WorldWideScience

Sample records for outcomes statistical analysis

  1. Demonstration of a software design and statistical analysis methodology with application to patient outcomes data sets.

    Science.gov (United States)

    Mayo, Charles; Conners, Steve; Warren, Christopher; Miller, Robert; Court, Laurence; Popple, Richard

    2013-11-01

    With emergence of clinical outcomes databases as tools utilized routinely within institutions, comes need for software tools to support automated statistical analysis of these large data sets and intrainstitutional exchange from independent federated databases to support data pooling. In this paper, the authors present a design approach and analysis methodology that addresses both issues. A software application was constructed to automate analysis of patient outcomes data using a wide range of statistical metrics, by combining use of C#.Net and R code. The accuracy and speed of the code was evaluated using benchmark data sets. The approach provides data needed to evaluate combinations of statistical measurements for ability to identify patterns of interest in the data. Through application of the tools to a benchmark data set for dose-response threshold and to SBRT lung data sets, an algorithm was developed that uses receiver operator characteristic curves to identify a threshold value and combines use of contingency tables, Fisher exact tests, Welch t-tests, and Kolmogorov-Smirnov tests to filter the large data set to identify values demonstrating dose-response. Kullback-Leibler divergences were used to provide additional confirmation. The work demonstrates the viability of the design approach and the software tool for analysis of large data sets.

  2. Influence of peer review on the reporting of primary outcome(s) and statistical analyses of randomised trials.

    Science.gov (United States)

    Hopewell, Sally; Witt, Claudia M; Linde, Klaus; Icke, Katja; Adedire, Olubusola; Kirtley, Shona; Altman, Douglas G

    2018-01-11

    Selective reporting of outcomes in clinical trials is a serious problem. We aimed to investigate the influence of the peer review process within biomedical journals on reporting of primary outcome(s) and statistical analyses within reports of randomised trials. Each month, PubMed (May 2014 to April 2015) was searched to identify primary reports of randomised trials published in six high-impact general and 12 high-impact specialty journals. The corresponding author of each trial was invited to complete an online survey asking authors about changes made to their manuscript as part of the peer review process. Our main outcomes were to assess: (1) the nature and extent of changes as part of the peer review process, in relation to reporting of the primary outcome(s) and/or primary statistical analysis; (2) how often authors followed these requests; and (3) whether this was related to specific journal or trial characteristics. Of 893 corresponding authors who were invited to take part in the online survey 258 (29%) responded. The majority of trials were multicentre (n = 191; 74%); median sample size 325 (IQR 138 to 1010). The primary outcome was clearly defined in 92% (n = 238), of which the direction of treatment effect was statistically significant in 49%. The majority responded (1-10 Likert scale) they were satisfied with the overall handling (mean 8.6, SD 1.5) and quality of peer review (mean 8.5, SD 1.5) of their manuscript. Only 3% (n = 8) said that the editor or peer reviewers had asked them to change or clarify the trial's primary outcome. However, 27% (n = 69) reported they were asked to change or clarify the statistical analysis of the primary outcome; most had fulfilled the request, the main motivation being to improve the statistical methods (n = 38; 55%) or avoid rejection (n = 30; 44%). Overall, there was little association between authors being asked to make this change and the type of journal, intervention, significance of the

  3. Diagnosis checking of statistical analysis in RCTs indexed in PubMed.

    Science.gov (United States)

    Lee, Paul H; Tse, Andy C Y

    2017-11-01

    Statistical analysis is essential for reporting of the results of randomized controlled trials (RCTs), as well as evaluating their effectiveness. However, the validity of a statistical analysis also depends on whether the assumptions of that analysis are valid. To review all RCTs published in journals indexed in PubMed during December 2014 to provide a complete picture of how RCTs handle assumptions of statistical analysis. We reviewed all RCTs published in December 2014 that appeared in journals indexed in PubMed using the Cochrane highly sensitive search strategy. The 2014 impact factors of the journals were used as proxies for their quality. The type of statistical analysis used and whether the assumptions of the analysis were tested were reviewed. In total, 451 papers were included. Of the 278 papers that reported a crude analysis for the primary outcomes, 31 (27·2%) reported whether the outcome was normally distributed. Of the 172 papers that reported an adjusted analysis for the primary outcomes, diagnosis checking was rarely conducted, with only 20%, 8·6% and 7% checked for generalized linear model, Cox proportional hazard model and multilevel model, respectively. Study characteristics (study type, drug trial, funding sources, journal type and endorsement of CONSORT guidelines) were not associated with the reporting of diagnosis checking. The diagnosis of statistical analyses in RCTs published in PubMed-indexed journals was usually absent. Journals should provide guidelines about the reporting of a diagnosis of assumptions. © 2017 Stichting European Society for Clinical Investigation Journal Foundation.

  4. Statistical analysis plan for the EuroHYP-1 trial

    DEFF Research Database (Denmark)

    Winkel, Per; Bath, Philip M; Gluud, Christian

    2017-01-01

    Score; (4) brain infarct size at 48 +/-24 hours; (5) EQ-5D-5 L score, and (6) WHODAS 2.0 score. Other outcomes are: the primary safety outcome serious adverse events; and the incremental cost-effectiveness, and cost utility ratios. The analysis sets include (1) the intention-to-treat population, and (2...... outcome), logistic regression (binary outcomes), general linear model (continuous outcomes), and the Poisson or negative binomial model (rate outcomes). DISCUSSION: Major adjustments compared with the original statistical analysis plan encompass: (1) adjustment of analyses by nationality; (2) power......) the per protocol population. The sample size is estimated to 800 patients (5% type 1 and 20% type 2 errors). All analyses are adjusted for the protocol-specified stratification variables (nationality of centre), and the minimisation variables. In the analysis, we use ordinal regression (the primary...

  5. Outcomes Definitions and Statistical Tests in Oncology Studies: A Systematic Review of the Reporting Consistency.

    Science.gov (United States)

    Rivoirard, Romain; Duplay, Vianney; Oriol, Mathieu; Tinquaut, Fabien; Chauvin, Franck; Magne, Nicolas; Bourmaud, Aurelie

    2016-01-01

    Quality of reporting for Randomized Clinical Trials (RCTs) in oncology was analyzed in several systematic reviews, but, in this setting, there is paucity of data for the outcomes definitions and consistency of reporting for statistical tests in RCTs and Observational Studies (OBS). The objective of this review was to describe those two reporting aspects, for OBS and RCTs in oncology. From a list of 19 medical journals, three were retained for analysis, after a random selection: British Medical Journal (BMJ), Annals of Oncology (AoO) and British Journal of Cancer (BJC). All original articles published between March 2009 and March 2014 were screened. Only studies whose main outcome was accompanied by a corresponding statistical test were included in the analysis. Studies based on censored data were excluded. Primary outcome was to assess quality of reporting for description of primary outcome measure in RCTs and of variables of interest in OBS. A logistic regression was performed to identify covariates of studies potentially associated with concordance of tests between Methods and Results parts. 826 studies were included in the review, and 698 were OBS. Variables were described in Methods section for all OBS studies and primary endpoint was clearly detailed in Methods section for 109 RCTs (85.2%). 295 OBS (42.2%) and 43 RCTs (33.6%) had perfect agreement for reported statistical test between Methods and Results parts. In multivariable analysis, variable "number of included patients in study" was associated with test consistency: aOR (adjusted Odds Ratio) for third group compared to first group was equal to: aOR Grp3 = 0.52 [0.31-0.89] (P value = 0.009). Variables in OBS and primary endpoint in RCTs are reported and described with a high frequency. However, statistical tests consistency between methods and Results sections of OBS is not always noted. Therefore, we encourage authors and peer reviewers to verify consistency of statistical tests in oncology studies.

  6. Diagnosis of students' ability in a statistical course based on Rasch probabilistic outcome

    Science.gov (United States)

    Mahmud, Zamalia; Ramli, Wan Syahira Wan; Sapri, Shamsiah; Ahmad, Sanizah

    2017-06-01

    Measuring students' ability and performance are important in assessing how well students have learned and mastered the statistical courses. Any improvement in learning will depend on the student's approaches to learning, which are relevant to some factors of learning, namely assessment methods carrying out tasks consisting of quizzes, tests, assignment and final examination. This study has attempted an alternative approach to measure students' ability in an undergraduate statistical course based on the Rasch probabilistic model. Firstly, this study aims to explore the learning outcome patterns of students in a statistics course (Applied Probability and Statistics) based on an Entrance-Exit survey. This is followed by investigating students' perceived learning ability based on four Course Learning Outcomes (CLOs) and students' actual learning ability based on their final examination scores. Rasch analysis revealed that students perceived themselves as lacking the ability to understand about 95% of the statistics concepts at the beginning of the class but eventually they had a good understanding at the end of the 14 weeks class. In terms of students' performance in their final examination, their ability in understanding the topics varies at different probability values given the ability of the students and difficulty of the questions. Majority found the probability and counting rules topic to be the most difficult to learn.

  7. Systematic review of learning curves for minimally invasive abdominal surgery: a review of the methodology of data collection, depiction of outcomes, and statistical analysis.

    Science.gov (United States)

    Harrysson, Iliana J; Cook, Jonathan; Sirimanna, Pramudith; Feldman, Liane S; Darzi, Ara; Aggarwal, Rajesh

    2014-07-01

    To determine how minimally invasive surgical learning curves are assessed and define an ideal framework for this assessment. Learning curves have implications for training and adoption of new procedures and devices. In 2000, a review of the learning curve literature was done by Ramsay et al and it called for improved reporting and statistical evaluation of learning curves. Since then, a body of literature is emerging on learning curves but the presentation and analysis vary. A systematic search was performed of MEDLINE, EMBASE, ISI Web of Science, ERIC, and the Cochrane Library from 1985 to August 2012. The inclusion criteria are minimally invasive abdominal surgery formally analyzing the learning curve and English language. 592 (11.1%) of the identified studies met the selection criteria. Time is the most commonly used proxy for the learning curve (508, 86%). Intraoperative outcomes were used in 316 (53%) of the articles, postoperative outcomes in 306 (52%), technical skills in 102 (17%), and patient-oriented outcomes in 38 (6%) articles. Over time, there was evidence of an increase in the relative amount of laparoscopic and robotic studies (P statistical evidence of a change in the complexity of analysis (P = 0.121). Assessment of learning curves is needed to inform surgical training and evaluate new clinical procedures. An ideal analysis would account for the degree of complexity of individual cases and the inherent differences between surgeons. There is no single proxy that best represents the success of surgery, and hence multiple outcomes should be collected.

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

    Science.gov (United States)

    Ma, Yan; Mazumdar, Madhu

    2011-10-30

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

  9. Side effect of acting on the world: Acquisition of action-outcome statistic relation alters visual interpretation of action outcome

    Directory of Open Access Journals (Sweden)

    Takahiro eKawabe

    2013-09-01

    Full Text Available Humans can acquire the statistical features of the external world and employ them to control behaviors. Some external events occur in harmony with an agent’s action, and thus humans should also be able to acquire the statistical features between an action and its external outcome. We report that the acquired action-outcome statistical features alter the visual appearance of the action outcome. Pressing either of two assigned keys triggered visual motion whose direction was statistically biased either upward or downward, and observers judged the stimulus motion direction. Points of subjective equality (PSE for judging motion direction were shifted repulsively from the mean of the distribution associated with each key. Our Bayesian model accounted for the PSE shifts, indicating the optimal acquisition of the action-effect statistical relation. The PSE shifts were moderately attenuated when the action-outcome contingency was reduced. The Bayesian model again accounted for the attenuated PSE shifts. On the other hand, when the action-outcome contiguity was greatly reduced, the PSE shifts were greatly attenuated, and however, the Bayesian model could not accounted for the shifts. The results indicate that visual appearance can be modified by prediction based on the optimal acquisition of action-effect causal relation.

  10. Predicting radiotherapy outcomes using statistical learning techniques

    International Nuclear Information System (INIS)

    El Naqa, Issam; Bradley, Jeffrey D; Deasy, Joseph O; Lindsay, Patricia E; Hope, Andrew J

    2009-01-01

    Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model

  11. Cognitive Transfer Outcomes for a Simulation-Based Introductory Statistics Curriculum

    Science.gov (United States)

    Backman, Matthew D.; Delmas, Robert C.; Garfield, Joan

    2017-01-01

    Cognitive transfer is the ability to apply learned skills and knowledge to new applications and contexts. This investigation evaluates cognitive transfer outcomes for a tertiary-level introductory statistics course using the CATALST curriculum, which exclusively used simulation-based methods to develop foundations of statistical inference. A…

  12. Funding source and primary outcome changes in clinical trials registered on ClinicalTrials.gov are associated with the reporting of a statistically significant primary outcome: a cross-sectional study [v2; ref status: indexed, http://f1000r.es/5bj

    Directory of Open Access Journals (Sweden)

    Sreeram V Ramagopalan

    2015-04-01

    Full Text Available Background: We and others have shown a significant proportion of interventional trials registered on ClinicalTrials.gov have their primary outcomes altered after the listed study start and completion dates. The objectives of this study were to investigate whether changes made to primary outcomes are associated with the likelihood of reporting a statistically significant primary outcome on ClinicalTrials.gov. Methods: A cross-sectional analysis of all interventional clinical trials registered on ClinicalTrials.gov as of 20 November 2014 was performed. The main outcome was any change made to the initially listed primary outcome and the time of the change in relation to the trial start and end date. Findings: 13,238 completed interventional trials were registered with ClinicalTrials.gov that also had study results posted on the website. 2555 (19.3% had one or more statistically significant primary outcomes. Statistical analysis showed that registration year, funding source and primary outcome change after trial completion were associated with reporting a statistically significant primary outcome. Conclusions: Funding source and primary outcome change after trial completion are associated with a statistically significant primary outcome report on clinicaltrials.gov.

  13. Statistical data analysis using SAS intermediate statistical methods

    CERN Document Server

    Marasinghe, Mervyn G

    2018-01-01

    The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitab...

  14. Commentary: Using Potential Outcomes to Understand Causal Mediation Analysis

    Science.gov (United States)

    Imai, Kosuke; Jo, Booil; Stuart, Elizabeth A.

    2011-01-01

    In this commentary, we demonstrate how the potential outcomes framework can help understand the key identification assumptions underlying causal mediation analysis. We show that this framework can lead to the development of alternative research design and statistical analysis strategies applicable to the longitudinal data settings considered by…

  15. Common pitfalls in statistical analysis: Odds versus risk

    Science.gov (United States)

    Ranganathan, Priya; Aggarwal, Rakesh; Pramesh, C. S.

    2015-01-01

    In biomedical research, we are often interested in quantifying the relationship between an exposure and an outcome. “Odds” and “Risk” are the most common terms which are used as measures of association between variables. In this article, which is the fourth in the series of common pitfalls in statistical analysis, we explain the meaning of risk and odds and the difference between the two. PMID:26623395

  16. Statistical Compilation of the ICT Sector and Policy Analysis | Page 2 ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    ... to widen and deepen, so too does its impact on economic development. ... The outcomes of such efforts will subsequently inform policy discourse and ... Studies. Statistical Compilation of the ICT Sector and Policy Analysis project : country experiences; Malaysia ... Asian outlook: New growth dependent on new productivity.

  17. Australasian Resuscitation In Sepsis Evaluation trial statistical analysis plan.

    Science.gov (United States)

    Delaney, Anthony; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve

    2013-10-01

    The Australasian Resuscitation In Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the ED with severe sepsis. In keeping with current practice, and taking into considerations aspects of trial design and reporting specific to non-pharmacologic interventions, this document outlines the principles and methods for analysing and reporting the trial results. The document is prepared prior to completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and prior to completion of the two related international studies. The statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. The data collected by the research team as specified in the study protocol, and detailed in the study case report form were reviewed. Information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation and other related therapies, and other relevant data are described with appropriate comparisons between groups. The primary, secondary and tertiary outcomes for the study are defined, with description of the planned statistical analyses. A statistical analysis plan was developed, along with a trial profile, mock-up tables and figures. A plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies, along with adverse events are described. The primary, secondary and tertiary outcomes are described along with identification of subgroups to be analysed. A statistical analysis plan for the ARISE study has been developed, and is available in the public domain, prior to the completion of recruitment into the

  18. A New Statistical Method to Determine the Degree of Validity of Health Economic Model Outcomes against Empirical Data.

    Science.gov (United States)

    Corro Ramos, Isaac; van Voorn, George A K; Vemer, Pepijn; Feenstra, Talitha L; Al, Maiwenn J

    2017-09-01

    The validation of health economic (HE) model outcomes against empirical data is of key importance. Although statistical testing seems applicable, guidelines for the validation of HE models lack guidance on statistical validation, and actual validation efforts often present subjective judgment of graphs and point estimates. To discuss the applicability of existing validation techniques and to present a new method for quantifying the degrees of validity statistically, which is useful for decision makers. A new Bayesian method is proposed to determine how well HE model outcomes compare with empirical data. Validity is based on a pre-established accuracy interval in which the model outcomes should fall. The method uses the outcomes of a probabilistic sensitivity analysis and results in a posterior distribution around the probability that HE model outcomes can be regarded as valid. We use a published diabetes model (Modelling Integrated Care for Diabetes based on Observational data) to validate the outcome "number of patients who are on dialysis or with end-stage renal disease." Results indicate that a high probability of a valid outcome is associated with relatively wide accuracy intervals. In particular, 25% deviation from the observed outcome implied approximately 60% expected validity. Current practice in HE model validation can be improved by using an alternative method based on assessing whether the model outcomes fit to empirical data at a predefined level of accuracy. This method has the advantage of assessing both model bias and parameter uncertainty and resulting in a quantitative measure of the degree of validity that penalizes models predicting the mean of an outcome correctly but with overly wide credible intervals. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  19. Statistical power analysis a simple and general model for traditional and modern hypothesis tests

    CERN Document Server

    Murphy, Kevin R; Wolach, Allen

    2014-01-01

    Noted for its accessible approach, this text applies the latest approaches of power analysis to both null hypothesis and minimum-effect testing using the same basic unified model. Through the use of a few simple procedures and examples, the authors show readers with little expertise in statistical analysis how to obtain the values needed to carry out the power analysis for their research. Illustrations of how these analyses work and how they can be used to choose the appropriate criterion for defining statistically significant outcomes are sprinkled throughout. The book presents a simple and g

  20. The Australasian Resuscitation in Sepsis Evaluation (ARISE) trial statistical analysis plan.

    Science.gov (United States)

    Delaney, Anthony P; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve

    2013-09-01

    The Australasian Resuscitation in Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the emergency department with severe sepsis. In keeping with current practice, and considering aspects of trial design and reporting specific to non-pharmacological interventions, our plan outlines the principles and methods for analysing and reporting the trial results. The document is prepared before completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and before completion of the two related international studies. Our statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. We reviewed the data collected by the research team as specified in the study protocol and detailed in the study case report form. We describe information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation, other related therapies and other relevant data with appropriate comparisons between groups. We define the primary, secondary and tertiary outcomes for the study, with description of the planned statistical analyses. We have developed a statistical analysis plan with a trial profile, mock-up tables and figures. We describe a plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies and adverse events. We describe the primary, secondary and tertiary outcomes with identification of subgroups to be analysed. We have developed a statistical analysis plan for the ARISE study, available in the public domain, before the completion of recruitment into the study. This will minimise analytical bias and

  1. Beginning statistics with data analysis

    CERN Document Server

    Mosteller, Frederick; Rourke, Robert EK

    2013-01-01

    This introduction to the world of statistics covers exploratory data analysis, methods for collecting data, formal statistical inference, and techniques of regression and analysis of variance. 1983 edition.

