MYR, EUR-MYR and IPI play important roles in the total volumes of Malaysia's imports. Meanwhile crude oil price, USD-MYR and GDP play important roles in the total volumes of Malaysia's exports.

Impact of El Niño Variability on Oceanic Phytoplankton

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Marie-Fanny Racault

2017-05-01

Full Text Available Oceanic phytoplankton respond rapidly to a complex spectrum of climate-driven perturbations, confounding attempts to isolate the principal causes of observed changes. A dominant mode of variability in the Earth-climate system is that generated by the El Niño phenomenon. Marked variations are observed in the centroid of anomalous warming in the Equatorial Pacific under El Niño, associated with quite different alterations in environmental and biological properties. Here, using observational and reanalysis datasets, we differentiate the regional physical forcing mechanisms, and compile a global atlas of associated impacts on oceanic phytoplankton caused by two extreme types of El Niño. We find robust evidence that during Eastern Pacific (EP and Central Pacific (CP types of El Niño, impacts on phytoplankton can be felt everywhere, but tend to be greatest in the tropics and subtropics, encompassing up to 67% of the total affected areas, with the remaining 33% being areas located in high-latitudes. Our analysis also highlights considerable and sometimes opposing regional effects. During EP El Niño, we estimate decreases of −56 TgC/y in the tropical eastern Pacific Ocean, and −82 TgC/y in the western Indian Ocean, and increase of +13 TgC/y in eastern Indian Ocean, whereas during CP El Niño, we estimate decreases −68 TgC/y in the tropical western Pacific Ocean and −10 TgC/y in the central Atlantic Ocean. We advocate that analysis of the dominant mechanisms forcing the biophysical under El Niño variability may provide a useful guide to improve our understanding of projected changes in the marine ecosystem in a warming climate and support development of adaptation and mitigation plans.

Oil price shocks and long run price and import demand behavior

International Nuclear Information System (INIS)

Kleibergen, F.; Van Dijk, H.K.; Urbain, J.P.

1997-01-01

The effect which the oil price time series has on the long run properties of Vector AutoRegressive (VAR) models for price levels and import demand is investigated. As the oil price variable is assumed to be weakly exogenous for the long run parameters, a cointegration testing procedure allowing for weakly exogenous variables is developed using a LU decomposition of the long run multiplier matrix. The likelihood based cointegration test statistics, Wald, Likelihood Ratio and Lagrange Multiplier, are constructed and their limiting distributions derived. Using these tests, we find that incorporating the oil price in a model for the domestic or import price level of seven industrialized countries decreases the long run memory of the inflation rate. Second, we find that the results for import demand can be classified with respect to the oil importing or exporting status of the specific country. The result for Japan is typical as its import price is not influenced by gnp in the long run, which is the case for all other countries. 31 refs

Identify the dominant variables to predict stream water temperature

Science.gov (United States)

Chien, H.; Flagler, J.

2016-12-01

Stream water temperature is a critical variable controlling water quality and the health of aquatic ecosystems. Accurate prediction of water temperature and the assessment of the impacts of environmental variables on water temperature variation are critical for water resources management, particularly in the context of water quality and aquatic ecosystem sustainability. The objective of this study is to measure stream water temperature and air temperature and to examine the importance of streamflow on stream water temperature prediction. The measured stream water temperature and air temperature will be used to test two hypotheses: 1) streamflow is a relatively more important factor than air temperature in regulating water temperature, and 2) by combining air temperature and streamflow data stream water temperature can be more accurately estimated. Water and air temperature data loggers are placed at two USGS stream gauge stations #01362357and #01362370, located in the upper Esopus Creek watershed in Phonecia, NY. The ARIMA (autoregressive integrated moving average) time series model is used to analyze the measured water temperature data, identify the dominant environmental variables, and predict the water temperature with identified dominant variable. The preliminary results show that streamflow is not a significant variable in predicting stream water temperature at both USGS gauge stations. Daily mean air temperature is sufficient to predict stream water temperature at this site scale.