  2. Statistical analysis of subjective preferences for video enhancement

    Science.gov (United States)

    Woods, Russell L.; Satgunam, PremNandhini; Bronstad, P. Matthew; Peli, Eli

    2010-02-01

    Measuring preferences for moving video quality is harder than for static images due to the fleeting and variable nature of moving video. Subjective preferences for image quality can be tested by observers indicating their preference for one image over another. Such pairwise comparisons can be analyzed using Thurstone scaling (Farrell, 1999). Thurstone (1927) scaling is widely used in applied psychology, marketing, food tasting and advertising research. Thurstone analysis constructs an arbitrary perceptual scale for the items that are compared (e.g. enhancement levels). However, Thurstone scaling does not determine the statistical significance of the differences between items on that perceptual scale. Recent papers have provided inferential statistical methods that produce an outcome similar to Thurstone scaling (Lipovetsky and Conklin, 2004). Here, we demonstrate that binary logistic regression can analyze preferences for enhanced video.

  3. Cluster analysis as a prediction tool for pregnancy outcomes.

    Science.gov (United States)

    Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

    2015-03-01

    Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

  4. Research design and statistical analysis

    CERN Document Server

    Myers, Jerome L; Lorch Jr, Robert F

    2013-01-01

    Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data.  The book's goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations.  Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions.  Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations

  5. Confounding in statistical mediation analysis: What it is and how to address it.

    Science.gov (United States)

    Valente, Matthew J; Pelham, William E; Smyth, Heather; MacKinnon, David P

    2017-11-01

    Psychology researchers are often interested in mechanisms underlying how randomized interventions affect outcomes such as substance use and mental health. Mediation analysis is a common statistical method for investigating psychological mechanisms that has benefited from exciting new methodological improvements over the last 2 decades. One of the most important new developments is methodology for estimating causal mediated effects using the potential outcomes framework for causal inference. Potential outcomes-based methods developed in epidemiology and statistics have important implications for understanding psychological mechanisms. We aim to provide a concise introduction to and illustration of these new methods and emphasize the importance of confounder adjustment. First, we review the traditional regression approach for estimating mediated effects. Second, we describe the potential outcomes framework. Third, we define what a confounder is and how the presence of a confounder can provide misleading evidence regarding mechanisms of interventions. Fourth, we describe experimental designs that can help rule out confounder bias. Fifth, we describe new statistical approaches to adjust for measured confounders of the mediator-outcome relation and sensitivity analyses to probe effects of unmeasured confounders on the mediated effect. All approaches are illustrated with application to a real counseling intervention dataset. Counseling psychologists interested in understanding the causal mechanisms of their interventions can benefit from incorporating the most up-to-date techniques into their mediation analyses. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  6. Statistical data analysis handbook

    National Research Council Canada - National Science Library

    Wall, Francis J

    1986-01-01

    It must be emphasized that this is not a text book on statistics. Instead it is a working tool that presents data analysis in clear, concise terms which can be readily understood even by those without formal training in statistics...

  7. A Statistical Model for Misreported Binary Outcomes in Clustered RCTs of Education Interventions

    Science.gov (United States)

    Schochet, Peter Z.

    2013-01-01

    In education randomized control trials (RCTs), the misreporting of student outcome data could lead to biased estimates of average treatment effects (ATEs) and their standard errors. This article discusses a statistical model that adjusts for misreported binary outcomes for two-level, school-based RCTs, where it is assumed that misreporting could…

  8. Statistical Power in Meta-Analysis

    Science.gov (United States)

    Liu, Jin

    2015-01-01

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

  9. Rweb:Web-based Statistical Analysis

    Directory of Open Access Journals (Sweden)

    Jeff Banfield

    1999-03-01

    Full Text Available Rweb is a freely accessible statistical analysis environment that is delivered through the World Wide Web (WWW. It is based on R, a well known statistical analysis package. The only requirement to run the basic Rweb interface is a WWW browser that supports forms. If you want graphical output you must, of course, have a browser that supports graphics. The interface provides access to WWW accessible data sets, so you may run Rweb on your own data. Rweb can provide a four window statistical computing environment (code input, text output, graphical output, and error information through browsers that support Javascript. There is also a set of point and click modules under development for use in introductory statistics courses.

  10. Regularized Statistical Analysis of Anatomy

    DEFF Research Database (Denmark)

    Sjöstrand, Karl

    2007-01-01

    This thesis presents the application and development of regularized methods for the statistical analysis of anatomical structures. Focus is on structure-function relationships in the human brain, such as the connection between early onset of Alzheimer’s disease and shape changes of the corpus...... and mind. Statistics represents a quintessential part of such investigations as they are preluded by a clinical hypothesis that must be verified based on observed data. The massive amounts of image data produced in each examination pose an important and interesting statistical challenge...... efficient algorithms which make the analysis of large data sets feasible, and gives examples of applications....

  11. The covariance between the number of accidents and the number of victims in multivariate analysis of accident related outcomes

    NARCIS (Netherlands)

    Bijleveld, F. D.

    In this study some statistical issues involved in the simultaneous analysis of accident related outcomes of the road traffic process are investigated. Since accident related outcomes like the number of victims, fatalities or accidents show interdependencies, their simultaneous analysis requires that

  12. Statistical methods for astronomical data analysis

    CERN Document Server

    Chattopadhyay, Asis Kumar

    2014-01-01

    This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for ...

  13. Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force.

    Science.gov (United States)

    Hauber, A Brett; González, Juan Marcos; Groothuis-Oudshoorn, Catharina G M; Prior, Thomas; Marshall, Deborah A; Cunningham, Charles; IJzerman, Maarten J; Bridges, John F P

    2016-06-01

    Conjoint analysis is a stated-preference survey method that can be used to elicit responses that reveal preferences, priorities, and the relative importance of individual features associated with health care interventions or services. Conjoint analysis methods, particularly discrete choice experiments (DCEs), have been increasingly used to quantify preferences of patients, caregivers, physicians, and other stakeholders. Recent consensus-based guidance on good research practices, including two recent task force reports from the International Society for Pharmacoeconomics and Outcomes Research, has aided in improving the quality of conjoint analyses and DCEs in outcomes research. Nevertheless, uncertainty regarding good research practices for the statistical analysis of data from DCEs persists. There are multiple methods for analyzing DCE data. Understanding the characteristics and appropriate use of different analysis methods is critical to conducting a well-designed DCE study. This report will assist researchers in evaluating and selecting among alternative approaches to conducting statistical analysis of DCE data. We first present a simplistic DCE example and a simple method for using the resulting data. We then present a pedagogical example of a DCE and one of the most common approaches to analyzing data from such a question format-conditional logit. We then describe some common alternative methods for analyzing these data and the strengths and weaknesses of each alternative. We present the ESTIMATE checklist, which includes a list of questions to consider when justifying the choice of analysis method, describing the analysis, and interpreting the results. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  14. Analysis and meta-analysis of single-case designs with a standardized mean difference statistic: a primer and applications.

    Science.gov (United States)

    Shadish, William R; Hedges, Larry V; Pustejovsky, James E

    2014-04-01

    This article presents a d-statistic for single-case designs that is in the same metric as the d-statistic used in between-subjects designs such as randomized experiments and offers some reasons why such a statistic would be useful in SCD research. The d has a formal statistical development, is accompanied by appropriate power analyses, and can be estimated using user-friendly SPSS macros. We discuss both advantages and disadvantages of d compared to other approaches such as previous d-statistics, overlap statistics, and multilevel modeling. It requires at least three cases for computation and assumes normally distributed outcomes and stationarity, assumptions that are discussed in some detail. We also show how to test these assumptions. The core of the article then demonstrates in depth how to compute d for one study, including estimation of the autocorrelation and the ratio of between case variance to total variance (between case plus within case variance), how to compute power using a macro, and how to use the d to conduct a meta-analysis of studies using single-case designs in the free program R, including syntax in an appendix. This syntax includes how to read data, compute fixed and random effect average effect sizes, prepare a forest plot and a cumulative meta-analysis, estimate various influence statistics to identify studies contributing to heterogeneity and effect size, and do various kinds of publication bias analyses. This d may prove useful for both the analysis and meta-analysis of data from SCDs. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  15. Ten ways to improve the use of statistical mediation analysis in the practice of child and adolescent treatment research

    NARCIS (Netherlands)

    Maric, M.; Wiers, R.W.; Prins, P.J.M.

    2012-01-01

    Despite guidelines and repeated calls from the literature, statistical mediation analysis in youth treatment outcome research is rare. Even more concerning is that many studies that have reported mediation analyses do not fulfill basic requirements for mediation analysis, providing inconclusive data

  16. Effectiveness of a healthy lifestyle intervention for low back pain and osteoarthritis of the knee: protocol and statistical analysis plan for two randomised controlled trials

    Directory of Open Access Journals (Sweden)

    Kate M. O’Brien

    Full Text Available ABSTRACT Background These trials are the first randomised controlled trials of telephone-based weight management and healthy lifestyle interventions for low back pain and knee osteoarthritis. This article describes the protocol and statistical analysis plan. Method These trials are parallel randomised controlled trials that investigate and compare the effect of a telephone-based weight management and healthy lifestyle intervention for improving pain intensity in overweight or obese patients with low back pain or knee osteoarthritis. The analysis plan was finalised prior to initiation of analyses. All data collected as part of the trial were reviewed, without stratification by group, and classified by baseline characteristics, process of care and trial outcomes. Trial outcomes were classified as primary and secondary outcomes. Appropriate descriptive statistics and statistical testing of between-group differences, where relevant, have been planned and described. Conclusions A protocol for standard analyses was developed for the results of two randomised controlled trials. This protocol describes the data, and the pre-determined statistical tests of relevant outcome measures. The plan demonstrates transparent and verifiable use of the data collected. This a priori protocol will be followed to ensure rigorous standards of data analysis are strictly adhered to.

  17. Effectiveness of a healthy lifestyle intervention for low back pain and osteoarthritis of the knee: protocol and statistical analysis plan for two randomised controlled trials

    Science.gov (United States)

    O’Brien, Kate M.; Williams, Amanda; Wiggers, John; Wolfenden, Luke; Yoong, Serene; Campbell, Elizabeth; Kamper, Steven J.; McAuley, James; Attia, John; Oldmeadow, Chris; Williams, Christopher M.

    2016-01-01

    ABSTRACT Background These trials are the first randomised controlled trials of telephone-based weight management and healthy lifestyle interventions for low back pain and knee osteoarthritis. This article describes the protocol and statistical analysis plan. Method These trials are parallel randomised controlled trials that investigate and compare the effect of a telephone-based weight management and healthy lifestyle intervention for improving pain intensity in overweight or obese patients with low back pain or knee osteoarthritis. The analysis plan was finalised prior to initiation of analyses. All data collected as part of the trial were reviewed, without stratification by group, and classified by baseline characteristics, process of care and trial outcomes. Trial outcomes were classified as primary and secondary outcomes. Appropriate descriptive statistics and statistical testing of between-group differences, where relevant, have been planned and described. Conclusions A protocol for standard analyses was developed for the results of two randomised controlled trials. This protocol describes the data, and the pre-determined statistical tests of relevant outcome measures. The plan demonstrates transparent and verifiable use of the data collected. This a priori protocol will be followed to ensure rigorous standards of data analysis are strictly adhered to. PMID:27683839

  18. An evaluation of intraoperative and postoperative outcomes of torsional mode versus longitudinal ultrasound mode phacoemulsification: a Meta-analysis

    Directory of Open Access Journals (Sweden)

    Pia Leon

    2016-06-01

    Full Text Available AIM: To evaluate and compare the intraoperative parameters and postoperative outcomes of torsional mode and longitudinal mode of phacoemulsification. METHODS: Pertinent studies were identified by a computerized MEDLINE search from January 2002 to September 2013. The Meta-analysis is composed of two parts. In the first part the intraoperative parameters were considered: ultrasound time (UST and cumulative dissipated energy (CDE. The intraoperative values were also distinctly considered for two categories (moderate and hard cataract group depending on the nuclear opacity grade. In the second part of the study the postoperative outcomes as the best corrected visual acuity (BCVA and the endothelial cell loss (ECL were taken in consideration. RESULTS: The UST and CDE values proved statistically significant in support of torsional mode for both moderate and hard cataract group. The analysis of BCVA did not present statistically significant difference between the two surgical modalities. The ECL count was statistically significant in support of torsional mode (P<0.001. CONCLUSION: The Meta-analysis shows the superiority of the torsional mode for intraoperative parameters (UST, CDE and postoperative ECL outcomes.

  19. An evaluation of intraoperative and postoperative outcomes of torsional mode versus longitudinal ultrasound mode phacoemulsification: a Meta-analysis.

    Science.gov (United States)

    Leon, Pia; Umari, Ingrid; Mangogna, Alessandro; Zanei, Andrea; Tognetto, Daniele

    2016-01-01

    To evaluate and compare the intraoperative parameters and postoperative outcomes of torsional mode and longitudinal mode of phacoemulsification. Pertinent studies were identified by a computerized MEDLINE search from January 2002 to September 2013. The Meta-analysis is composed of two parts. In the first part the intraoperative parameters were considered: ultrasound time (UST) and cumulative dissipated energy (CDE). The intraoperative values were also distinctly considered for two categories (moderate and hard cataract group) depending on the nuclear opacity grade. In the second part of the study the postoperative outcomes as the best corrected visual acuity (BCVA) and the endothelial cell loss (ECL) were taken in consideration. The UST and CDE values proved statistically significant in support of torsional mode for both moderate and hard cataract group. The analysis of BCVA did not present statistically significant difference between the two surgical modalities. The ECL count was statistically significant in support of torsional mode (P<0.001). The Meta-analysis shows the superiority of the torsional mode for intraoperative parameters (UST, CDE) and postoperative ECL outcomes.

  20. Surgical management of gynecomastia: an outcome analysis.

    Science.gov (United States)

    Kasielska, Anna; Antoszewski, Bogusław

    2013-11-01

    The aim of the study was to evaluate the surgical management of gynecomastia focusing on techniques, complications, and aesthetic results. The authors also proposed an evaluation scale of the cosmetic results after the treatment. We conducted a retrospective analysis of 113 patients undergoing the surgery for gynecomastia in our department. Preoperative clinical evaluation included the grade of gynecomastia, its etiology, and side, whereas postoperative analysis concerned histologic findings, complications, and cosmetic results. Operative techniques included subcutaneous mastectomy through circumareolar approach in 94 patients, subcutaneous mastectomy with skin excision in 9 patients, inverted-T reduction mastopexy with nipple-areola complex (NAC) transposition in 6 subjects, and breast amputation through inframammary fold approach with free transplantation of NAC in 4 cases. Complications occurred in a total of 25 patients and did not differ statistically within Simon stages. The operative technique appeared to be the crucial determinant of good aesthetic outcome. The postoperative result of shape and symmetry of the NAC was not as satisfactory as postoperative breast size and symmetry. We showed that subcutaneous mastectomy using a circumareolar incision without additional liposuction provides a good or very good aesthetic outcome in patients with Simon grades I to IIa gynecomastia and that it is challenging to achieve a very good or even a good aesthetic outcome in patients with Simon grades IIb to III gynecomastia.

  1. A Statistical Toolkit for Data Analysis

    International Nuclear Information System (INIS)

    Donadio, S.; Guatelli, S.; Mascialino, B.; Pfeiffer, A.; Pia, M.G.; Ribon, A.; Viarengo, P.

    2006-01-01

    The present project aims to develop an open-source and object-oriented software Toolkit for statistical data analysis. Its statistical testing component contains a variety of Goodness-of-Fit tests, from Chi-squared to Kolmogorov-Smirnov, to less known, but generally much more powerful tests such as Anderson-Darling, Goodman, Fisz-Cramer-von Mises, Kuiper, Tiku. Thanks to the component-based design and the usage of the standard abstract interfaces for data analysis, this tool can be used by other data analysis systems or integrated in experimental software frameworks. This Toolkit has been released and is downloadable from the web. In this paper we describe the statistical details of the algorithms, the computational features of the Toolkit and describe the code validation

  2. Outcome predictors in the management of intramedullary classic ependymoma: An integrative survival analysis.

    Science.gov (United States)

    Wang, Yinqing; Cai, Ranze; Wang, Rui; Wang, Chunhua; Chen, Chunmei

    2018-06-01

    This is a retrospective study.The aim of this study was to illustrate the survival outcomes of patients with classic ependymoma (CE) and identify potential prognostic factors.CE is the most common category of spinal ependymomas, but few published studies have discussed predictors of the survival outcome.A Boolean search of the PubMed, Embase, and OVID databases was conducted by 2 investigators independently. The objects were intramedullary grade II ependymoma according to 2007 WHO classification. Univariate Kaplan-Meier analysis and Log-Rank tests were performed to identify variables associated with progression-free survival (PFS) or overall survival (OS). Multivariate Cox regression was performed to assess hazard ratios (HRs) with 95% confidence intervals (95% CIs). Statistical analysis was performed by SPSS version 23.0 (IBM Corp.) with statistical significance defined as P analysis showed that patients who had undergone total resection (TR) had better PFS and OS than those with subtotal resection (STR) and biopsy (P = .002, P = .004, respectively). Within either univariate or multivariate analysis (P = .000, P = .07, respectively), histological type was an independent prognostic factor for PFS of CE [papillary type: HR 0.002, 95% CI (0.000-0.073), P = .001, tanycytic type: HR 0.010, 95% CI (0.000-0.218), P = .003].It was the first integrative analysis of CE to elucidate the correlation between kinds of factors and prognostic outcomes. Definite histological type and safely TR were foundation of CE's management. 4.

  3. Statistical considerations on safety analysis

    International Nuclear Information System (INIS)

    Pal, L.; Makai, M.

    2004-01-01

    The authors have investigated the statistical methods applied to safety analysis of nuclear reactors and arrived at alarming conclusions: a series of calculations with the generally appreciated safety code ATHLET were carried out to ascertain the stability of the results against input uncertainties in a simple experimental situation. Scrutinizing those calculations, we came to the conclusion that the ATHLET results may exhibit chaotic behavior. A further conclusion is that the technological limits are incorrectly set when the output variables are correlated. Another formerly unnoticed conclusion of the previous ATHLET calculations that certain innocent looking parameters (like wall roughness factor, the number of bubbles per unit volume, the number of droplets per unit volume) can influence considerably such output parameters as water levels. The authors are concerned with the statistical foundation of present day safety analysis practices and can only hope that their own misjudgment will be dispelled. Until then, the authors suggest applying correct statistical methods in safety analysis even if it makes the analysis more expensive. It would be desirable to continue exploring the role of internal parameters (wall roughness factor, steam-water surface in thermal hydraulics codes, homogenization methods in neutronics codes) in system safety codes and to study their effects on the analysis. In the validation and verification process of a code one carries out a series of computations. The input data are not precisely determined because measured data have an error, calculated data are often obtained from a more or less accurate model. Some users of large codes are content with comparing the nominal output obtained from the nominal input, whereas all the possible inputs should be taken into account when judging safety. At the same time, any statement concerning safety must be aleatory, and its merit can be judged only when the probability is known with which the

  4. Statistical shape analysis with applications in R

    CERN Document Server

    Dryden, Ian L

    2016-01-01

    A thoroughly revised and updated edition of this introduction to modern statistical methods for shape analysis Shape analysis is an important tool in the many disciplines where objects are compared using geometrical features. Examples include comparing brain shape in schizophrenia; investigating protein molecules in bioinformatics; and describing growth of organisms in biology. This book is a significant update of the highly-regarded `Statistical Shape Analysis’ by the same authors. The new edition lays the foundations of landmark shape analysis, including geometrical concepts and statistical techniques, and extends to include analysis of curves, surfaces, images and other types of object data. Key definitions and concepts are discussed throughout, and the relative merits of different approaches are presented. The authors have included substantial new material on recent statistical developments and offer numerous examples throughout the text. Concepts are introduced in an accessible manner, while reta...

  5. Spatial analysis statistics, visualization, and computational methods

    CERN Document Server

    Oyana, Tonny J

    2015-01-01

    An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis-containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS-as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statisti...

  6. Application of descriptive statistics in analysis of experimental data

    OpenAIRE

    Mirilović Milorad; Pejin Ivana

    2008-01-01

    Statistics today represent a group of scientific methods for the quantitative and qualitative investigation of variations in mass appearances. In fact, statistics present a group of methods that are used for the accumulation, analysis, presentation and interpretation of data necessary for reaching certain conclusions. Statistical analysis is divided into descriptive statistical analysis and inferential statistics. The values which represent the results of an experiment, and which are the subj...

  7. Statistical Analysis of Research Data | Center for Cancer Research

    Science.gov (United States)

    Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data. The Statistical Analysis of Research Data (SARD) course will be held on April 5-6, 2018 from 9 a.m.-5 p.m. at the National Institutes of Health's Natcher Conference Center, Balcony C on the Bethesda Campus. SARD is designed to provide an overview on the general principles of statistical analysis of research data.  The first day will feature univariate data analysis, including descriptive statistics, probability distributions, one- and two-sample inferential statistics.

  8. Ten Ways to Improve the Use of Statistical Mediation Analysis in the Practice of Child and Adolescent Treatment Research

    Science.gov (United States)

    Maric, Marija; Wiers, Reinout W.; Prins, Pier J. M.

    2012-01-01

    Despite guidelines and repeated calls from the literature, statistical mediation analysis in youth treatment outcome research is rare. Even more concerning is that many studies that "have" reported mediation analyses do not fulfill basic requirements for mediation analysis, providing inconclusive data and clinical implications. As a result, after…

  9. Topics in statistical data analysis for high-energy physics

    International Nuclear Information System (INIS)

    Cowan, G.

    2011-01-01

    These lectures concert two topics that are becoming increasingly important in the analysis of high-energy physics data: Bayesian statistics and multivariate methods. In the Bayesian approach, we extend the interpretation of probability not only to cover the frequency of repeatable outcomes but also to include a degree of belief. In this way we are able to associate probability with a hypothesis and thus to answer directly questions that cannot be addressed easily with traditional frequentist methods. In multivariate analysis, we try to exploit as much information as possible from the characteristics that we measure for each event to distinguish between event types. In particular we will look at a method that has gained popularity in high-energy physics in recent years: the boosted decision tree. Finally, we give a brief sketch of how multivariate methods may be applied in a search for a new signal process. (author)

  10. Statistical analysis with Excel for dummies

    CERN Document Server

    Schmuller, Joseph

    2013-01-01

    Take the mystery out of statistical terms and put Excel to work! If you need to create and interpret statistics in business or classroom settings, this easy-to-use guide is just what you need. It shows you how to use Excel's powerful tools for statistical analysis, even if you've never taken a course in statistics. Learn the meaning of terms like mean and median, margin of error, standard deviation, and permutations, and discover how to interpret the statistics of everyday life. You'll learn to use Excel formulas, charts, PivotTables, and other tools to make sense of everything fro

  11. Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders.

    Science.gov (United States)

    Vanderweele, Tyler J; Arah, Onyebuchi A

    2011-01-01

    Uncontrolled confounding in observational studies gives rise to biased effect estimates. Sensitivity analysis techniques can be useful in assessing the magnitude of these biases. In this paper, we use the potential outcomes framework to derive a general class of sensitivity-analysis formulas for outcomes, treatments, and measured and unmeasured confounding variables that may be categorical or continuous. We give results for additive, risk-ratio and odds-ratio scales. We show that these results encompass a number of more specific sensitivity-analysis methods in the statistics and epidemiology literature. The applicability, usefulness, and limits of the bias-adjustment formulas are discussed. We illustrate the sensitivity-analysis techniques that follow from our results by applying them to 3 different studies. The bias formulas are particularly simple and easy to use in settings in which the unmeasured confounding variable is binary with constant effect on the outcome across treatment levels.

  12. Vector-field statistics for the analysis of time varying clinical gait data.

    Science.gov (United States)

    Donnelly, C J; Alexander, C; Pataky, T C; Stannage, K; Reid, S; Robinson, M A

    2017-01-01

    In clinical settings, the time varying analysis of gait data relies heavily on the experience of the individual(s) assessing these biological signals. Though three dimensional kinematics are recognised as time varying waveforms (1D), exploratory statistical analysis of these data are commonly carried out with multiple discrete or 0D dependent variables. In the absence of an a priori 0D hypothesis, clinicians are at risk of making type I and II errors in their analyis of time varying gait signatures in the event statistics are used in concert with prefered subjective clinical assesment methods. The aim of this communication was to determine if vector field waveform statistics were capable of providing quantitative corroboration to practically significant differences in time varying gait signatures as determined by two clinically trained gait experts. The case study was a left hemiplegic Cerebral Palsy (GMFCS I) gait patient following a botulinum toxin (BoNT-A) injection to their left gastrocnemius muscle. When comparing subjective clinical gait assessments between two testers, they were in agreement with each other for 61% of the joint degrees of freedom and phases of motion analysed. For tester 1 and tester 2, they were in agreement with the vector-field analysis for 78% and 53% of the kinematic variables analysed. When the subjective analyses of tester 1 and tester 2 were pooled together and then compared to the vector-field analysis, they were in agreement for 83% of the time varying kinematic variables analysed. These outcomes demonstrate that in principle, vector-field statistics corroborates with what a team of clinical gait experts would classify as practically meaningful pre- versus post time varying kinematic differences. The potential for vector-field statistics to be used as a useful clinical tool for the objective analysis of time varying clinical gait data is established. Future research is recommended to assess the usefulness of vector-field analyses

  13. Statistical analysis of dynamic parameters of the core

    International Nuclear Information System (INIS)

    Ionov, V.S.

    2007-01-01

    The transients of various types were investigated for the cores of zero power critical facilities in RRC KI and NPP. Dynamic parameters of neutron transients were explored by tool statistical analysis. Its have sufficient duration, few channels for currents of chambers and reactivity and also some channels for technological parameters. On these values the inverse period. reactivity, lifetime of neutrons, reactivity coefficients and some effects of a reactivity are determinate, and on the values were restored values of measured dynamic parameters as result of the analysis. The mathematical means of statistical analysis were used: approximation(A), filtration (F), rejection (R), estimation of parameters of descriptive statistic (DSP), correlation performances (kk), regression analysis(KP), the prognosis (P), statistician criteria (SC). The calculation procedures were realized by computer language MATLAB. The reasons of methodical and statistical errors are submitted: inadequacy of model operation, precision neutron-physical parameters, features of registered processes, used mathematical model in reactivity meters, technique of processing for registered data etc. Examples of results of statistical analysis. Problems of validity of the methods used for definition and certification of values of statistical parameters and dynamic characteristics are considered (Authors)

  14. Retropubic radical prostatectomy: Clinicopathological observations and outcome analysis of 428 consecutive patients

    Directory of Open Access Journals (Sweden)

    Jagdeesh N Kulkarni

    2011-01-01

    Full Text Available Aim : We report the outcome analysis of retropubic radical prostatectomy (RRP performed in 428 patients in terms of pathological findings, complications, and survival. Materials and Methods : Systematically recorded case reports forms of consecutive 428 RRPs done over a 14-year period were analyzed using the SPSS 14 software. Secondary analysis was done to evaluate era specific (pre and post 2002 changes in clinical features and survivals. Results : Seven-year overall survival (OAS, cancer-specific survival (CSS, and event-free survival (EFS was 83.2%, 82.8%, and 69.8% respectively in our series. Era-specific survival showed higher CSS post 2002, and there was an increase in presentation with organ-confined disease. Univariate and multivariate analysis showed statistically significant impact on era specific outcome. With the improvement in techniques decrease in complications rate and increase in quality of life was noted. Conclusions : Our series spanning over decade demonstrates that RRP is viable option to offer cure to organ-confined carcinoma prostate. Further, there is evidence of stage migration and improvements in outcome in post 2002 patients. Although our series is modest in number, the success rates and outcome data matches those reported in the literature.

  15. CONFIDENCE LEVELS AND/VS. STATISTICAL HYPOTHESIS TESTING IN STATISTICAL ANALYSIS. CASE STUDY

    Directory of Open Access Journals (Sweden)

    ILEANA BRUDIU

    2009-05-01

    Full Text Available Estimated parameters with confidence intervals and testing statistical assumptions used in statistical analysis to obtain conclusions on research from a sample extracted from the population. Paper to the case study presented aims to highlight the importance of volume of sample taken in the study and how this reflects on the results obtained when using confidence intervals and testing for pregnant. If statistical testing hypotheses not only give an answer "yes" or "no" to some questions of statistical estimation using statistical confidence intervals provides more information than a test statistic, show high degree of uncertainty arising from small samples and findings build in the "marginally significant" or "almost significant (p very close to 0.05.

  16. Collecting operational event data for statistical analysis

    International Nuclear Information System (INIS)

    Atwood, C.L.

    1994-09-01

    This report gives guidance for collecting operational data to be used for statistical analysis, especially analysis of event counts. It discusses how to define the purpose of the study, the unit (system, component, etc.) to be studied, events to be counted, and demand or exposure time. Examples are given of classification systems for events in the data sources. A checklist summarizes the essential steps in data collection for statistical analysis

  17. Statistics 101 for Radiologists.

    Science.gov (United States)

    Anvari, Arash; Halpern, Elkan F; Samir, Anthony E

    2015-10-01

    Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. © RSNA, 2015.

  18. Statistics and analysis of scientific data

    CERN Document Server

    Bonamente, Massimiliano

    2013-01-01

    Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and analytical methods that are essential for the present-day analyst of scientific data. Topics covered include probability theory, distribution functions of statistics, fits to two-dimensional datasheets and parameter estimation, Monte Carlo methods and Markov chains. Equal attention is paid to the theory and its practical application, and results from classic experiments in various fields are used to illustrate the importance of statistics in the analysis of scientific data. The main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and proactive use of the material for practical applications. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is us...

  19. Method for statistical data analysis of multivariate observations

    CERN Document Server

    Gnanadesikan, R

    1997-01-01

    A practical guide for multivariate statistical techniques-- now updated and revised In recent years, innovations in computer technology and statistical methodologies have dramatically altered the landscape of multivariate data analysis. This new edition of Methods for Statistical Data Analysis of Multivariate Observations explores current multivariate concepts and techniques while retaining the same practical focus of its predecessor. It integrates methods and data-based interpretations relevant to multivariate analysis in a way that addresses real-world problems arising in many areas of inte

  20. Advances in statistical models for data analysis

    CERN Document Server

    Minerva, Tommaso; Vichi, Maurizio

    2015-01-01

    This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.

  1. Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat

    Science.gov (United States)

    Ranganathan, Priya; Pramesh, C. S.; Aggarwal, Rakesh

    2016-01-01

    In the previous article in this series on common pitfalls in statistical analysis, we looked at the difference between risk and odds. Risk, which refers to the probability of occurrence of an event or outcome, can be defined in absolute or relative terms. Understanding what these measures represent is essential for the accurate interpretation of study results. PMID:26952180

  2. Statistical models and methods for reliability and survival analysis

    CERN Document Server

    Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo

    2013-01-01

    Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical

  3. Classification, (big) data analysis and statistical learning

    CERN Document Server

    Conversano, Claudio; Vichi, Maurizio

    2018-01-01

    This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pul...

  4. Statistical hot spot analysis of reactor cores

    International Nuclear Information System (INIS)

    Schaefer, H.

    1974-05-01

    This report is an introduction into statistical hot spot analysis. After the definition of the term 'hot spot' a statistical analysis is outlined. The mathematical method is presented, especially the formula concerning the probability of no hot spots in a reactor core is evaluated. A discussion with the boundary conditions of a statistical hot spot analysis is given (technological limits, nominal situation, uncertainties). The application of the hot spot analysis to the linear power of pellets and the temperature rise in cooling channels is demonstrated with respect to the test zone of KNK II. Basic values, such as probability of no hot spots, hot spot potential, expected hot spot diagram and cumulative distribution function of hot spots, are discussed. It is shown, that the risk of hot channels can be dispersed equally over all subassemblies by an adequate choice of the nominal temperature distribution in the core

  5. The statistical analysis of anisotropies

    International Nuclear Information System (INIS)

    Webster, A.

    1977-01-01

    One of the many uses to which a radio survey may be put is an analysis of the distribution of the radio sources on the celestial sphere to find out whether they are bunched into clusters or lie in preferred regions of space. There are many methods of testing for clustering in point processes and since they are not all equally good this contribution is presented as a brief guide to what seems to be the best of them. The radio sources certainly do not show very strong clusering and may well be entirely unclustered so if a statistical method is to be useful it must be both powerful and flexible. A statistic is powerful in this context if it can efficiently distinguish a weakly clustered distribution of sources from an unclustered one, and it is flexible if it can be applied in a way which avoids mistaking defects in the survey for true peculiarities in the distribution of sources. The paper divides clustering statistics into two classes: number density statistics and log N/log S statistics. (Auth.)

  6. Basic statistical tools in research and data analysis

    Directory of Open Access Journals (Sweden)

    Zulfiqar Ali

    2016-01-01

    Full Text Available Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data. The results and inferences are precise only if proper statistical tests are used. This article will try to acquaint the reader with the basic research tools that are utilised while conducting various studies. The article covers a brief outline of the variables, an understanding of quantitative and qualitative variables and the measures of central tendency. An idea of the sample size estimation, power analysis and the statistical errors is given. Finally, there is a summary of parametric and non-parametric tests used for data analysis.

  7. Reproducible statistical analysis with multiple languages

    DEFF Research Database (Denmark)

    Lenth, Russell; Højsgaard, Søren

    2011-01-01

    This paper describes the system for making reproducible statistical analyses. differs from other systems for reproducible analysis in several ways. The two main differences are: (1) Several statistics programs can be in used in the same document. (2) Documents can be prepared using OpenOffice or ......Office or \\LaTeX. The main part of this paper is an example showing how to use and together in an OpenOffice text document. The paper also contains some practical considerations on the use of literate programming in statistics....

  8. Statistical Power in Evaluations That Investigate Effects on Multiple Outcomes: A Guide for Researchers

    Science.gov (United States)

    Porter, Kristin E.

    2018-01-01

    Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs) are statistical…

  9. A New Statistical Method to Determine the Degree of Validity of Health Economic Model Outcomes against Empirical Data.

    NARCIS (Netherlands)

    Corro Ramos, Isaac; van Voorn, George A K; Vemer, Pepijn; Feenstra, Talitha L; Al, Maiwenn J

    2017-01-01

    The validation of health economic (HE) model outcomes against empirical data is of key importance. Although statistical testing seems applicable, guidelines for the validation of HE models lack guidance on statistical validation, and actual validation efforts often present subjective judgment of

  10. A framework for the economic analysis of data collection methods for vital statistics.

    Science.gov (United States)

    Jimenez-Soto, Eliana; Hodge, Andrew; Nguyen, Kim-Huong; Dettrick, Zoe; Lopez, Alan D

    2014-01-01

    Over recent years there has been a strong movement towards the improvement of vital statistics and other types of health data that inform evidence-based policies. Collecting such data is not cost free. To date there is no systematic framework to guide investment decisions on methods of data collection for vital statistics or health information in general. We developed a framework to systematically assess the comparative costs and outcomes/benefits of the various data methods for collecting vital statistics. The proposed framework is four-pronged and utilises two major economic approaches to systematically assess the available data collection methods: cost-effectiveness analysis and efficiency analysis. We built a stylised example of a hypothetical low-income country to perform a simulation exercise in order to illustrate an application of the framework. Using simulated data, the results from the stylised example show that the rankings of the data collection methods are not affected by the use of either cost-effectiveness or efficiency analysis. However, the rankings are affected by how quantities are measured. There have been several calls for global improvements in collecting useable data, including vital statistics, from health information systems to inform public health policies. Ours is the first study that proposes a systematic framework to assist countries undertake an economic evaluation of DCMs. Despite numerous challenges, we demonstrate that a systematic assessment of outputs and costs of DCMs is not only necessary, but also feasible. The proposed framework is general enough to be easily extended to other areas of health information.

  11. Dysphagia management: an analysis of patient outcomes using VitalStim therapy compared to traditional swallow therapy.

    Science.gov (United States)

    Kiger, Mary; Brown, Catherine S; Watkins, Lynn

    2006-10-01

    This study compares the outcomes using VitalStim therapy to outcomes using traditional swallowing therapy for deglutition disorders. Twenty-two patients had an initial and a followup videofluoroscopic swallowing study or fiberoptic endoscopic evaluation of swallowing and were divided into an experimental group that received VitalStim treatments and a control group that received traditional swallowing therapy. Outcomes were analyzed for changes in oral and pharyngeal phase dysphagia severity, dietary consistency restrictions, and progression from nonoral to oral intake. Results of chi(2) analysis showed no statistically significant difference in outcomes between the experimental and control groups.

  12. Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study

    Science.gov (United States)

    2014-01-01

    Background Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. Methods 126 hypothetical trial scenarios were evaluated (126 000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Results Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Conclusions Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power. PMID:24712304

  13. Common pitfalls in statistical analysis: "P" values, statistical significance and confidence intervals

    Directory of Open Access Journals (Sweden)

    Priya Ranganathan

    2015-01-01

    Full Text Available In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ′P′ value, explain the importance of ′confidence intervals′ and clarify the importance of including both values in a paper

  14. Statistics and analysis of scientific data

    CERN Document Server

    Bonamente, Massimiliano

    2017-01-01

    The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains. Features new to this edition include: • a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets. • a new chapter on the various measures of the mean including logarithmic averages. • new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors. • a new case study and additional worked examples. • mathematical derivations and theoretical background material have been appropriately marked,to improve the readabili...

  15. Statistical evaluation of diagnostic performance topics in ROC analysis

    CERN Document Server

    Zou, Kelly H; Bandos, Andriy I; Ohno-Machado, Lucila; Rockette, Howard E

    2016-01-01

    Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are relevant to a wide variety of applications, including medical imaging, cancer research, epidemiology, and bioinformatics. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis covers areas including monotone-transformation techniques in parametric ROC analysis, ROC methods for combined and pooled biomarkers, Bayesian hierarchical transformation models, sequential designs and inferences in the ROC setting, predictive modeling, multireader ROC analysis, and free-response ROC (FROC) methodology. The book is suitable for graduate-level students and researchers in statistics, biostatistics, epidemiology, public health, biomedical engineering, radiology, medi...