Energy conservation by reducing process variability

Energy Technology Data Exchange (ETDEWEB)

Wising, Ulrika; Lafourcade, Sebastien [Pepite S.A., Liege (Belgium); Mack, Philippe [Pepite Technologies Inc., Montreal (Canada)

2011-12-21

Energy conservation is becoming an increasingly important instrument to stay competitive in today is increasingly global market. Important investments have been made in infrastructure and personnel in order to improve the management of energy such as increased metering, energy dashboards, energy managers, etc. Despite these investments, the results have not materialized and there is still a significant potential to further reduce energy consumption. In this paper a new methodology will be presented that helps industry better operate existing assets in order to reduce energy consumption, without having to make capital investments. The methodology uses a combination of advanced data analysis tools and a specific implementation scheme that has lead to significant savings in industry. The advanced data analysis tools are used to analyze the variability of the process in order to assess when the plant has been operated well or not so well in the past. By finding the root causes of these variations and the key variables that can explain them, improved operating guidelines and models can be developed and implemented. The specific implementation scheme is an important part of the methodology as it involves the people operating the plant. Several user cases will be presented showing an energy conservation of between 10%-20% without capital investments necessary. (author)

When is affect variability bad for health? The association between affect variability and immune response to the influenza vaccination.

Science.gov (United States)

Jenkins, Brooke N; Hunter, John F; Cross, Marie P; Acevedo, Amanda M; Pressman, Sarah D

2018-01-01

This study addresses methodological and theoretical questions about the association between affect and physical health. Specifically, we examine the role of affect variability and its interaction with mean levels of affect to predict antibody (Ab) levels in response to an influenza vaccination. Participants (N=83) received the vaccination and completed daily diary measures of affect four times a day for 13days. At one and four months post-vaccination, blood was collected from the participants to assess Ab levels. Findings indicate that affect variability and its interaction with mean levels of affect predict an individual's immune response. Those high in mean positive affect (PA) who had more PA variability were more likely to have a lower Ab response in comparison to those who had high mean PA and less PA variability. Although it did not interact with mean negative affect (NA), NA variability on its own was associated with Ab response, whereby those with less NA variability mounted a more robust immune response. Affect variability is related to immune response to an influenza vaccination and, in some cases, interacts with mean levels of affect. These oscillations in affective experiences are critical to consider in order to unpack the intricacies of how affect influences health. These findings suggest that future researchers should consider the important role of affect variability on physical health-relevant outcomes as well as examine the moderating effect of mean affect levels. Copyright © 2017 Elsevier Inc. All rights reserved.

High background radiation area: an important source of exploring the health effects of low dose ionizing radiation

International Nuclear Information System (INIS)

Wei Luxin

1997-01-01

Objective: For obtaining more effective data from epidemiological investigation in high background radiation areas, it is necessary to analyze the advantages, disadvantages, weak points and problems of this kind of radiation research. Methods: For epidemiological investigation of population health effects of high background radiation, the author selected high background radiation areas of Yangjiang (HBRA) and a nearby control area (CA) as an instance for analysis. The investigation included classification of dose groups, comparison of the confounding factors in the incidence of mutation related diseases, cancer mortalities and the frequencies of chromosomal aberrations between HBRA and CA. This research program has become a China-Japan cooperative research since 1991. Results: The confounding factors above-mentioned were comparable between HBRA and CA, and within the dose groups in HBRA, based on a systematic study for many years. The frequencies of chromosomal aberrations increased with the increase of cumulative dose, but not for children around or below 10 years of age. The relative risks (RR) of total and site-specific cancer mortalities for HBRA were lower or around 1.00, compared with CA. The incidence of hereditary diseases and congenital deformities in HBRA were in normal range. The results were interpreted preliminarily by the modified 'dual radiation action' theory and the 'benefit-detriment competition' hypothesis. Conclusions: The author emphasizes the necessity for continuing epidemiological research in HBRA, especially for international cooperation. He also emphasizes the importance of combination of epidemiology and radiobiology

Memory Test Performance on Analogous Verbal and Nonverbal Memory Tests in Patients with Frontotemporal Dementia and Alzheimer's Disease.

Science.gov (United States)

Baldock, Deanna; Miller, Justin B; Leger, Gabriel C; Banks, Sarah Jane

2016-01-01

Patients with frontotemporal dementia (FTD) typically have initial deficits in language or changes in personality, while the defining characteristic of Alzheimer's disease (AD) is memory impairment. Neuropsychological findings in the two diseases tend to differ, but can be confounded by verbal impairment in FTD impacting performance on memory tests in these patients. Twenty-seven patients with FTD and 102 patients with AD underwent a neuropsychological assessment before diagnosis. By utilizing analogous versions of a verbal and nonverbal memory test, we demonstrated differences in these two modalities between AD and FTD. Better differentiation between AD and FTD is found in a nonverbal memory test, possibly because it eliminates the confounding variable of language deficits found in patients with FTD. These results highlight the importance of nonverbal learning tests with multiple learning trials in diagnostic testing.

Variability in reaction time performance of younger and older adults.