  16. Bayesian Inference in Statistical Analysis

    CERN Document Server

    Box, George E P

    2011-01-01

    The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Rob

  17. Sources of Safety Data and Statistical Strategies for Design and Analysis: Clinical Trials.

    Science.gov (United States)

    Zink, Richard C; Marchenko, Olga; Sanchez-Kam, Matilde; Ma, Haijun; Jiang, Qi

    2018-03-01

    There has been an increased emphasis on the proactive and comprehensive evaluation of safety endpoints to ensure patient well-being throughout the medical product life cycle. In fact, depending on the severity of the underlying disease, it is important to plan for a comprehensive safety evaluation at the start of any development program. Statisticians should be intimately involved in this process and contribute their expertise to study design, safety data collection, analysis, reporting (including data visualization), and interpretation. In this manuscript, we review the challenges associated with the analysis of safety endpoints and describe the safety data that are available to influence the design and analysis of premarket clinical trials. We share our recommendations for the statistical and graphical methodologies necessary to appropriately analyze, report, and interpret safety outcomes, and we discuss the advantages and disadvantages of safety data obtained from clinical trials compared to other sources. Clinical trials are an important source of safety data that contribute to the totality of safety information available to generate evidence for regulators, sponsors, payers, physicians, and patients. This work is a result of the efforts of the American Statistical Association Biopharmaceutical Section Safety Working Group.

  18. Analysis of Variance: What Is Your Statistical Software Actually Doing?

    Science.gov (United States)

    Li, Jian; Lomax, Richard G.

    2011-01-01

    Users assume statistical software packages produce accurate results. In this article, the authors systematically examined Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) for 3 analysis of variance (ANOVA) designs, mixed-effects ANOVA, fixed-effects analysis of covariance (ANCOVA), and nested ANOVA. For each…

  19. Statistical Power in Evaluations That Investigate Effects on Multiple Outcomes: A Guide for Researchers

    Science.gov (United States)

    Porter, Kristin E.

    2016-01-01

    In education research and in many other fields, researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple…

  20. Comparing Visual and Statistical Analysis of Multiple Baseline Design Graphs.

    Science.gov (United States)

    Wolfe, Katie; Dickenson, Tammiee S; Miller, Bridget; McGrath, Kathleen V

    2018-04-01

    A growing number of statistical analyses are being developed for single-case research. One important factor in evaluating these methods is the extent to which each corresponds to visual analysis. Few studies have compared statistical and visual analysis, and information about more recently developed statistics is scarce. Therefore, our purpose was to evaluate the agreement between visual analysis and four statistical analyses: improvement rate difference (IRD); Tau-U; Hedges, Pustejovsky, Shadish (HPS) effect size; and between-case standardized mean difference (BC-SMD). Results indicate that IRD and BC-SMD had the strongest overall agreement with visual analysis. Although Tau-U had strong agreement with visual analysis on raw values, it had poorer agreement when those values were dichotomized to represent the presence or absence of a functional relation. Overall, visual analysis appeared to be more conservative than statistical analysis, but further research is needed to evaluate the nature of these disagreements.

  1. Sensitivity analysis and related analysis : A survey of statistical techniques

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    1995-01-01

    This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or what-if analysis, (ii) uncertainty or risk analysis, (iii) screening, (iv) validation, and (v) optimization. The main question is: when should which type of analysis be applied; which statistical

  2. Comparing Distributions of Environmental Outcomes for Regulatory Environmental Justice Analysis

    Directory of Open Access Journals (Sweden)

    Glenn Sheriff

    2011-05-01

    Full Text Available Economists have long been interested in measuring distributional impacts of policy interventions. As environmental justice (EJ emerged as an ethical issue in the 1970s, the academic literature has provided statistical analyses of the incidence and causes of various environmental outcomes as they relate to race, income, and other demographic variables. In the context of regulatory impacts, however, there is a lack of consensus regarding what information is relevant for EJ analysis, and how best to present it. This paper helps frame the discussion by suggesting a set of questions fundamental to regulatory EJ analysis, reviewing past approaches to quantifying distributional equity, and discussing the potential for adapting existing tools to the regulatory context.

  3. How to interpret the results of medical time series data analysis: Classical statistical approaches versus dynamic Bayesian network modeling.

    Science.gov (United States)

    Onisko, Agnieszka; Druzdzel, Marek J; Austin, R Marshall

    2016-01-01

    Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the Bayesian approach, argued by many of its proponents to be superior to the classical frequentist approach, is still not well-recognized in the analysis of medical data. The goal of this study is to encourage data analysts to use the Bayesian approach, such as modeling with graphical probabilistic networks, as an insightful alternative to classical statistical analysis of medical data. This paper offers a comparison of two approaches to analysis of medical time series data: (1) classical statistical approach, such as the Kaplan-Meier estimator and the Cox proportional hazards regression model, and (2) dynamic Bayesian network modeling. Our comparison is based on time series cervical cancer screening data collected at Magee-Womens Hospital, University of Pittsburgh Medical Center over 10 years. The main outcomes of our comparison are cervical cancer risk assessments produced by the three approaches. However, our analysis discusses also several aspects of the comparison, such as modeling assumptions, model building, dealing with incomplete data, individualized risk assessment, results interpretation, and model validation. Our study shows that the Bayesian approach is (1) much more flexible in terms of modeling effort, and (2) it offers an individualized risk assessment, which is more cumbersome for classical statistical approaches.

  4. Online Statistical Modeling (Regression Analysis) for Independent Responses

    Science.gov (United States)

    Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

    2017-06-01

    Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

  5. Can Family Planning Service Statistics Be Used to Track Population-Level Outcomes?

    Science.gov (United States)

    Magnani, Robert J; Ross, John; Williamson, Jessica; Weinberger, Michelle

    2018-03-21

    The need for annual family planning program tracking data under the Family Planning 2020 (FP2020) initiative has contributed to renewed interest in family planning service statistics as a potential data source for annual estimates of the modern contraceptive prevalence rate (mCPR). We sought to assess (1) how well a set of commonly recorded data elements in routine service statistics systems could, with some fairly simple adjustments, track key population-level outcome indicators, and (2) whether some data elements performed better than others. We used data from 22 countries in Africa and Asia to analyze 3 data elements collected from service statistics: (1) number of contraceptive commodities distributed to clients, (2) number of family planning service visits, and (3) number of current contraceptive users. Data quality was assessed via analysis of mean square errors, using the United Nations Population Division World Contraceptive Use annual mCPR estimates as the "gold standard." We also examined the magnitude of several components of measurement error: (1) variance, (2) level bias, and (3) slope (or trend) bias. Our results indicate modest levels of tracking error for data on commodities to clients (7%) and service visits (10%), and somewhat higher error rates for data on current users (19%). Variance and slope bias were relatively small for all data elements. Level bias was by far the largest contributor to tracking error. Paired comparisons of data elements in countries that collected at least 2 of the 3 data elements indicated a modest advantage of data on commodities to clients. None of the data elements considered was sufficiently accurate to be used to produce reliable stand-alone annual estimates of mCPR. However, the relatively low levels of variance and slope bias indicate that trends calculated from these 3 data elements can be productively used in conjunction with the Family Planning Estimation Tool (FPET) currently used to produce annual m

  6. A functional U-statistic method for association analysis of sequencing data.

    Science.gov (United States)

    Jadhav, Sneha; Tong, Xiaoran; Lu, Qing

    2017-11-01

    Although sequencing studies hold great promise for uncovering novel variants predisposing to human diseases, the high dimensionality of the sequencing data brings tremendous challenges to data analysis. Moreover, for many complex diseases (e.g., psychiatric disorders) multiple related phenotypes are collected. These phenotypes can be different measurements of an underlying disease, or measurements characterizing multiple related diseases for studying common genetic mechanism. Although jointly analyzing these phenotypes could potentially increase the power of identifying disease-associated genes, the different types of phenotypes pose challenges for association analysis. To address these challenges, we propose a nonparametric method, functional U-statistic method (FU), for multivariate analysis of sequencing data. It first constructs smooth functions from individuals' sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic. The method provides a general framework for analyzing various types of phenotypes (e.g., binary and continuous phenotypes) with unknown distributions. Fitting the genetic variants within a gene using a smoothing function also allows us to capture complexities of gene structure (e.g., linkage disequilibrium, LD), which could potentially increase the power of association analysis. Through simulations, we compared our method to the multivariate outcome score test (MOST), and found that our test attained better performance than MOST. In a real data application, we apply our method to the sequencing data from Minnesota Twin Study (MTS) and found potential associations of several nicotine receptor subunit (CHRN) genes, including CHRNB3, associated with nicotine dependence and/or alcohol dependence. © 2017 WILEY PERIODICALS, INC.

  7. Cigarette smoking impairs clinical outcomes of assisted reproduction technologies: a meta-analysis of the literature.

    Science.gov (United States)

    Budani, Maria Cristina; Fensore, Stefania; Di Marzio, Marco; Tiboni, Gian Mario

    2018-06-12

    There is convincing evidence that cigarette smoking can impair female reproductive potential. This meta-analysis updates the knowledge regarding the effects of cigarette smoking on clinical outcomes of assisted reproductive technologies (ART). Twenty-six studies were included in this meta-analysis. Results were expressed as odds ratios (OR) with 95% confidence intervals (CI) and statistical heterogeneity between the studies was evaluated with Higgins (I 2 ), Breslow (τ 2 ), Birge's ratio (H 2 ) indices and Chi-square test (χ 2 ). A P-value < 0.05 was considered statistically significant. The analysis showed a significant decrease in live birth rate per cycle for smoking patients (OR 0.59, 95% CI 0.44-0.79; P = 0.0005), a significant lower clinical pregnancy rate per cycle for smoking women (OR 0.53, 95% CI 0.41-0.68; P < 0.0001), and a significant increase in terms of spontaneous miscarriage rate (OR 2.22, 95% CI 1.10-4.48; P = 0.025) for smokers. These findings demonstrate clear negative effects of cigarette smoking on the outcome of ART programs. Copyright © 2018 Elsevier Inc. All rights reserved.

  8. Application of Ontology Technology in Health Statistic Data Analysis.

    Science.gov (United States)

    Guo, Minjiang; Hu, Hongpu; Lei, Xingyun

    2017-01-01

    Research Purpose: establish health management ontology for analysis of health statistic data. Proposed Methods: this paper established health management ontology based on the analysis of the concepts in China Health Statistics Yearbook, and used protégé to define the syntactic and semantic structure of health statistical data. six classes of top-level ontology concepts and their subclasses had been extracted and the object properties and data properties were defined to establish the construction of these classes. By ontology instantiation, we can integrate multi-source heterogeneous data and enable administrators to have an overall understanding and analysis of the health statistic data. ontology technology provides a comprehensive and unified information integration structure of the health management domain and lays a foundation for the efficient analysis of multi-source and heterogeneous health system management data and enhancement of the management efficiency.

  9. Explorations in Statistics: The Analysis of Change

    Science.gov (United States)

    Curran-Everett, Douglas; Williams, Calvin L.

    2015-01-01

    Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This tenth installment of "Explorations in Statistics" explores the analysis of a potential change in some physiological response. As researchers, we often express absolute change as percent change so we can…

  10. Common pitfalls in statistical analysis: “P” values, statistical significance and confidence intervals

    Science.gov (United States)

    Ranganathan, Priya; Pramesh, C. S.; Buyse, Marc

    2015-01-01

    In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ‘P’ value, explain the importance of ‘confidence intervals’ and clarify the importance of including both values in a paper PMID:25878958

  11. Initiating statistical process control to improve quality outcomes in colorectal surgery.

    Science.gov (United States)

    Keller, Deborah S; Stulberg, Jonah J; Lawrence, Justin K; Samia, Hoda; Delaney, Conor P

    2015-12-01

    Unexpected variations in postoperative length of stay (LOS) negatively impact resources and patient outcomes. Statistical process control (SPC) measures performance, evaluates productivity, and modifies processes for optimal performance. The goal of this study was to initiate SPC to identify LOS outliers and evaluate its feasibility to improve outcomes in colorectal surgery. Review of a prospective database identified colorectal procedures performed by a single surgeon. Patients were grouped into elective and emergent categories and then stratified by laparoscopic and open approaches. All followed a standardized enhanced recovery protocol. SPC was applied to identify outliers and evaluate causes within each group. A total of 1294 cases were analyzed--83% elective (n = 1074) and 17% emergent (n = 220). Emergent cases were 70.5% open and 29.5% laparoscopic; elective cases were 36.8% open and 63.2% laparoscopic. All groups had a wide range in LOS. LOS outliers ranged from 8.6% (elective laparoscopic) to 10.8% (emergent laparoscopic). Evaluation of outliers demonstrated patient characteristics of higher ASA scores, longer operating times, ICU requirement, and temporary nursing at discharge. Outliers had higher postoperative complication rates in elective open (57.1 vs. 20.0%) and elective lap groups (77.6 vs. 26.1%). Outliers also had higher readmission rates for emergent open (11.4 vs. 5.4%), emergent lap (14.3 vs. 9.2%), and elective lap (32.8 vs. 6.9%). Elective open outliers did not follow trends of longer LOS or higher reoperation rates. SPC is feasible and promising for improving colorectal surgery outcomes. SPC identified patient and process characteristics associated with increased LOS. SPC may allow real-time outlier identification, during quality improvement efforts, and reevaluation of outcomes after introducing process change. SPC has clinical implications for improving patient outcomes and resource utilization.

  12. TECHNIQUE OF THE STATISTICAL ANALYSIS OF INVESTMENT APPEAL OF THE REGION

    Directory of Open Access Journals (Sweden)

    А. А. Vershinina

    2014-01-01

    Full Text Available The technique of the statistical analysis of investment appeal of the region is given in scientific article for direct foreign investments. Definition of a technique of the statistical analysis is given, analysis stages reveal, the mathematico-statistical tools are considered.

  13. Statistical analysis of network data with R

    CERN Document Server

    Kolaczyk, Eric D

    2014-01-01

    Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

  14. Semiclassical analysis, Witten Laplacians, and statistical mechanis

    CERN Document Server

    Helffer, Bernard

    2002-01-01

    This important book explains how the technique of Witten Laplacians may be useful in statistical mechanics. It considers the problem of analyzing the decay of correlations, after presenting its origin in statistical mechanics. In addition, it compares the Witten Laplacian approach with other techniques, such as the transfer matrix approach and its semiclassical analysis. The author concludes by providing a complete proof of the uniform Log-Sobolev inequality. Contents: Witten Laplacians Approach; Problems in Statistical Mechanics with Discrete Spins; Laplace Integrals and Transfer Operators; S

  15. A novel statistic for genome-wide interaction analysis.

    Directory of Open Access Journals (Sweden)

    Xuesen Wu

    2010-09-01

    Full Text Available Although great progress in genome-wide association studies (GWAS has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked. The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001analysis is a valuable tool for finding remaining missing heritability unexplained by the current GWAS, and the developed novel statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies.

  16. Analysis of Pregnancy Outcomes among Interracial Couples in Korea.

    Science.gov (United States)

    Yang, Sun Young; Jung, Un Suk; Hong, Hye Ri; Hwang, Soon Young; Oh, Min Jeong; Kim, Hai Joong; Cho, Geum Joon

    2017-10-01

    Although the prevalence of interracial marriages in Korea is increasing, little is known regarding the pregnancy outcomes of interracial couples. The aim of this study was to investigate the differences in pregnancy outcomes between Korean and interracial Korean-foreign couples. Data for infants born in 2011 and 2012 were obtained from the national birth registry of the Korean Statistical Office. The couples were subdivided into Korean father-Korean mother, Korean father-foreign mother, and foreign father-Korean mother groups. Pregnancy outcomes included neonates with low birth weight ( 4,000 g). In 2010 and 2011, 888,447 Korean father-Korean mother, 36,024 Korean father-foreign mother, and 4,955 foreign father-Korean mother neonates were delivered in Korea. After adjustment for parental age, educational level, parity, gestational age at delivery, and neonatal sex, the birth weights were found to be different between groups, with the highest number of foreign father-Korean mother and lowest number of Korean father-foreign mother pregnancies. Based on multivariate logistic regression analysis, the risk of low and large birth weights was higher in the Korean father-foreign mother and foreign father-Korean mother groups, respectively, compared with that in the Korean father-Korean mother group. There are significant differences in pregnancy outcomes including birth weights between Korean and interracial Korean-foreign couples. © 2017 The Korean Academy of Medical Sciences.

  17. The effectiveness and safety of antifibrinolytics in patients with acute intracranial haemorrhage: statistical analysis plan for an individual patient data meta-analysis.

    Science.gov (United States)

    Ker, Katharine; Prieto-Merino, David; Sprigg, Nikola; Mahmood, Abda; Bath, Philip; Kang Law, Zhe; Flaherty, Katie; Roberts, Ian

    2017-01-01

    Introduction : The Antifibrinolytic Trialists Collaboration aims to increase knowledge about the effectiveness and safety of antifibrinolytic treatment by conducting individual patient data (IPD) meta-analyses of randomised trials. This article presents the statistical analysis plan for an IPD meta-analysis of the effects of antifibrinolytics for acute intracranial haemorrhage. Methods : The protocol for the IPD meta-analysis has been registered with PROSPERO (CRD42016052155). We will conduct an individual patient data meta-analysis of randomised controlled trials with 1000 patients or more assessing the effects of antifibrinolytics in acute intracranial haemorrhage. We will assess the effect on two co-primary outcomes: 1) death in hospital at end of trial follow-up, and 2) death in hospital or dependency at end of trial follow-up. The co-primary outcomes will be limited to patients treated within three hours of injury or stroke onset. We will report treatment effects using odds ratios and 95% confidence intervals. We use logistic regression models to examine how the effect of antifibrinolytics vary by time to treatment, severity of intracranial bleeding, and age. We will also examine the effect of antifibrinolytics on secondary outcomes including death, dependency, vascular occlusive events, seizures, and neurological outcomes. Secondary outcomes will be assessed in all patients irrespective of time of treatment. All analyses will be conducted on an intention-to-treat basis. Conclusions : This IPD meta-analysis will examine important clinical questions about the effects of antifibrinolytic treatment in patients with intracranial haemorrhage that cannot be answered using aggregate data. With IPD we can examine how effects vary by time to treatment, bleeding severity, and age, to gain better understanding of the balance of benefit and harms on which to base recommendations for practice.

  18. Statistical analysis of 4 types of neck whiplash injuries based on classical meridian theory.

    Science.gov (United States)

    Chen, Yemeng; Zhao, Yan; Xue, Xiaolin; Li, Hui; Wu, Xiuyan; Zhang, Qunce; Zheng, Xin; Wang, Tianfang

    2015-01-01

    As one component of the Chinese medicine meridian system, the meridian sinew (Jingjin, (see text), tendino-musculo) is specially described as being for acupuncture treatment of the musculoskeletal system because of its dynamic attributes and tender point correlations. In recent decades, the therapeutic importance of the sinew meridian has become revalued in clinical application. Based on this theory, the authors have established therapeutic strategies of acupuncture treatment in Whiplash-Associated Disorders (WAD) by categorizing four types of neck symptom presentations. The advantage of this new system is to make it much easier for the clinician to find effective acupuncture points. This study attempts to prove the significance of the proposed therapeutic strategies by analyzing data collected from a clinical survey of various WAD using non-supervised statistical methods, such as correlation analysis, factor analysis, and cluster analysis. The clinical survey data have successfully verified discrete characteristics of four neck syndromes, based upon the range of motion (ROM) and tender point location findings. A summary of the relationships among the symptoms of the four neck syndromes has shown the correlation coefficient as having a statistical significance (P < 0.01 or P < 0.05), especially with regard to ROM. Furthermore, factor and cluster analyses resulted in a total of 11 categories of general symptoms, which implies syndrome factors are more related to the Liver, as originally described in classical theory. The hypothesis of meridian sinew syndromes in WAD is clearly supported by the statistical analysis of the clinical trials. This new discovery should be beneficial in improving therapeutic outcomes.

  19. A statistical approach to plasma profile analysis

    International Nuclear Information System (INIS)

    Kardaun, O.J.W.F.; McCarthy, P.J.; Lackner, K.; Riedel, K.S.

    1990-05-01

    A general statistical approach to the parameterisation and analysis of tokamak profiles is presented. The modelling of the profile dependence on both the radius and the plasma parameters is discussed, and pertinent, classical as well as robust, methods of estimation are reviewed. Special attention is given to statistical tests for discriminating between the various models, and to the construction of confidence intervals for the parameterised profiles and the associated global quantities. The statistical approach is shown to provide a rigorous approach to the empirical testing of plasma profile invariance. (orig.)

  20. Study designs, use of statistical tests, and statistical analysis software choice in 2015: Results from two Pakistani monthly Medline indexed journals.

    Science.gov (United States)

    Shaikh, Masood Ali

    2017-09-01

    Assessment of research articles in terms of study designs used, statistical tests applied and the use of statistical analysis programmes help determine research activity profile and trends in the country. In this descriptive study, all original articles published by Journal of Pakistan Medical Association (JPMA) and Journal of the College of Physicians and Surgeons Pakistan (JCPSP), in the year 2015 were reviewed in terms of study designs used, application of statistical tests, and the use of statistical analysis programmes. JPMA and JCPSP published 192 and 128 original articles, respectively, in the year 2015. Results of this study indicate that cross-sectional study design, bivariate inferential statistical analysis entailing comparison between two variables/groups, and use of statistical software programme SPSS to be the most common study design, inferential statistical analysis, and statistical analysis software programmes, respectively. These results echo previously published assessment of these two journals for the year 2014.

  1. Statistical analysis of brake squeal noise

    Science.gov (United States)

    Oberst, S.; Lai, J. C. S.

    2011-06-01

    Despite substantial research efforts applied to the prediction of brake squeal noise since the early 20th century, the mechanisms behind its generation are still not fully understood. Squealing brakes are of significant concern to the automobile industry, mainly because of the costs associated with warranty claims. In order to remedy the problems inherent in designing quieter brakes and, therefore, to understand the mechanisms, a design of experiments study, using a noise dynamometer, was performed by a brake system manufacturer to determine the influence of geometrical parameters (namely, the number and location of slots) of brake pads on brake squeal noise. The experimental results were evaluated with a noise index and ranked for warm and cold brake stops. These data are analysed here using statistical descriptors based on population distributions, and a correlation analysis, to gain greater insight into the functional dependency between the time-averaged friction coefficient as the input and the peak sound pressure level data as the output quantity. The correlation analysis between the time-averaged friction coefficient and peak sound pressure data is performed by applying a semblance analysis and a joint recurrence quantification analysis. Linear measures are compared with complexity measures (nonlinear) based on statistics from the underlying joint recurrence plots. Results show that linear measures cannot be used to rank the noise performance of the four test pad configurations. On the other hand, the ranking of the noise performance of the test pad configurations based on the noise index agrees with that based on nonlinear measures: the higher the nonlinearity between the time-averaged friction coefficient and peak sound pressure, the worse the squeal. These results highlight the nonlinear character of brake squeal and indicate the potential of using nonlinear statistical analysis tools to analyse disc brake squeal.

  2. The Statistical Analysis of Time Series

    CERN Document Server

    Anderson, T W

    2011-01-01

    The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences George

  3. Analysis of room transfer function and reverberant signal statistics

    DEFF Research Database (Denmark)

    Georganti, Eleftheria; Mourjopoulos, John; Jacobsen, Finn

    2008-01-01

    For some time now, statistical analysis has been a valuable tool in analyzing room transfer functions (RTFs). This work examines existing statistical time-frequency models and techniques for RTF analysis (e.g., Schroeder's stochastic model and the standard deviation over frequency bands for the RTF...... magnitude and phase). RTF fractional octave smoothing, as with 1-slash 3 octave analysis, may lead to RTF simplifications that can be useful for several audio applications, like room compensation, room modeling, auralisation purposes. The aim of this work is to identify the relationship of optimal response...... and the corresponding ratio of the direct and reverberant signal. In addition, this work examines the statistical quantities for speech and audio signals prior to their reproduction within rooms and when recorded in rooms. Histograms and other statistical distributions are used to compare RTF minima of typical...

  4. Transit safety & security statistics & analysis 2002 annual report (formerly SAMIS)

    Science.gov (United States)

    2004-12-01

    The Transit Safety & Security Statistics & Analysis 2002 Annual Report (formerly SAMIS) is a compilation and analysis of mass transit accident, casualty, and crime statistics reported under the Federal Transit Administrations (FTAs) National Tr...

  5. Transit safety & security statistics & analysis 2003 annual report (formerly SAMIS)

    Science.gov (United States)

    2005-12-01

    The Transit Safety & Security Statistics & Analysis 2003 Annual Report (formerly SAMIS) is a compilation and analysis of mass transit accident, casualty, and crime statistics reported under the Federal Transit Administrations (FTAs) National Tr...

  6. Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

    Science.gov (United States)

    Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

    2014-07-21

    Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on

  7. Statistical Modelling of Wind Proles - Data Analysis and Modelling

    DEFF Research Database (Denmark)

    Jónsson, Tryggvi; Pinson, Pierre

    The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....

  8. Statistical power in parallel group point exposure studies with time-to-event outcomes: an empirical comparison of the performance of randomized controlled trials and the inverse probability of treatment weighting (IPTW) approach.

    Science.gov (United States)

    Austin, Peter C; Schuster, Tibor; Platt, Robert W

    2015-10-15

    Estimating statistical power is an important component of the design of both randomized controlled trials (RCTs) and observational studies. Methods for estimating statistical power in RCTs have been well described and can be implemented simply. In observational studies, statistical methods must be used to remove the effects of confounding that can occur due to non-random treatment assignment. Inverse probability of treatment weighting (IPTW) using the propensity score is an attractive method for estimating the effects of treatment using observational data. However, sample size and power calculations have not been adequately described for these methods. We used an extensive series of Monte Carlo simulations to compare the statistical power of an IPTW analysis of an observational study with time-to-event outcomes with that of an analysis of a similarly-structured RCT. We examined the impact of four factors on the statistical power function: number of observed events, prevalence of treatment, the marginal hazard ratio, and the strength of the treatment-selection process. We found that, on average, an IPTW analysis had lower statistical power compared to an analysis of a similarly-structured RCT. The difference in statistical power increased as the magnitude of the treatment-selection model increased. The statistical power of an IPTW analysis tended to be lower than the statistical power of a similarly-structured RCT.

  9. Statistical analysis of long term spatial and temporal trends of ...

    Indian Academy of Sciences (India)

    Statistical analysis of long term spatial and temporal trends of temperature ... CGCM3; HadCM3; modified Mann–Kendall test; statistical analysis; Sutlej basin. ... Water Resources Systems Division, National Institute of Hydrology, Roorkee 247 ...

  10. CORSSA: The Community Online Resource for Statistical Seismicity Analysis

    Science.gov (United States)

    Michael, Andrew J.; Wiemer, Stefan

    2010-01-01

    Statistical seismology is the application of rigorous statistical methods to earthquake science with the goal of improving our knowledge of how the earth works. Within statistical seismology there is a strong emphasis on the analysis of seismicity data in order to improve our scientific understanding of earthquakes and to improve the evaluation and testing of earthquake forecasts, earthquake early warning, and seismic hazards assessments. Given the societal importance of these applications, statistical seismology must be done well. Unfortunately, a lack of educational resources and available software tools make it difficult for students and new practitioners to learn about this discipline. The goal of the Community Online Resource for Statistical Seismicity Analysis (CORSSA) is to promote excellence in statistical seismology by providing the knowledge and resources necessary to understand and implement the best practices, so that the reader can apply these methods to their own research. This introduction describes the motivation for and vision of CORRSA. It also describes its structure and contents.

  11. Application of Dempster–Shafer theory in dose response outcome analysis

    International Nuclear Information System (INIS)

    Chen Wenzhou; Cui Yunfeng; Yu Yan; Galvin, James; Xiao Ying; He Yanyan; Hussaini, Yousuff M

    2012-01-01

    The Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) reviews summarize the currently available three-dimensional dose/volume/outcome data from multi-institutions and numerous articles to update and refine the normal tissue dose/volume tolerance guidelines. As pointed out in the review, the data have limitations and even some inconsistency. However, with the help of new physical and statistical techniques, the information in the review could be updated so that patient care can be continually improved. The purpose of this work is to demonstrate the application of a mathematical theory, the Dempster–Shafer theory, in dose/volume/outcome data analysis. We applied this theory to the original data obtained from published clinical studies describing dose response for radiation pneumonitis. Belief and plausibility concepts were introduced for dose response evaluation. We were also able to consider the uncertainty and inconsistency of the data from these studies with Yager's combination rule, a special methodology of Dempster–Shafer theory, to fuse the data at several specific doses. The values of belief and plausibility functions were obtained at the corresponding doses. Then we applied the Lyman–Kutcher–Burman (LKB) model to fit these values and a belief–plausibility range was obtained. This range could be considered as a probability range to assist physicians and treatment planners in determining acceptable dose–volume constraints. Finally, the parameters obtained from the LKB model fitting were compared with those in Emami and Burman's papers and those from other frequentist statistics methods. We found that Emami and Burman's parameters are within the belief–plausibility range we calculated by the Dempster–Shafer theory. (paper)

  12. Application of Dempster-Shafer theory in dose response outcome analysis

    Science.gov (United States)

    Chen, Wenzhou; Cui, Yunfeng; He, Yanyan; Yu, Yan; Galvin, James; Hussaini, Yousuff M.; Xiao, Ying

    2012-09-01

    The Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) reviews summarize the currently available three-dimensional dose/volume/outcome data from multi-institutions and numerous articles to update and refine the normal tissue dose/volume tolerance guidelines. As pointed out in the review, the data have limitations and even some inconsistency. However, with the help of new physical and statistical techniques, the information in the review could be updated so that patient care can be continually improved. The purpose of this work is to demonstrate the application of a mathematical theory, the Dempster-Shafer theory, in dose/volume/outcome data analysis. We applied this theory to the original data obtained from published clinical studies describing dose response for radiation pneumonitis. Belief and plausibility concepts were introduced for dose response evaluation. We were also able to consider the uncertainty and inconsistency of the data from these studies with Yager's combination rule, a special methodology of Dempster-Shafer theory, to fuse the data at several specific doses. The values of belief and plausibility functions were obtained at the corresponding doses. Then we applied the Lyman-Kutcher-Burman (LKB) model to fit these values and a belief-plausibility range was obtained. This range could be considered as a probability range to assist physicians and treatment planners in determining acceptable dose-volume constraints. Finally, the parameters obtained from the LKB model fitting were compared with those in Emami and Burman's papers and those from other frequentist statistics methods. We found that Emami and Burman's parameters are within the belief-plausibility range we calculated by the Dempster-Shafer theory.

  13. Multivariate statistical analysis a high-dimensional approach

    CERN Document Server

    Serdobolskii, V

    2000-01-01

    In the last few decades the accumulation of large amounts of in­ formation in numerous applications. has stimtllated an increased in­ terest in multivariate analysis. Computer technologies allow one to use multi-dimensional and multi-parametric models successfully. At the same time, an interest arose in statistical analysis with a de­ ficiency of sample data. Nevertheless, it is difficult to describe the recent state of affairs in applied multivariate methods as satisfactory. Unimprovable (dominating) statistical procedures are still unknown except for a few specific cases. The simplest problem of estimat­ ing the mean vector with minimum quadratic risk is unsolved, even for normal distributions. Commonly used standard linear multivari­ ate procedures based on the inversion of sample covariance matrices can lead to unstable results or provide no solution in dependence of data. Programs included in standard statistical packages cannot process 'multi-collinear data' and there are no theoretical recommen­ ...

  14. Meta-analysis of Clinical and Radiographic Outcomes After Arthroscopic Single-Row Versus Double-Row Rotator Cuff Repair.

    Science.gov (United States)

    Perser, Karen; Godfrey, David; Bisson, Leslie

    2011-05-01

    Double-row rotator cuff repair methods have improved biomechanical performance when compared with single-row repairs. To review clinical outcomes of single-row versus double-row rotator cuff repair with the hypothesis that double-row rotator cuff repair will result in better clinical and radiographic outcomes. Published literature from January 1980 to April 2010. Key terms included rotator cuff, prospective studies, outcomes, and suture techniques. The literature was systematically searched, and 5 level I and II studies were found comparing clinical outcomes of single-row and double-row rotator cuff repair. Coleman methodology scores were calculated for each article. Meta-analysis was performed, with treatment effect between single row and double row for clinical outcomes and with odds ratios for radiographic results. The sample size necessary to detect a given difference in clinical outcome between the 2 methods was calculated. Three level I studies had Coleman scores of 80, 74, and 81, and two level II studies had scores of 78 and 73. There were 156 patients with single-row repairs and 147 patients with double-row repairs, both with an average follow-up of 23 months (range, 12-40 months). Double-row repairs resulted in a greater treatment effect for each validated outcome measure in 4 studies, but the differences were not clinically or statistically significant (range, 0.4-2.2 points; 95% confidence interval, -0.19, 4.68 points). Double-row repairs had better radiographic results, but the differences were also not statistically significant (P = 0.13). Two studies had adequate power to detect a 10-point difference between repair methods using the Constant score, and 1 study had power to detect a 5-point difference using the UCLA (University of California, Los Angeles) score. Double-row rotator cuff repair does not show a statistically significant improvement in clinical outcome or radiographic healing with short-term follow-up.

  15. Applied multivariate statistical analysis

    CERN Document Server

    Härdle, Wolfgang Karl

    2015-01-01

    Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners.  It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.  All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.  All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...

  16. Statistical evaluation of vibration analysis techniques

    Science.gov (United States)

    Milner, G. Martin; Miller, Patrice S.

    1987-01-01

    An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.

  17. HistFitter software framework for statistical data analysis

    CERN Document Server

    Baak, M.; Côte, D.; Koutsman, A.; Lorenz, J.; Short, D.

    2015-01-01

    We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fitted to data and interpreted with statistical tests. A key innovation of HistFitter is its design, which is rooted in core analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its very fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with mu...

  18. Statistical analysis on extreme wave height

    Digital Repository Service at National Institute of Oceanography (India)

    Teena, N.V.; SanilKumar, V.; Sudheesh, K.; Sajeev, R.

    -294. • WAFO (2000) – A MATLAB toolbox for analysis of random waves and loads, Lund University, Sweden, homepage http://www.maths.lth.se/matstat/wafo/,2000. 15    Table 1: Statistical results of data and fitted distribution for cumulative distribution...

  19. Statistical Analysis of Zebrafish Locomotor Response.

    Science.gov (United States)

    Liu, Yiwen; Carmer, Robert; Zhang, Gaonan; Venkatraman, Prahatha; Brown, Skye Ashton; Pang, Chi-Pui; Zhang, Mingzhi; Ma, Ping; Leung, Yuk Fai

    2015-01-01

    Zebrafish larvae display rich locomotor behaviour upon external stimulation. The movement can be simultaneously tracked from many larvae arranged in multi-well plates. The resulting time-series locomotor data have been used to reveal new insights into neurobiology and pharmacology. However, the data are of large scale, and the corresponding locomotor behavior is affected by multiple factors. These issues pose a statistical challenge for comparing larval activities. To address this gap, this study has analyzed a visually-driven locomotor behaviour named the visual motor response (VMR) by the Hotelling's T-squared test. This test is congruent with comparing locomotor profiles from a time period. Different wild-type (WT) strains were compared using the test, which shows that they responded differently to light change at different developmental stages. The performance of this test was evaluated by a power analysis, which shows that the test was sensitive for detecting differences between experimental groups with sample numbers that were commonly used in various studies. In addition, this study investigated the effects of various factors that might affect the VMR by multivariate analysis of variance (MANOVA). The results indicate that the larval activity was generally affected by stage, light stimulus, their interaction, and location in the plate. Nonetheless, different factors affected larval activity differently over time, as indicated by a dynamical analysis of the activity at each second. Intriguingly, this analysis also shows that biological and technical repeats had negligible effect on larval activity. This finding is consistent with that from the Hotelling's T-squared test, and suggests that experimental repeats can be combined to enhance statistical power. Together, these investigations have established a statistical framework for analyzing VMR data, a framework that should be generally applicable to other locomotor data with similar structure.

  20. Statistical Analysis and Evaluation of the Depth of the Ruts on Lithuanian State Significance Roads

    Directory of Open Access Journals (Sweden)

    Erinijus Getautis

    2011-04-01

    Full Text Available The aim of this work is to gather information about the national flexible pavement roads ruts depth, to determine its statistical dispersijon index and to determine their validity for needed requirements. Analysis of scientific works of ruts apearance in the asphalt and their influence for driving is presented in this work. Dynamical models of ruts in asphalt are presented in the work as well. Experimental outcome data of rut depth dispersijon in the national highway of Lithuania Vilnius – Kaunas is prepared. Conclusions are formulated and presented. Article in Lithuanian

  1. Time Series Analysis Based on Running Mann Whitney Z Statistics

    Science.gov (United States)

    A sensitive and objective time series analysis method based on the calculation of Mann Whitney U statistics is described. This method samples data rankings over moving time windows, converts those samples to Mann-Whitney U statistics, and then normalizes the U statistics to Z statistics using Monte-...

  2. Sensitivity analysis of ranked data: from order statistics to quantiles

    NARCIS (Netherlands)

    Heidergott, B.F.; Volk-Makarewicz, W.

    2015-01-01

    In this paper we provide the mathematical theory for sensitivity analysis of order statistics of continuous random variables, where the sensitivity is with respect to a distributional parameter. Sensitivity analysis of order statistics over a finite number of observations is discussed before

  3. Rasch analysis of the Knee injury and Osteoarthritis Outcome Score (KOOS): a statistical re-evaluation

    DEFF Research Database (Denmark)

    Comins, J; Brodersen, J; Krogsgaard, M

    2008-01-01

    The knee injury and Osteoarthritis Outcome Score (KOOS), based on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), is widely used to evaluate subjective outcome in anterior cruciate ligament (ACL) reconstructed patients. However, the validity of KOOS has not been assessed...

  4. Feature-Based Statistical Analysis of Combustion Simulation Data

    Energy Technology Data Exchange (ETDEWEB)

    Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T

    2011-11-18

    We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion

  5. Statistical learning methods in high-energy and astrophysics analysis

    Energy Technology Data Exchange (ETDEWEB)

    Zimmermann, J. [Forschungszentrum Juelich GmbH, Zentrallabor fuer Elektronik, 52425 Juelich (Germany) and Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de; Kiesling, C. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)

    2004-11-21

    We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application.

  6. Statistical learning methods in high-energy and astrophysics analysis

    International Nuclear Information System (INIS)

    Zimmermann, J.; Kiesling, C.

    2004-01-01

    We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application

  7. The fuzzy approach to statistical analysis

    NARCIS (Netherlands)

    Coppi, Renato; Gil, Maria A.; Kiers, Henk A. L.

    2006-01-01

    For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. These namely are: (i) to introduce new data analysis problems in which the objective involves either fuzzy relationships or fuzzy terms;

  8. Statistical analysis applied to safety culture self-assessment

    International Nuclear Information System (INIS)

    Macedo Soares, P.P.