Science.gov (United States)

Hultsch, David F; MacDonald, Stuart W S; Dixon, Roger A

2002-03-01

Age differences in three basic types of variability were examined: variability between persons (diversity), variability within persons across tasks (dispersion), and variability within persons across time (inconsistency). Measures of variability were based on latency performance from four measures of reaction time (RT) performed by a total of 99 younger adults (ages 17--36 years) and 763 older adults (ages 54--94 years). Results indicated that all three types of variability were greater in older compared with younger participants even when group differences in speed were statistically controlled. Quantile-quantile plots showed age and task differences in the shape of the inconsistency distributions. Measures of within-person variability (dispersion and inconsistency) were positively correlated. Individual differences in RT inconsistency correlated negatively with level of performance on measures of perceptual speed, working memory, episodic memory, and crystallized abilities. Partial set correlation analyses indicated that inconsistency predicted cognitive performance independent of level of performance. The results indicate that variability of performance is an important indicator of cognitive functioning and aging.

Noise Reduction in Arterial Spin Labeling Based Functional Connectivity Using Nuisance Variables.

Science.gov (United States)

Jann, Kay; Smith, Robert X; Rios Piedra, Edgar A; Dapretto, Mirella; Wang, Danny J J

2016-01-01

Arterial Spin Labeling (ASL) perfusion image series have recently been utilized for functional connectivity (FC) analysis in healthy volunteers and children with autism spectrum disorders (ASD). Noise reduction by using nuisance variables has been shown to be necessary to minimize potential confounding effects of head motion and physiological signals on BOLD based FC analysis. The purpose of the present study is to systematically evaluate the effectiveness of different noise reduction strategies (NRS) using nuisance variables to improve perfusion based FC analysis in two cohorts of healthy adults using state of the art 3D background-suppressed (BS) GRASE pseudo-continuous ASL (pCASL) and dual-echo 2D-EPI pCASL sequences. Five different NRS were performed in healthy volunteers to compare their performance. We then compared seed-based FC analysis using 3D BS GRASE pCASL in a cohort of 12 children with ASD (3f/9m, age 12.8 ± 1.3 years) and 13 typically developing (TD) children (1f/12m; age 13.9 ± 3 years) in conjunction with NRS. Regression of different combinations of nuisance variables affected FC analysis from a seed in the posterior cingulate cortex (PCC) to other areas of the default mode network (DMN) in both BOLD and pCASL data sets. Consistent with existing literature on BOLD-FC, we observed improved spatial specificity after physiological noise reduction and improved long-range connectivity using head movement related regressors. Furthermore, 3D BS GRASE pCASL shows much higher temporal SNR compared to dual-echo 2D-EPI pCASL and similar effects of noise reduction as those observed for BOLD. Seed-based FC analysis using 3D BS GRASE pCASL in children with ASD and TD children showed that noise reduction including physiological and motion related signals as nuisance variables is crucial for identifying altered long-range connectivity from PCC to frontal brain areas associated with ASD. This is the first study that systematically evaluated the effects of

On the Temporal Variability of Low-Mode Internal Tides in the Deep Ocean

Science.gov (United States)

Ray, Richard D.; Zaron, E. D.

2010-01-01

In situ measurements of internal tides are typically characterized by high temporal variability, with strong dependence on stratification, mesoscale eddies, and background currents commonly observed. Thus, it is surprising to find phase-locked internal tides detectable by satellite altimetry. An important question is how much tidal variability is missed by altimetry. We address this question in several ways. We subset the altimetry by season and find only very small changes -- an important exception being internal tides in the South China Sea where we observe strong seasonal dependence. A wavenumber-domain analysis confirms that throughout most of the global ocean there is little temporal variability in altimetric internal-tide signals, at least in the first baroclinic mode, which is the mode that dominates surface elevation. The analysis shows higher order modes to be significantly more variable. The results of this study have important practical implications for the anticipated SWOT wide-swath altimeter mission, for which removal of internal tide signals is critical for observing non-tidal submesoscale phenomena.

Variability of Neuronal Responses: Types and Functional Significance in Neuroplasticity and Neural Darwinism.

Science.gov (United States)

Chervyakov, Alexander V; Sinitsyn, Dmitry O; Piradov, Michael A

2016-01-01

HIGHLIGHTS We suggest classifying variability of neuronal responses as follows: false (associated with a lack of knowledge about the influential factors), "genuine harmful" (noise), "genuine neutral" (synonyms, repeats), and "genuine useful" (the basis of neuroplasticity and learning).The genuine neutral variability is considered in terms of the phenomenon of degeneracy.Of particular importance is the genuine useful variability that is considered as a potential basis for neuroplasticity and learning. This type of variability is considered in terms of the neural Darwinism theory. In many cases, neural signals detected under the same external experimental conditions significantly change from trial to trial. The variability phenomenon, which complicates extraction of reproducible results and is ignored in many studies by averaging, has attracted attention of researchers in recent years. In this paper, we classify possible types of variability based on its functional significance and describe features of each type. We describe the key adaptive significance of variability at the neural network level and the degeneracy phenomenon that may be important for learning processes in connection with the principle of neuronal group selection.

Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems

Directory of Open Access Journals (Sweden)

José Carlos Ortiz-Bayliss

2018-01-01

Full Text Available When solving constraint satisfaction problems (CSPs, it is a common practice to rely on heuristics to decide which variable should be instantiated at each stage of the search. But, this ordering influences the search cost. Even so, and to the best of our knowledge, no earlier work has dealt with how first variable orderings affect the overall cost. In this paper, we explore the cost of finding high-quality orderings of variables within constraint satisfaction problems. We also study differences among the orderings produced by some commonly used heuristics and the way bad first decisions affect the search cost. One of the most important findings of this work confirms the paramount importance of first decisions. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. We propose a simple method to improve early decisions of heuristics. By using it, performance of heuristics increases.

Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems.

Science.gov (United States)

Ortiz-Bayliss, José Carlos; Amaya, Ivan; Conant-Pablos, Santiago Enrique; Terashima-Marín, Hugo

2018-01-01

When solving constraint satisfaction problems (CSPs), it is a common practice to rely on heuristics to decide which variable should be instantiated at each stage of the search. But, this ordering influences the search cost. Even so, and to the best of our knowledge, no earlier work has dealt with how first variable orderings affect the overall cost. In this paper, we explore the cost of finding high-quality orderings of variables within constraint satisfaction problems. We also study differences among the orderings produced by some commonly used heuristics and the way bad first decisions affect the search cost. One of the most important findings of this work confirms the paramount importance of first decisions. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. We propose a simple method to improve early decisions of heuristics. By using it, performance of heuristics increases.

Articulatory variability in cluttering.

Science.gov (United States)

Hartinger, Mariam; Mooshammer, Christine

2008-01-01

In order to investigate the articulatory processes of the hasty and mumbled speech in cluttering, the kinematic variability was analysed by means of electromagnetic midsagittal articulography. In contrast to persons with stuttering, those with cluttering improve their intelligibility by concentrating on their speech task. Variability has always been an important criterion in comparable studies of stuttering and is discussed in terms of the stability of the speech motor system. The aim of the current study was to analyse the spatial and temporal variability in the speech of three persons with cluttering (PWC) and three control speakers. All participants were native speakers of German. The speech material consisted of repetitive CV syllables and loan words such as 'emotionalisieren', because PWC have the severest problems with long words with a complex syllable structure. The results showed a significantly higher coefficient of variation for PWC in loan word production, both in the temporal and in the spatial domain, whereas the means of displacements and durations did not differ between groups. These findings were discussed in terms of the effects of the linguistic complexity, since for the syllable repetition task, no significant differences between PWC and controls were found. Copyright 2008 S. Karger AG, Basel.

A study on effects of demographic variables on success of social media

Directory of Open Access Journals (Sweden)

Marjan Mohammadreza

2012-10-01

Full Text Available In the recent years, social media have developed significantly and their usages have become main activities of internet users. The proposed study of this paper considers the effects of personal characteristics such as age, gender and marital status on social media. The study designs a questionnaire and distributes 385 questionnaires among students who are enrolled in different educational levels in governmental university named Allameh Tabatabayi university located in Tehran, Iran during the year of 2011. Because of abnormality of data, non-parametric test were used. In this research, we studied the effects of demographic variables on success of social media. The results showed that success of social media is more important among female students. Marriage situation shows that social media success variable is more important among married than single ones and, finally, this variable is more important among older people.

The contextual effects of social capital on health: a cross-national instrumental variable analysis.

Science.gov (United States)

Kim, Daniel; Baum, Christopher F; Ganz, Michael L; Subramanian, S V; Kawachi, Ichiro

2011-12-01

Past research on the associations between area-level/contextual social capital and health has produced conflicting evidence. However, interpreting this rapidly growing literature is difficult because estimates using conventional regression are prone to major sources of bias including residual confounding and reverse causation. Instrumental variable (IV) analysis can reduce such bias. Using data on up to 167,344 adults in 64 nations in the European and World Values Surveys and applying IV and ordinary least squares (OLS) regression, we estimated the contextual effects of country-level social trust on individual self-rated health. We further explored whether these associations varied by gender and individual levels of trust. Using OLS regression, we found higher average country-level trust to be associated with better self-rated health in both women and men. Instrumental variable analysis yielded qualitatively similar results, although the estimates were more than double in size in both sexes when country population density and corruption were used as instruments. The estimated health effects of raising the percentage of a country's population that trusts others by 10 percentage points were at least as large as the estimated health effects of an individual developing trust in others. These findings were robust to alternative model specifications and instruments. Conventional regression and to a lesser extent IV analysis suggested that these associations are more salient in women and in women reporting social trust. In a large cross-national study, our findings, including those using instrumental variables, support the presence of beneficial effects of higher country-level trust on self-rated health. Previous findings for contextual social capital using traditional regression may have underestimated the true associations. Given the close linkages between self-rated health and all-cause mortality, the public health gains from raising social capital within and across

The Salience of Selected Variables on Choice for Movie Attendance among High School Students.

Science.gov (United States)

Austin, Bruce A.

A questionnaire was designed for a study assessing both the importance of 28 variables in movie attendance and the importance of movie-going as a leisure-time activity. Respondents were 130 ninth and twelfth grade students. The 28 variables were broadly organized into eight categories: movie production personnel, production elements, advertising,…

North atlantic multidecadal climate variability: An investigation of dominant time scales and processes

NARCIS (Netherlands)

Frankcombe, L.M.|info:eu-repo/dai/nl/304829838; von der Heydt, A.S.|info:eu-repo/dai/nl/245567526; Dijkstra, H.A.|info:eu-repo/dai/nl/073504467

2010-01-01

The issue of multidecadal variability in the North Atlantic has been an important topic of late. It is clear that there are multidecadal variations in several climate variables in the North Atlantic, such as sea surface temperature and sea level height. The details of this variability, in particular

Harnessing real world data from wearables and self-monitoring devices: feasibility, confounders and ethical considerations

Directory of Open Access Journals (Sweden)

Uttam Barick

2016-07-01

Full Text Available The increasing usage of smart phones has compelled mobile technology to become a universal part of everyday life. From wearable gadgets to sophisticated implantable medical devices, the advent of mobile technology has completely transformed the healthcare delivery scenario. Self-report measures enabled by mobile technology are increasingly becoming a more time and cost efficient method of assessing real world health outcomes. But, amidst all the optimism, there are concerns also on adopting this technology as regulations and ethical considerations on privacy legislations of end users are unclear. In general, the healthcare industry functions on some stringent regulations and compliances to ensure the safety and protection of patient information. A couple of the most common regulations are Health Insurance Portability Accountability Act (HIPPA and Health Information Technology for Economic and Clinical Health (HITECH. To harness the true potential of mobile technology to empower stakeholders and provide them a common platform which seamlessly integrates healthcare delivery and research, it is imperative that challenges and drawbacks in the sphere are identified and addressed. In this age of information and technology, no stones should be left unturned to ensure that the human race has access to the best healthcare services without an intrusion into his/her confidentiality. This article is an overview of the role of tracking and self-monitoring devices in data collection for real world evidence/observational studies in context to feasibility, confounders and ethical considerations.

On the Importance of Elimination Heuristics in Lazy Propagation

DEFF Research Database (Denmark)

Madsen, Anders Læsø; Butz, Cory J.

2012-01-01

elimination orders on-line. This paper considers the importance of elimination heuristics in LP when using Variable Elimination (VE) as the message and single marginal computation algorithm. It considers well-known cost measures for selecting the next variable to eliminate and a new cost measure....... The empirical evaluation examines dierent heuristics as well as sequences of cost measures, and was conducted on real-world and randomly generated Bayesian networks. The results show that for most cases performance is robust relative to the cost measure used and in some cases the elimination heuristic can have...

Design study and performance analysis of a high-speed multistage variable-geometry fan for a variable cycle engine

Science.gov (United States)

Sullivan, T. J.; Parker, D. E.

1979-01-01

A design technology study was performed to identify a high speed, multistage, variable geometry fan configuration capable of achieving wide flow modulation with near optimum efficiency at the important operating condition. A parametric screening study of the front and rear block fans was conducted in which the influence of major fan design features on weight and efficiency was determined. Key design parameters were varied systematically to determine the fan configuration most suited for a double bypass, variable cycle engine. Two and three stage fans were considered for the front block. A single stage, core driven fan was studied for the rear block. Variable geometry concepts were evaluated to provide near optimum off design performance. A detailed aerodynamic design and a preliminary mechanical design were carried out for the selected fan configuration. Performance predictions were made for the front and rear block fans.