    2002-01-01

    Interviews and opinion surveys are instruments used to assess the safety culture in an organization as part of the Safety Culture Enhancement Programme. Specific statistical tools are used to analyse the survey results. This paper presents an example of an opinion survey with the corresponding application of the statistical analysis and the conclusions obtained. Survey validation, Frequency statistics, Kolmogorov-Smirnov non-parametric test, Student (T-test) and ANOVA means comparison tests and LSD post-hoc multiple comparison test, are discussed. (author)

  9. Foundation of statistical energy analysis in vibroacoustics

    CERN Document Server

    Le Bot, A

    2015-01-01

    This title deals with the statistical theory of sound and vibration. The foundation of statistical energy analysis is presented in great detail. In the modal approach, an introduction to random vibration with application to complex systems having a large number of modes is provided. For the wave approach, the phenomena of propagation, group speed, and energy transport are extensively discussed. Particular emphasis is given to the emergence of diffuse field, the central concept of the theory.

  10. Detailed statistical analysis plan for the target temperature management after out-of-hospital cardiac arrest trial

    DEFF Research Database (Denmark)

    Nielsen, Niklas; Winkel, Per; Cronberg, Tobias

    2013-01-01

    Animal experimental studies and previous randomized trials suggest an improvement in mortality and neurological function with temperature regulation to hypothermia after cardiac arrest. According to a systematic review, previous trials were small, had a risk of bias, evaluated select populations......, and did not treat hyperthermia in the control groups. The optimal target temperature management (TTM) strategy is not known. To prevent outcome reporting bias, selective reporting and data-driven results, we present the a priori defined detailed statistical analysis plan as an update to the previously...

  11. Statistical Analysis of Big Data on Pharmacogenomics

    Science.gov (United States)

    Fan, Jianqing; Liu, Han

    2013-01-01

    This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905

  12. HistFitter software framework for statistical data analysis

    Energy Technology Data Exchange (ETDEWEB)

    Baak, M. [CERN, Geneva (Switzerland); Besjes, G.J. [Radboud University Nijmegen, Nijmegen (Netherlands); Nikhef, Amsterdam (Netherlands); Cote, D. [University of Texas, Arlington (United States); Koutsman, A. [TRIUMF, Vancouver (Canada); Lorenz, J. [Ludwig-Maximilians-Universitaet Muenchen, Munich (Germany); Excellence Cluster Universe, Garching (Germany); Short, D. [University of Oxford, Oxford (United Kingdom)

    2015-04-15

    We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fit to data and interpreted with statistical tests. Internally HistFitter uses the statistics packages RooStats and HistFactory. A key innovation of HistFitter is its design, which is rooted in analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple models at once that describe the data, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication quality style through a simple command-line interface. (orig.)

  13. HistFitter software framework for statistical data analysis

    International Nuclear Information System (INIS)

    Baak, M.; Besjes, G.J.; Cote, D.; Koutsman, A.; Lorenz, J.; Short, D.

    2015-01-01

    We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fit to data and interpreted with statistical tests. Internally HistFitter uses the statistics packages RooStats and HistFactory. A key innovation of HistFitter is its design, which is rooted in analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple models at once that describe the data, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication quality style through a simple command-line interface. (orig.)

  14. Robust statistics and geochemical data analysis

    International Nuclear Information System (INIS)

    Di, Z.

    1987-01-01

    Advantages of robust procedures over ordinary least-squares procedures in geochemical data analysis is demonstrated using NURE data from the Hot Springs Quadrangle, South Dakota, USA. Robust principal components analysis with 5% multivariate trimming successfully guarded the analysis against perturbations by outliers and increased the number of interpretable factors. Regression with SINE estimates significantly increased the goodness-of-fit of the regression and improved the correspondence of delineated anomalies with known uranium prospects. Because of the ubiquitous existence of outliers in geochemical data, robust statistical procedures are suggested as routine procedures to replace ordinary least-squares procedures

  15. Gender-related analysis of the clinical presentation, treatment response and outcome in patients with immune thrombocytopenia.

    Science.gov (United States)

    Andrès, Emmanuel; Mecili, Mustapha; Fothergill, Helen; Zimmer, Jacques; Vogel, Thomas; Maloisel, Frédéric

    2012-09-01

    Immune thrombocytopenia (idiopathic thrombocytopenic purpura [ITP]) frequently occurs in young adults, particularly women in their third or fourth decade. The female predominance suggests that sex hormones may play a role in the different aspects of ITP. In this paper, we report a gender-related analysis of patients with ITP, specifically examining the clinical manifestations, responses to treatment and overall outcomes of the patients. We included patients with "ITP" attending the departments of onco-hematology or internal medicine B (university hospital of Strasbourg, France) between 1990 and December 2010 The gender-related analysis was retrospective. We studied in 225 consecutive cases of established ITP with a follow-up period of 1.7 to 112 months The mean age of the patients was 44 years; 156 patients were female. The analysis revealed no significant statistical differences regarding patient characteristics between the female and male groups, with the exception of the following characteristics: the bleeding score, which altered in the presence of meno- and/or metrorrhagia and hematuria in female patients (P=0.03); the presence of anemia (P=0.04); and the detection of antinuclear and/or antiphospholipid antibodies (P=0.02). During the follow-up, no statistically significant difference was found regarding outcome or treatment response in relation to gender among these 225 patients (all P>0.05). Gender does not appear to affect the manifestation of immune thrombocytopenia, the outcome or response to treatment. However, further large-scale randomized trials are needed to confirm these findings. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

  16. Using Pre-Statistical Analysis to Streamline Monitoring Assessments

    International Nuclear Information System (INIS)

    Reed, J.K.

    1999-01-01

    A variety of statistical methods exist to aid evaluation of groundwater quality and subsequent decision making in regulatory programs. These methods are applied because of large temporal and spatial extrapolations commonly applied to these data. In short, statistical conclusions often serve as a surrogate for knowledge. However, facilities with mature monitoring programs that have generated abundant data have inherently less uncertainty because of the sheer quantity of analytical results. In these cases, statistical tests can be less important, and ''expert'' data analysis should assume an important screening role.The WSRC Environmental Protection Department, working with the General Separations Area BSRI Environmental Restoration project team has developed a method for an Integrated Hydrogeological Analysis (IHA) of historical water quality data from the F and H Seepage Basins groundwater remediation project. The IHA combines common sense analytical techniques and a GIS presentation that force direct interactive evaluation of the data. The IHA can perform multiple data analysis tasks required by the RCRA permit. These include: (1) Development of a groundwater quality baseline prior to remediation startup, (2) Targeting of constituents for removal from RCRA GWPS, (3) Targeting of constituents for removal from UIC, permit, (4) Targeting of constituents for reduced, (5)Targeting of monitoring wells not producing representative samples, (6) Reduction in statistical evaluation, and (7) Identification of contamination from other facilities

  17. Meta-analysis of studies comparing oncologic outcomes of radical prostatectomy and brachytherapy for localized prostate cancer.

    Science.gov (United States)

    Cozzi, Gabriele; Musi, Gennaro; Bianchi, Roberto; Bottero, Danilo; Brescia, Antonio; Cioffi, Antonio; Cordima, Giovanni; Delor, Maurizio; Di Trapani, Ettore; Ferro, Matteo; Matei, Deliu Victor; Russo, Andrea; Mistretta, Francesco Alessandro; De Cobelli, Ottavio

    2017-11-01

    The aim of this study was to compare oncologic outcomes of radical prostatectomy (RP) with brachytherapy (BT). A literature review was conducted according to the 'Preferred reporting items for systematic reviews and meta-analyses' (PRISMA) statement. We included studies reporting comparative oncologic outcomes of RP versus BT for localized prostate cancer (PCa). From each comparative study, we extracted the study design, the number and features of the included patients, and the oncologic outcomes expressed as all-cause mortality (ACM), PCa-specific mortality (PCSM) or, when the former were unavailable, as biochemical recurrence (BCR). All of the data retrieved from the selected studies were recorded in an electronic database. Cumulative analysis was conducted using the Review Manager version 5.3 software, designed for composing Cochrane Reviews (Cochrane Collaboration, Oxford, UK). Statistical heterogeneity was tested using the Chi-square test. Our cumulative analysis did not show any significant difference in terms of BCR, ACM or PCSM rates between the RP and BT cohorts. Only three studies reported risk-stratified outcomes of intermediate- and high-risk patients, which are the most prone to treatment failure. our analysis suggested that RP and BT may have similar oncologic outcomes. However, the analysis included a limited number of studies, and most of them were retrospective, making it impossible to derive any definitive conclusion, especially for intermediate- and high-risk patients. In this scenario, appropriate urologic counseling remains of utmost importance.

  18. Conjunction analysis and propositional logic in fMRI data analysis using Bayesian statistics.

    Science.gov (United States)

    Rudert, Thomas; Lohmann, Gabriele

    2008-12-01

    To evaluate logical expressions over different effects in data analyses using the general linear model (GLM) and to evaluate logical expressions over different posterior probability maps (PPMs). In functional magnetic resonance imaging (fMRI) data analysis, the GLM was applied to estimate unknown regression parameters. Based on the GLM, Bayesian statistics can be used to determine the probability of conjunction, disjunction, implication, or any other arbitrary logical expression over different effects or contrast. For second-level inferences, PPMs from individual sessions or subjects are utilized. These PPMs can be combined to a logical expression and its probability can be computed. The methods proposed in this article are applied to data from a STROOP experiment and the methods are compared to conjunction analysis approaches for test-statistics. The combination of Bayesian statistics with propositional logic provides a new approach for data analyses in fMRI. Two different methods are introduced for propositional logic: the first for analyses using the GLM and the second for common inferences about different probability maps. The methods introduced extend the idea of conjunction analysis to a full propositional logic and adapt it from test-statistics to Bayesian statistics. The new approaches allow inferences that are not possible with known standard methods in fMRI. (c) 2008 Wiley-Liss, Inc.

  19. Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    1995-01-01

    This tutorial discusses what-if analysis and optimization of System Dynamics models. These problems are solved, using the statistical techniques of regression analysis and design of experiments (DOE). These issues are illustrated by applying the statistical techniques to a System Dynamics model for

  20. Multivariate Statistical Methods as a Tool of Financial Analysis of Farm Business

    Czech Academy of Sciences Publication Activity Database

    Novák, J.; Sůvová, H.; Vondráček, Jiří

    2002-01-01

    Roč. 48, č. 1 (2002), s. 9-12 ISSN 0139-570X Institutional research plan: AV0Z1030915 Keywords : financial analysis * financial ratios * multivariate statistical methods * correlation analysis * discriminant analysis * cluster analysis Subject RIV: BB - Applied Statistics, Operational Research

  1. Advances in Statistical Methods for Substance Abuse Prevention Research

    Science.gov (United States)

    MacKinnon, David P.; Lockwood, Chondra M.

    2010-01-01

    The paper describes advances in statistical methods for prevention research with a particular focus on substance abuse prevention. Standard analysis methods are extended to the typical research designs and characteristics of the data collected in prevention research. Prevention research often includes longitudinal measurement, clustering of data in units such as schools or clinics, missing data, and categorical as well as continuous outcome variables. Statistical methods to handle these features of prevention data are outlined. Developments in mediation, moderation, and implementation analysis allow for the extraction of more detailed information from a prevention study. Advancements in the interpretation of prevention research results include more widespread calculation of effect size and statistical power, the use of confidence intervals as well as hypothesis testing, detailed causal analysis of research findings, and meta-analysis. The increased availability of statistical software has contributed greatly to the use of new methods in prevention research. It is likely that the Internet will continue to stimulate the development and application of new methods. PMID:12940467

  2. Statistical analysis and interpretation of prenatal diagnostic imaging studies, Part 2: descriptive and inferential statistical methods.

    Science.gov (United States)

    Tuuli, Methodius G; Odibo, Anthony O

    2011-08-01

    The objective of this article is to discuss the rationale for common statistical tests used for the analysis and interpretation of prenatal diagnostic imaging studies. Examples from the literature are used to illustrate descriptive and inferential statistics. The uses and limitations of linear and logistic regression analyses are discussed in detail.

  3. Statistical analysis of environmental data

    International Nuclear Information System (INIS)

    Beauchamp, J.J.; Bowman, K.O.; Miller, F.L. Jr.

    1975-10-01

    This report summarizes the analyses of data obtained by the Radiological Hygiene Branch of the Tennessee Valley Authority from samples taken around the Browns Ferry Nuclear Plant located in Northern Alabama. The data collection was begun in 1968 and a wide variety of types of samples have been gathered on a regular basis. The statistical analysis of environmental data involving very low-levels of radioactivity is discussed. Applications of computer calculations for data processing are described

  4. Study populations and casemix: influence on analysis of postoperative outcomes.

    Science.gov (United States)

    Isbister, W H

    2000-04-01

    The importance of patient casemix as a determinant of surgical outcome is now being recognized. The present study was undertaken in order to compare the presentation and outcomes in colorectal patients managed surgically by the same surgeon, in the same way, in different settings. Colorectal outcome data from the University Department of Surgery in Wellington and the King Faisal Specialist Hospital in Riyadh were analysed in order to determine casemix differences between the two hospitals. Data relating to the type of surgery, the surgeon, the patient's disease, the operation performed and the postoperative complications were compared. Specific colorectal clinical indicators were compared for two commonly performed operations for rectal cancer: anterior resection and abdomino-perineal resection of the rectum. Wellington patients were slightly older and there were more females. Emergency surgery was more frequent in Wellington. Left hemicolectomy, sigmoid colectomy, abscess drainage and pilonidal surgery were more common in Wellington whereas abdomino-perineal resection and anterior resection of the rectum, stoma closure, fistula surgery, seton insertion, restorative proctocolectomy and ileostomy were undertaken more frequently in Riyadh. More complex anal fistulas were managed in Riyadh. Condylomata accuminata, pilonidal abscess, anorectal abscess, rectal prolapse and diverticular disease were rarely seen in Riyadh. There were more postoperative pulmonary and cardiac complications in Wellington. Patients having anterior resection of the rectum were younger in Riyadh and there were proportionally more females. There were some obvious numerical outcome differences in postoperative atelectasis, wound infection, anastomotic leak and deep vein thrombosis rates but none of these reached statistical significance except atelectasis. In Riyadh the usual male-to-female ratio of patients undergoing abdomino-perineal resection was reversed but, again, none of the numerical

  5. Highly Robust Statistical Methods in Medical Image Analysis

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2012-01-01

    Roč. 32, č. 2 (2012), s. 3-16 ISSN 0208-5216 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust statistics * classification * faces * robust image analysis * forensic science Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.208, year: 2012 http://www.ibib.waw.pl/bbe/bbefulltext/BBE_32_2_003_FT.pdf

  6. Statistical Power Analysis with Missing Data A Structural Equation Modeling Approach

    CERN Document Server

    Davey, Adam

    2009-01-01

    Statistical power analysis has revolutionized the ways in which we conduct and evaluate research.  Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This volume brings statistical power and incomplete data together under a common framework, in a way that is readily accessible to those with only an introductory familiarity with structural equation modeling.  It answers many practical questions such as: How missing data affects the statistical power in a study How much power is likely with different amounts and types

  7. Analyzing sickness absence with statistical models for survival data

    DEFF Research Database (Denmark)

    Christensen, Karl Bang; Andersen, Per Kragh; Smith-Hansen, Lars

    2007-01-01

    OBJECTIVES: Sickness absence is the outcome in many epidemiologic studies and is often based on summary measures such as the number of sickness absences per year. In this study the use of modern statistical methods was examined by making better use of the available information. Since sickness...... absence data deal with events occurring over time, the use of statistical models for survival data has been reviewed, and the use of frailty models has been proposed for the analysis of such data. METHODS: Three methods for analyzing data on sickness absences were compared using a simulation study...... involving the following: (i) Poisson regression using a single outcome variable (number of sickness absences), (ii) analysis of time to first event using the Cox proportional hazards model, and (iii) frailty models, which are random effects proportional hazards models. Data from a study of the relation...

  8. Statistical Analysis of Data for Timber Strengths

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    2003-01-01

    Statistical analyses are performed for material strength parameters from a large number of specimens of structural timber. Non-parametric statistical analysis and fits have been investigated for the following distribution types: Normal, Lognormal, 2 parameter Weibull and 3-parameter Weibull...... fits to the data available, especially if tail fits are used whereas the Log Normal distribution generally gives a poor fit and larger coefficients of variation, especially if tail fits are used. The implications on the reliability level of typical structural elements and on partial safety factors...... for timber are investigated....

  9. Numeric computation and statistical data analysis on the Java platform

    CERN Document Server

    Chekanov, Sergei V

    2016-01-01

    Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis ...

  10. Mendelian randomization analysis of a time-varying exposure for binary disease outcomes using functional data analysis methods.

    Science.gov (United States)

    Cao, Ying; Rajan, Suja S; Wei, Peng

    2016-12-01

    A Mendelian randomization (MR) analysis is performed to analyze the causal effect of an exposure variable on a disease outcome in observational studies, by using genetic variants that affect the disease outcome only through the exposure variable. This method has recently gained popularity among epidemiologists given the success of genetic association studies. Many exposure variables of interest in epidemiological studies are time varying, for example, body mass index (BMI). Although longitudinal data have been collected in many cohort studies, current MR studies only use one measurement of a time-varying exposure variable, which cannot adequately capture the long-term time-varying information. We propose using the functional principal component analysis method to recover the underlying individual trajectory of the time-varying exposure from the sparsely and irregularly observed longitudinal data, and then conduct MR analysis using the recovered curves. We further propose two MR analysis methods. The first assumes a cumulative effect of the time-varying exposure variable on the disease risk, while the second assumes a time-varying genetic effect and employs functional regression models. We focus on statistical testing for a causal effect. Our simulation studies mimicking the real data show that the proposed functional data analysis based methods incorporating longitudinal data have substantial power gains compared to standard MR analysis using only one measurement. We used the Framingham Heart Study data to demonstrate the promising performance of the new methods as well as inconsistent results produced by the standard MR analysis that relies on a single measurement of the exposure at some arbitrary time point. © 2016 WILEY PERIODICALS, INC.

  11. A Divergence Statistics Extension to VTK for Performance Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Pebay, Philippe Pierre [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bennett, Janine Camille [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-02-01

    This report follows the series of previous documents ([PT08, BPRT09b, PT09, BPT09, PT10, PB13], where we presented the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k -means, order and auto-correlative statistics engines which we developed within the Visualization Tool Kit ( VTK ) as a scalable, parallel and versatile statistics package. We now report on a new engine which we developed for the calculation of divergence statistics, a concept which we hereafter explain and whose main goal is to quantify the discrepancy, in a stasticial manner akin to measuring a distance, between an observed empirical distribution and a theoretical, "ideal" one. The ease of use of the new diverence statistics engine is illustrated by the means of C++ code snippets. Although this new engine does not yet have a parallel implementation, it has already been applied to HPC performance analysis, of which we provide an example.

  12. A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic.

    Science.gov (United States)

    Shadish, William R; Hedges, Larry V; Pustejovsky, James E; Boyajian, Jonathan G; Sullivan, Kristynn J; Andrade, Alma; Barrientos, Jeannette L

    2014-01-01

    We describe a standardised mean difference statistic (d) for single-case designs that is equivalent to the usual d in between-groups experiments. We show how it can be used to summarise treatment effects over cases within a study, to do power analyses in planning new studies and grant proposals, and to meta-analyse effects across studies of the same question. We discuss limitations of this d-statistic, and possible remedies to them. Even so, this d-statistic is better founded statistically than other effect size measures for single-case design, and unlike many general linear model approaches such as multilevel modelling or generalised additive models, it produces a standardised effect size that can be integrated over studies with different outcome measures. SPSS macros for both effect size computation and power analysis are available.

  13. Developments in statistical analysis in quantitative genetics

    DEFF Research Database (Denmark)

    Sorensen, Daniel

    2009-01-01

    of genetic means and variances, models for the analysis of categorical and count data, the statistical genetics of a model postulating that environmental variance is partly under genetic control, and a short discussion of models that incorporate massive genetic marker information. We provide an overview......A remarkable research impetus has taken place in statistical genetics since the last World Conference. This has been stimulated by breakthroughs in molecular genetics, automated data-recording devices and computer-intensive statistical methods. The latter were revolutionized by the bootstrap...... and by Markov chain Monte Carlo (McMC). In this overview a number of specific areas are chosen to illustrate the enormous flexibility that McMC has provided for fitting models and exploring features of data that were previously inaccessible. The selected areas are inferences of the trajectories over time...

  14. On the Statistical Validation of Technical Analysis

    Directory of Open Access Journals (Sweden)

    Rosane Riera Freire

    2007-06-01

    Full Text Available Technical analysis, or charting, aims on visually identifying geometrical patterns in price charts in order to antecipate price "trends". In this paper we revisit the issue of thecnical analysis validation which has been tackled in the literature without taking care for (i the presence of heterogeneity and (ii statistical dependence in the analyzed data - various agglutinated return time series from distinct financial securities. The main purpose here is to address the first cited problem by suggesting a validation methodology that also "homogenizes" the securities according to the finite dimensional probability distribution of their return series. The general steps go through the identification of the stochastic processes for the securities returns, the clustering of similar securities and, finally, the identification of presence, or absence, of informatinal content obtained from those price patterns. We illustrate the proposed methodology with a real data exercise including several securities of the global market. Our investigation shows that there is a statistically significant informational content in two out of three common patterns usually found through technical analysis, namely: triangle, rectangle and head and shoulders.

  15. Effect and safety of early weight-bearing on the outcome after open-wedge high tibial osteotomy: a systematic review and meta-analysis.

    Science.gov (United States)

    Lee, O-Sung; Ahn, Soyeon; Lee, Yong Seuk

    2017-07-01

    The purpose of this systematic review and meta-analysis was to evaluate the effectiveness and safety of early weight-bearing by comparing clinical and radiological outcomes between early and traditional delayed weight-bearing after OWHTO. A rigorous and systematic approach was used. The methodological quality was also assessed. Results that are possible to be compared in two or more than two articles were presented as forest plots. A 95% confidence interval was calculated for each effect size, and we calculated the I 2 statistic, which presents the percentage of total variation attributable to the heterogeneity among studies. The random-effects model was used to calculate the effect size. Six articles were included in the final analysis. All case groups were composed of early full weight-bearing within 2 weeks. All control groups were composed of late full weight-bearing between 6 weeks and 2 months. Pooled analysis was possible for the improvement in Lysholm score, but there was no statistically significant difference shown between groups. Other clinical results were also similar between groups. Four studies reported mechanical femorotibial angle (mFTA) and this result showed no statistically significant difference between groups in the pooled analysis. Furthermore, early weight-bearing showed more favorable results in some radiologic results (osseointegration and patellar height) and complications (thrombophlebitis and recurrence). Our analysis supports that early full weight-bearing after OWHTO using a locking plate leads to improvement in outcomes and was comparable to the delayed weight-bearing in terms of clinical and radiological outcomes. On the contrary, early weight-bearing was more favorable with respect to some radiologic parameters and complications compared with delayed weight-bearing.

  16. The significance of Sampling Design on Inference: An Analysis of Binary Outcome Model of Children’s Schooling Using Indonesian Large Multi-stage Sampling Data

    OpenAIRE

    Ekki Syamsulhakim

    2008-01-01

    This paper aims to exercise a rather recent trend in applied microeconometrics, namely the effect of sampling design on statistical inference, especially on binary outcome model. Many theoretical research in econometrics have shown the inappropriateness of applying i.i.dassumed statistical analysis on non-i.i.d data. These research have provided proofs showing that applying the iid-assumed analysis on a non-iid observations would result in an inflated standard errors which could make the esti...

  17. Sources of Safety Data and Statistical Strategies for Design and Analysis: Postmarket Surveillance.

    Science.gov (United States)

    Izem, Rima; Sanchez-Kam, Matilde; Ma, Haijun; Zink, Richard; Zhao, Yueqin

    2018-03-01

    Safety data are continuously evaluated throughout the life cycle of a medical product to accurately assess and characterize the risks associated with the product. The knowledge about a medical product's safety profile continually evolves as safety data accumulate. This paper discusses data sources and analysis considerations for safety signal detection after a medical product is approved for marketing. This manuscript is the second in a series of papers from the American Statistical Association Biopharmaceutical Section Safety Working Group. We share our recommendations for the statistical and graphical methodologies necessary to appropriately analyze, report, and interpret safety outcomes, and we discuss the advantages and disadvantages of safety data obtained from passive postmarketing surveillance systems compared to other sources. Signal detection has traditionally relied on spontaneous reporting databases that have been available worldwide for decades. However, current regulatory guidelines and ease of reporting have increased the size of these databases exponentially over the last few years. With such large databases, data-mining tools using disproportionality analysis and helpful graphics are often used to detect potential signals. Although the data sources have many limitations, analyses of these data have been successful at identifying safety signals postmarketing. Experience analyzing these dynamic data is useful in understanding the potential and limitations of analyses with new data sources such as social media, claims, or electronic medical records data.

  18. Data management and statistical analysis for environmental assessment

    International Nuclear Information System (INIS)

    Wendelberger, J.R.; McVittie, T.I.

    1995-01-01

    Data management and statistical analysis for environmental assessment are important issues on the interface of computer science and statistics. Data collection for environmental decision making can generate large quantities of various types of data. A database/GIS system developed is described which provides efficient data storage as well as visualization tools which may be integrated into the data analysis process. FIMAD is a living database and GIS system. The system has changed and developed over time to meet the needs of the Los Alamos National Laboratory Restoration Program. The system provides a repository for data which may be accessed by different individuals for different purposes. The database structure is driven by the large amount and varied types of data required for environmental assessment. The integration of the database with the GIS system provides the foundation for powerful visualization and analysis capabilities

  19. Statistical Reasoning Ability, Self-Efficacy, and Value Beliefs in a University Statistics Course

    Science.gov (United States)

    Olani, A.; Hoekstra, R.; Harskamp, E.; van der Werf, G.

    2011-01-01

    Introduction: The study investigated the degree to which students' statistical reasoning abilities, statistics self-efficacy, and perceived value of statistics improved during a reform based introductory statistics course. The study also examined whether the changes in these learning outcomes differed with respect to the students' mathematical…

  20. Compliance strategy for statistically based neutron overpower protection safety analysis methodology

    International Nuclear Information System (INIS)

    Holliday, E.; Phan, B.; Nainer, O.

    2009-01-01

    The methodology employed in the safety analysis of the slow Loss of Regulation (LOR) event in the OPG and Bruce Power CANDU reactors, referred to as Neutron Overpower Protection (NOP) analysis, is a statistically based methodology. Further enhancement to this methodology includes the use of Extreme Value Statistics (EVS) for the explicit treatment of aleatory and epistemic uncertainties, and probabilistic weighting of the initial core states. A key aspect of this enhanced NOP methodology is to demonstrate adherence, or compliance, with the analysis basis. This paper outlines a compliance strategy capable of accounting for the statistical nature of the enhanced NOP methodology. (author)

  1. A κ-generalized statistical mechanics approach to income analysis

    Science.gov (United States)

    Clementi, F.; Gallegati, M.; Kaniadakis, G.

    2009-02-01

    This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low-middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful.

  2. A κ-generalized statistical mechanics approach to income analysis

    International Nuclear Information System (INIS)

    Clementi, F; Gallegati, M; Kaniadakis, G

    2009-01-01

    This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low–middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful

  3. Normality Tests for Statistical Analysis: A Guide for Non-Statisticians

    Science.gov (United States)

    Ghasemi, Asghar; Zahediasl, Saleh

    2012-01-01

    Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. The aim of this commentary is to overview checking for normality in statistical analysis using SPSS. PMID:23843808

  4. Development of computer-assisted instruction application for statistical data analysis android platform as learning resource

    Science.gov (United States)

    Hendikawati, P.; Arifudin, R.; Zahid, M. Z.

    2018-03-01

    This study aims to design an android Statistics Data Analysis application that can be accessed through mobile devices to making it easier for users to access. The Statistics Data Analysis application includes various topics of basic statistical along with a parametric statistics data analysis application. The output of this application system is parametric statistics data analysis that can be used for students, lecturers, and users who need the results of statistical calculations quickly and easily understood. Android application development is created using Java programming language. The server programming language uses PHP with the Code Igniter framework, and the database used MySQL. The system development methodology used is the Waterfall methodology with the stages of analysis, design, coding, testing, and implementation and system maintenance. This statistical data analysis application is expected to support statistical lecturing activities and make students easier to understand the statistical analysis of mobile devices.

  5. Statistical analysis of metallicity in spiral galaxies

    Energy Technology Data Exchange (ETDEWEB)

    Galeotti, P [Consiglio Nazionale delle Ricerche, Turin (Italy). Lab. di Cosmo-Geofisica; Turin Univ. (Italy). Ist. di Fisica Generale)

    1981-04-01

    A principal component analysis of metallicity and other integral properties of 33 spiral galaxies is presented; the involved parameters are: morphological type, diameter, luminosity and metallicity. From the statistical analysis it is concluded that the sample has only two significant dimensions and additonal tests, involving different parameters, show similar results. Thus it seems that only type and luminosity are independent variables, being the other integral properties of spiral galaxies correlated with them.

  6. Statistical Analysis of Protein Ensembles

    Science.gov (United States)

    Máté, Gabriell; Heermann, Dieter

    2014-04-01

    As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.

  7. State analysis of BOP using statistical and heuristic methods

    International Nuclear Information System (INIS)

    Heo, Gyun Young; Chang, Soon Heung

    2003-01-01

    Under the deregulation environment, the performance enhancement of BOP in nuclear power plants is being highlighted. To analyze performance level of BOP, we use the performance test procedures provided from an authorized institution such as ASME. However, through plant investigation, it was proved that the requirements of the performance test procedures about the reliability and quantity of sensors was difficult to be satisfied. As a solution of this, state analysis method that are the expanded concept of signal validation, was proposed on the basis of the statistical and heuristic approaches. Authors recommended the statistical linear regression model by analyzing correlation among BOP parameters as a reference state analysis method. Its advantage is that its derivation is not heuristic, it is possible to calculate model uncertainty, and it is easy to apply to an actual plant. The error of the statistical linear regression model is below 3% under normal as well as abnormal system states. Additionally a neural network model was recommended since the statistical model is impossible to apply to the validation of all of the sensors and is sensitive to the outlier that is the signal located out of a statistical distribution. Because there are a lot of sensors need to be validated in BOP, wavelet analysis (WA) were applied as a pre-processor for the reduction of input dimension and for the enhancement of training accuracy. The outlier localization capability of WA enhanced the robustness of the neural network. The trained neural network restored the degraded signals to the values within ±3% of the true signals

  8. Precision Statistical Analysis of Images Based on Brightness Distribution

    Directory of Open Access Journals (Sweden)

    Muzhir Shaban Al-Ani

    2017-07-01

    Full Text Available Study the content of images is considered an important topic in which reasonable and accurate analysis of images are generated. Recently image analysis becomes a vital field because of huge number of images transferred via transmission media in our daily life. These crowded media with images lead to highlight in research area of image analysis. In this paper, the implemented system is passed into many steps to perform the statistical measures of standard deviation and mean values of both color and grey images. Whereas the last step of the proposed method concerns to compare the obtained results in different cases of the test phase. In this paper, the statistical parameters are implemented to characterize the content of an image and its texture. Standard deviation, mean and correlation values are used to study the intensity distribution of the tested images. Reasonable results are obtained for both standard deviation and mean value via the implementation of the system. The major issue addressed in the work is concentrated on brightness distribution via statistical measures applying different types of lighting.

  9. Fisher statistics for analysis of diffusion tensor directional information.

    Science.gov (United States)

    Hutchinson, Elizabeth B; Rutecki, Paul A; Alexander, Andrew L; Sutula, Thomas P

    2012-04-30

    A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (pstatistical comparison of tissue structural orientation. Copyright © 2012 Elsevier B.V. All rights reserved.

  10. Statistical analysis of RHIC beam position monitors performance

    Science.gov (United States)

    Calaga, R.; Tomás, R.

    2004-04-01

    A detailed statistical analysis of beam position monitors (BPM) performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.

  11. Statistical analysis of RHIC beam position monitors performance

    Directory of Open Access Journals (Sweden)

    R. Calaga

    2004-04-01

    Full Text Available A detailed statistical analysis of beam position monitors (BPM performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.

  12. Statistics Education Research in Malaysia and the Philippines: A Comparative Analysis

    Science.gov (United States)

    Reston, Enriqueta; Krishnan, Saras; Idris, Noraini

    2014-01-01

    This paper presents a comparative analysis of statistics education research in Malaysia and the Philippines by modes of dissemination, research areas, and trends. An electronic search for published research papers in the area of statistics education from 2000-2012 yielded 20 for Malaysia and 19 for the Philippines. Analysis of these papers showed…

  13. Statistical analysis of next generation sequencing data

    CERN Document Server

    Nettleton, Dan

    2014-01-01

    Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized med...

  14. Selected papers on analysis, probability, and statistics

    CERN Document Server

    Nomizu, Katsumi

    1994-01-01

    This book presents papers that originally appeared in the Japanese journal Sugaku. The papers fall into the general area of mathematical analysis as it pertains to probability and statistics, dynamical systems, differential equations and analytic function theory. Among the topics discussed are: stochastic differential equations, spectra of the Laplacian and Schrödinger operators, nonlinear partial differential equations which generate dissipative dynamical systems, fractal analysis on self-similar sets and the global structure of analytic functions.

  15. Analysis of statistical misconception in terms of statistical reasoning

    Science.gov (United States)

    Maryati, I.; Priatna, N.

    2018-05-01

    Reasoning skill is needed for everyone to face globalization era, because every person have to be able to manage and use information from all over the world which can be obtained easily. Statistical reasoning skill is the ability to collect, group, process, interpret, and draw conclusion of information. Developing this skill can be done through various levels of education. However, the skill is low because many people assume that statistics is just the ability to count and using formulas and so do students. Students still have negative attitude toward course which is related to research. The purpose of this research is analyzing students’ misconception in descriptive statistic course toward the statistical reasoning skill. The observation was done by analyzing the misconception test result and statistical reasoning skill test; observing the students’ misconception effect toward statistical reasoning skill. The sample of this research was 32 students of math education department who had taken descriptive statistic course. The mean value of misconception test was 49,7 and standard deviation was 10,6 whereas the mean value of statistical reasoning skill test was 51,8 and standard deviation was 8,5. If the minimal value is 65 to state the standard achievement of a course competence, students’ mean value is lower than the standard competence. The result of students’ misconception study emphasized on which sub discussion that should be considered. Based on the assessment result, it was found that students’ misconception happen on this: 1) writing mathematical sentence and symbol well, 2) understanding basic definitions, 3) determining concept that will be used in solving problem. In statistical reasoning skill, the assessment was done to measure reasoning from: 1) data, 2) representation, 3) statistic format, 4) probability, 5) sample, and 6) association.

  16. Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review.

    Science.gov (United States)

    Weir, Christopher J; Butcher, Isabella; Assi, Valentina; Lewis, Stephanie C; Murray, Gordon D; Langhorne, Peter; Brady, Marian C

    2018-03-07

    Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis. We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios. For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally

  17. Outcome and Perspectives from the First IAEA International Technical Meeting on Statistical Methodologies for Safeguards

    International Nuclear Information System (INIS)

    Norman, C.; Binner, R.; Peter, N. J.; Wuester, J.; Zhao, K.; Krieger, T.; Walczak-Typke, A.C.; Richet, S.; Portaix, C.G.; Martin, K.; Bonner, E.R.

    2015-01-01

    Statistical and probabilistic methodologies have always played a fundamental role in the field of safeguards. In-field inspection approaches are based on sampling algorithms and random verification schemes designed to achieve a designed detection probability for defects of interest (e.g., missing material, indicators of tampering with containment and other equipment, changes of design). In addition, the evaluation of verification data with a view to drawing soundly based safeguards conclusions rests on the application of various advanced statistical methodologies. The considerable progress of information technology in the field of data processing and computational capabilities as well as the evolution of safeguards concepts and the steep increase in the volume of verification data in the last decades call for the review and modernization of safeguards statistical methodologies, not only to improve the efficiency of the analytical processes but also to address new statistical and probabilistic questions. Modern computer-intensive approaches are also needed to fully exploit the large body of verification data collected over the years in the increasing number and diversifying types of nuclear fuel cycle facilities in the world. The first biennial IAEA International Technical Meeting on Statistical Methodologies for Safeguards was held in Vienna from the 16 to 18 October 2013. Recommendations and a working plan were drafted which identify and chart necessary steps to review, harmonize, update and consolidate statistical methodologies for safeguards. Three major problem spaces were identified: Random Verification Schemes, Estimation of Uncertainties and Statistical Evaluation of Safeguards Verification Data for which a detailed list of objectives and actions to be taken were established. Since the meeting, considerable progress was made to meet these objectives. The actions undertaken and their outcome are presented in this paper. (author)

  18. Comparative analysis of positive and negative attitudes toward statistics

    Science.gov (United States)

    Ghulami, Hassan Rahnaward; Ab Hamid, Mohd Rashid; Zakaria, Roslinazairimah

    2015-02-01

    Many statistics lecturers and statistics education researchers are interested to know the perception of their students' attitudes toward statistics during the statistics course. In statistics course, positive attitude toward statistics is a vital because it will be encourage students to get interested in the statistics course and in order to master the core content of the subject matters under study. Although, students who have negative attitudes toward statistics they will feel depressed especially in the given group assignment, at risk for failure, are often highly emotional, and could not move forward. Therefore, this study investigates the students' attitude towards learning statistics. Six latent constructs have been the measurement of students' attitudes toward learning statistic such as affect, cognitive competence, value, difficulty, interest, and effort. The questionnaire was adopted and adapted from the reliable and validate instrument of Survey of Attitudes towards Statistics (SATS). This study is conducted among engineering undergraduate engineering students in the university Malaysia Pahang (UMP). The respondents consist of students who were taking the applied statistics course from different faculties. From the analysis, it is found that the questionnaire is acceptable and the relationships among the constructs has been proposed and investigated. In this case, students show full effort to master the statistics course, feel statistics course enjoyable, have confidence that they have intellectual capacity, and they have more positive attitudes then negative attitudes towards statistics learning. In conclusion in terms of affect, cognitive competence, value, interest and effort construct the positive attitude towards statistics was mostly exhibited. While negative attitudes mostly exhibited by difficulty construct.

  19. The effectiveness and safety of antifibrinolytics in patients with acute intracranial haemorrhage: statistical analysis plan for an individual patient data meta-analysis [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Katharine Ker

    2018-02-01

    Full Text Available Introduction: The Antifibrinolytic Trialists Collaboration aims to increase knowledge about the effectiveness and safety of antifibrinolytic treatment by conducting individual patient data (IPD meta-analyses of randomised trials. This article presents the statistical analysis plan for an IPD meta-analysis of the effects of antifibrinolytics for acute intracranial haemorrhage. Methods: The protocol for the IPD meta-analysis has been registered with PROSPERO (CRD42016052155. We will conduct an individual patient data meta-analysis of randomised controlled trials with 1000 patients or more assessing the effects of antifibrinolytics in acute intracranial haemorrhage. We will assess the effect on two co-primary outcomes: 1 Death in hospital within 30 days of randomisation, and 2 Death  or dependency at final follow-up within 90 days of randomisation. The co-primary outcomes will be limited to patients treated within three hours of injury or stroke onset. We will report treatment effects using odds ratios and 95% confidence intervals. We use logistic regression models to examine how the effect of antifibrinolytics vary by time to treatment, severity of intracranial bleeding, and age. We will also examine the effect of antifibrinolytics on secondary outcomes including death, dependency, vascular occlusive events, seizures, and neurological outcomes. Secondary outcomes will be assessed in all patients irrespective of time of treatment. All analyses will be conducted on an intention-to-treat basis. Conclusions: This IPD meta-analysis will examine important clinical questions about the effects of antifibrinolytic treatment in patients with intracranial haemorrhage that cannot be answered using aggregate data. With IPD we can examine how effects vary by time to treatment, bleeding severity, and age, to gain better understanding of the balance of benefit and harms on which to base recommendations for practice.

  20. The effectiveness and safety of antifibrinolytics in patients with acute intracranial haemorrhage: statistical analysis plan for an individual patient data meta-analysis [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Katharine Ker

    2017-12-01

    Full Text Available Introduction: The Antifibrinolytic Trialists Collaboration aims to increase knowledge about the effectiveness and safety of antifibrinolytic treatment by conducting individual patient data (IPD meta-analyses of randomised trials. This article presents the statistical analysis plan for an IPD meta-analysis of the effects of antifibrinolytics for acute intracranial haemorrhage. Methods: The protocol for the IPD meta-analysis has been registered with PROSPERO (CRD42016052155. We will conduct an individual patient data meta-analysis of randomised controlled trials with 1000 patients or more assessing the effects of antifibrinolytics in acute intracranial haemorrhage. We will assess the effect on two co-primary outcomes: 1 death in hospital at end of trial follow-up, and 2 death in hospital or dependency at end of trial follow-up. The co-primary outcomes will be limited to patients treated within three hours of injury or stroke onset. We will report treatment effects using odds ratios and 95% confidence intervals. We use logistic regression models to examine how the effect of antifibrinolytics vary by time to treatment, severity of intracranial bleeding, and age. We will also examine the effect of antifibrinolytics on secondary outcomes including death, dependency, vascular occlusive events, seizures, and neurological outcomes. Secondary outcomes will be assessed in all patients irrespective of time of treatment. All analyses will be conducted on an intention-to-treat basis. Conclusions: This IPD meta-analysis will examine important clinical questions about the effects of antifibrinolytic treatment in patients with intracranial haemorrhage that cannot be answered using aggregate data. With IPD we can examine how effects vary by time to treatment, bleeding severity, and age, to gain better understanding of the balance of benefit and harms on which to base recommendations for practice.

  1. Vapor Pressure Data Analysis and Statistics

    Science.gov (United States)

    2016-12-01

    near 8, 2000, and 200, respectively. The A (or a) value is directly related to vapor pressure and will be greater for high vapor pressure materials...1, (10) where n is the number of data points, Yi is the natural logarithm of the i th experimental vapor pressure value, and Xi is the...VAPOR PRESSURE DATA ANALYSIS AND STATISTICS ECBC-TR-1422 Ann Brozena RESEARCH AND TECHNOLOGY DIRECTORATE

  2. Statistical analysis of planktic foraminifera of the surface Continental ...

    African Journals Online (AJOL)

    Planktic foraminiferal assemblage recorded from selected samples obtained from shallow continental shelf sediments off southwestern Nigeria were subjected to statistical analysis. The Principal Component Analysis (PCA) was used to determine variants of planktic parameters. Values obtained for these parameters were ...

  3. Imaging mass spectrometry statistical analysis.

    Science.gov (United States)

    Jones, Emrys A; Deininger, Sören-Oliver; Hogendoorn, Pancras C W; Deelder, André M; McDonnell, Liam A

    2012-08-30

    Imaging mass spectrometry is increasingly used to identify new candidate biomarkers. This clinical application of imaging mass spectrometry is highly multidisciplinary: expertise in mass spectrometry is necessary to acquire high quality data, histology is required to accurately label the origin of each pixel's mass spectrum, disease biology is necessary to understand the potential meaning of the imaging mass spectrometry results, and statistics to assess the confidence of any findings. Imaging mass spectrometry data analysis is further complicated because of the unique nature of the data (within the mass spectrometry field); several of the assumptions implicit in the analysis of LC-MS/profiling datasets are not applicable to imaging. The very large size of imaging datasets and the reporting of many data analysis routines, combined with inadequate training and accessible reviews, have exacerbated this problem. In this paper we provide an accessible review of the nature of imaging data and the different strategies by which the data may be analyzed. Particular attention is paid to the assumptions of the data analysis routines to ensure that the reader is apprised of their correct usage in imaging mass spectrometry research. Copyright © 2012 Elsevier B.V. All rights reserved.

  4. Applied Behavior Analysis and Statistical Process Control?

    Science.gov (United States)

    Hopkins, B. L.

    1995-01-01

    Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…

  5. Histoplasmosis Statistics

    Science.gov (United States)

    ... Testing Treatment & Outcomes Health Professionals Statistics More Resources Candidiasis Candida infections of the mouth, throat, and esophagus Vaginal candidiasis Invasive candidiasis Definition Symptoms Risk & Prevention Sources Diagnosis ...

  6. Comparison of statistical and clinical predictions of functional outcome after ischemic stroke.

    Directory of Open Access Journals (Sweden)

    Douglas D Thompson

    Full Text Available To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor's clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs.A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS. Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3 using five previously described CPMs. The specificity of a doctor's informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97 and similar to CPMs (range 0.94 to 0.96; however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49 and clinical prediction models (range 0.38 to 0.45 was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76 and CPMs (range 0.69 to 0.75. No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.

  7. Feasibility, Process, and Outcomes of Cardiovascular Clinical Trial Data Sharing: A Reproduction Analysis of the SMART-AF Trial.

    Science.gov (United States)

    Gay, Hawkins C; Baldridge, Abigail S; Huffman, Mark D

    2017-12-01

    Data sharing is as an expanding initiative for enhancing trust in the clinical research enterprise. To evaluate the feasibility, process, and outcomes of a reproduction analysis of the THERMOCOOL SMARTTOUCH Catheter for the Treatment of Symptomatic Paroxysmal Atrial Fibrillation (SMART-AF) trial using shared clinical trial data. A reproduction analysis of the SMART-AF trial was performed using the data sets, data dictionary, case report file, and statistical analysis plan from the original trial accessed through the Yale Open Data Access Project using the SAS Clinical Trials Data Transparency platform. SMART-AF was a multicenter, single-arm trial evaluating the effectiveness and safety of an irrigated, contact force-sensing catheter for ablation of drug refractory, symptomatic paroxysmal atrial fibrillation in 172 participants recruited from 21 sites between June 2011 and December 2011. Analysis of the data was conducted between December 2016 and April 2017. Effectiveness outcomes included freedom from atrial arrhythmias after ablation and proportion of participants without any arrhythmia recurrence over the 12 months of follow-up after a 3-month blanking period. Safety outcomes included major adverse device- or procedure-related events. The SMART AF trial participants' mean age was 58.7 (10.8) years, and 72% were men. The time from initial proposal submission to final analysis was 11 months. Freedom from atrial arrhythmias at 12 months postprocedure was similar compared with the primary study report (74.0%; 95% CI, 66.0-82.0 vs 76.4%; 95% CI, 68.7-84.1). The reproduction analysis success rate was higher than the primary study report (65.8%; 95% CI 56.5-74.2 vs 75.6%; 95% CI, 67.2-82.5). Adverse events were minimal and similar between the 2 analyses, but contact force range or regression models could not be reproduced. The feasibility of a reproduction analysis of the SMART-AF trial was demonstrated through an academic data-sharing platform. Data sharing can be

  8. Statistical analysis of JET disruptions

    International Nuclear Information System (INIS)

    Tanga, A.; Johnson, M.F.

    1991-07-01

    In the operation of JET and of any tokamak many discharges are terminated by a major disruption. The disruptive termination of a discharge is usually an unwanted event which may cause damage to the structure of the vessel. In a reactor disruptions are potentially a very serious problem, hence the importance of studying them and devising methods to avoid disruptions. Statistical information has been collected about the disruptions which have occurred at JET over a long span of operations. The analysis is focused on the operational aspects of the disruptions rather than on the underlining physics. (Author)

  9. Simulation Experiments in Practice : Statistical Design and Regression Analysis

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2007-01-01

    In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. Statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic

  10. Using the Statistical Indicators for the General Insurances Activity

    Directory of Open Access Journals (Sweden)

    Ion Partachi

    2007-04-01

    Full Text Available The statistics of the general insurances activity is largely used in the actuarial calculations. The actuarial analysis are achieved exclusively on the basis of primary and derived indicators, which are drawn up by various statistical methods. The statistical indicators which are used in this respect are obtained on the basis of the factors and conditions allowing the compensation cases to occur.The actuarial analysis is performed over the time as well, by using the chronological which allow the decomposition of the phenomenon being studied by its factors of influence.In this article, after briefly presenting a number of point of view regarding the utilization of the statistical indicators in the actuarial analysis, we have analyzed, successively, a series of issues, such as: the statistical indicators as regards the general insurances fund forming, expressed in physical and value units, or as absolute, relative and average volumes; the statistical indicators of the utilization of the general insurances funds (with the same diversified form of expression and the statistical indicators of the outcomes of the general insurances activity.A particular accent went to the underlying of certain methodological aspects regarding the calculation of the above mentioned indicators, emphasizing certain particular characteristics concerning their utilization in the frame of the actuarial analysis.The article is stressing the clarification of the fact that these indicators are used in the actuarial analysis as a real system. The respective proportions are enumerated, by underlying the concrete possibilities of computation, which secure the possibility of performing the necessary analysis involved by a decisional process.

  11. Statistical analysis of the Ft. Calhoun reactor coolant pump system

    International Nuclear Information System (INIS)

    Patel, Bimal; Heising, C.D.

    1997-01-01

    In engineering science, statistical quality control techniques have traditionally been applied to control manufacturing processes. An application to commercial nuclear power plant maintenance and control is presented that can greatly improve plant safety. As a demonstration of such an approach, a specific system is analyzed: the reactor coolant pumps (RCPs) of the Ft. Calhoun nuclear power plant. This research uses capability analysis, Shewhart X-bar, R charts, canonical correlation methods, and design of experiments to analyze the process for the state of statistical control. The results obtained show that six out of ten parameters are under control specification limits and four parameters are not in the state of statistical control. The analysis shows that statistical process control methods can be applied as an early warning system capable of identifying significant equipment problems well in advance of traditional control room alarm indicators. Such a system would provide operators with ample time to respond to possible emergency situations and thus improve plant safety and reliability. (Author)

  12. Research and Development of Statistical Analysis Software System of Maize Seedling Experiment

    OpenAIRE

    Hui Cao

    2014-01-01

    In this study, software engineer measures were used to develop a set of software system for maize seedling experiments statistics and analysis works. During development works, B/S structure software design method was used and a set of statistics indicators for maize seedling evaluation were established. The experiments results indicated that this set of software system could finish quality statistics and analysis for maize seedling very well. The development of this software system explored a...

  13. Statistical approaches to assessing single and multiple outcome measures in dry eye therapy and diagnosis.

    Science.gov (United States)

    Tomlinson, Alan; Hair, Mario; McFadyen, Angus

    2013-10-01

    Dry eye is a multifactorial disease which would require a broad spectrum of test measures in the monitoring of its treatment and diagnosis. However, studies have typically reported improvements in individual measures with treatment. Alternative approaches involve multiple, combined outcomes being assessed by different statistical analyses. In order to assess the effect of various statistical approaches to the use of single and combined test measures in dry eye, this review reanalyzed measures from two previous studies (osmolarity, evaporation, tear turnover rate, and lipid film quality). These analyses assessed the measures as single variables within groups, pre- and post-intervention with a lubricant supplement, by creating combinations of these variables and by validating these combinations with the combined sample of data from all groups of dry eye subjects. The effectiveness of single measures and combinations in diagnosis of dry eye was also considered. Copyright © 2013. Published by Elsevier Inc.

  14. Statistical trend analysis methods for temporal phenomena

    Energy Technology Data Exchange (ETDEWEB)

    Lehtinen, E.; Pulkkinen, U. [VTT Automation, (Finland); Poern, K. [Poern Consulting, Nykoeping (Sweden)

    1997-04-01

    We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods. 14 refs, 10 figs.

  15. Statistical trend analysis methods for temporal phenomena

    International Nuclear Information System (INIS)

    Lehtinen, E.; Pulkkinen, U.; Poern, K.

    1997-04-01

    We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods

  16. StOCNET : Software for the statistical analysis of social networks

    NARCIS (Netherlands)

    Huisman, M.; van Duijn, M.A.J.

    2003-01-01

    StOCNET3 is an open software system in a Windows environment for the advanced statistical analysis of social networks. It provides a platform to make a number of recently developed and therefore not (yet) standard statistical methods available to a wider audience. A flexible user interface utilizing

  17. AutoBayes: A System for Generating Data Analysis Programs from Statistical Models

    OpenAIRE

    Fischer, Bernd; Schumann, Johann

    2003-01-01

    Data analysis is an important scientific task which is required whenever information needs to be extracted from raw data. Statistical approaches to data analysis, which use methods from probability theory and numerical analysis, are well-founded but dificult to implement: the development of a statistical data analysis program for any given application is time-consuming and requires substantial knowledge and experience in several areas. In this paper, we describe AutoBayes, a program synthesis...

  18. Network similarity and statistical analysis of earthquake seismic data

    OpenAIRE

    Deyasi, Krishanu; Chakraborty, Abhijit; Banerjee, Anirban

    2016-01-01

    We study the structural similarity of earthquake networks constructed from seismic catalogs of different geographical regions. A hierarchical clustering of underlying undirected earthquake networks is shown using Jensen-Shannon divergence in graph spectra. The directed nature of links indicates that each earthquake network is strongly connected, which motivates us to study the directed version statistically. Our statistical analysis of each earthquake region identifies the hub regions. We cal...

  19. Statistical analysis and interpolation of compositional data in materials science.

    Science.gov (United States)

    Pesenson, Misha Z; Suram, Santosh K; Gregoire, John M

    2015-02-09

    Compositional data are ubiquitous in chemistry and materials science: analysis of elements in multicomponent systems, combinatorial problems, etc., lead to data that are non-negative and sum to a constant (for example, atomic concentrations). The constant sum constraint restricts the sampling space to a simplex instead of the usual Euclidean space. Since statistical measures such as mean and standard deviation are defined for the Euclidean space, traditional correlation studies, multivariate analysis, and hypothesis testing may lead to erroneous dependencies and incorrect inferences when applied to compositional data. Furthermore, composition measurements that are used for data analytics may not include all of the elements contained in the material; that is, the measurements may be subcompositions of a higher-dimensional parent composition. Physically meaningful statistical analysis must yield results that are invariant under the number of composition elements, requiring the application of specialized statistical tools. We present specifics and subtleties of compositional data processing through discussion of illustrative examples. We introduce basic concepts, terminology, and methods required for the analysis of compositional data and utilize them for the spatial interpolation of composition in a sputtered thin film. The results demonstrate the importance of this mathematical framework for compositional data analysis (CDA) in the fields of materials science and chemistry.

  20. An Application of Multivariate Statistical Analysis for Query-Driven Visualization

    Energy Technology Data Exchange (ETDEWEB)

    Gosink, Luke J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Garth, Christoph [Univ. of California, Davis, CA (United States); Anderson, John C. [Univ. of California, Davis, CA (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Joy, Kenneth I. [Univ. of California, Davis, CA (United States)

    2011-03-01

    Driven by the ability to generate ever-larger, increasingly complex data, there is an urgent need in the scientific community for scalable analysis methods that can rapidly identify salient trends in scientific data. Query-Driven Visualization (QDV) strategies are among the small subset of techniques that can address both large and highly complex datasets. This paper extends the utility of QDV strategies with a statistics-based framework that integrates non-parametric distribution estimation techniques with a new segmentation strategy to visually identify statistically significant trends and features within the solution space of a query. In this framework, query distribution estimates help users to interactively explore their query's solution and visually identify the regions where the combined behavior of constrained variables is most important, statistically, to their inquiry. Our new segmentation strategy extends the distribution estimation analysis by visually conveying the individual importance of each variable to these regions of high statistical significance. We demonstrate the analysis benefits these two strategies provide and show how they may be used to facilitate the refinement of constraints over variables expressed in a user's query. We apply our method to datasets from two different scientific domains to demonstrate its broad applicability.

  1. Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

    Energy Technology Data Exchange (ETDEWEB)

    Lalonde, Michel, E-mail: mlalonde15@rogers.com; Wassenaar, Richard [Department of Physics, Carleton University, Ottawa, Ontario K1S 5B6 (Canada); Wells, R. Glenn; Birnie, David; Ruddy, Terrence D. [Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario K1Y 4W7 (Canada)

    2014-07-15

    Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster

  2. Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

    International Nuclear Information System (INIS)

    Lalonde, Michel; Wassenaar, Richard; Wells, R. Glenn; Birnie, David; Ruddy, Terrence D.

    2014-01-01

    Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster

  3. Clinical Outcomes of Gap Balancing vs Measured Resection in Total Knee Arthroplasty: A Systematic Review and Meta-Analysis Involving 2259 Subjects.

    Science.gov (United States)

    Li, Shuxiang; Luo, Xiaomin; Wang, Peng; Sun, Han; Wang, Kun; Sun, Xiaoliang

    2018-03-17

    The argument on the clinical effects between gap balancing (GB) and measured resection (MR) in total knee arthroplasty remains to be resolved. A systematic review and meta-analysis was performed to investigate which technique in total knee arthroplasty has better clinical effect. A total of 20 studies involving 2259 cases were included in the meta-analysis. The primary outcome measure was Knee Society Score (KSS), whereas the secondary outcomes included other function assessment systems (eg, range of motion, Western Ontario and McMaster University Osteoarthritis Index), radiological outcomes (eg, femoral component rotation, total outliers), revision rate, complications (eg, infection, loosening, instability), and surgical time. The GB technique was associated with statistically significant increases in the primary outcomes of KSS-function in 1 year. However, a mean difference of 2.12 points was below the minimal clinically important difference of 6 points. No differences were found in the analyses of KSS-knee and KSS-function in any other follow-up periods. Secondary outcome assessments showed significant decreased surgical time (mean difference, 16.18; P < .00001) for MR. Although statistically significant difference in favor of GB was identified in total outliers (risk ratio, 1.72, P = .0004), the 2 techniques were comparable in range of motion, Western Ontario and McMaster University Osteoarthritis Index, femoral component rotation, complications, and revision rate. We conclude that both techniques can result in equivalent results when done properly, and each surgeon must understand the strengths and weaknesses of each technique. Copyright © 2018 Elsevier Inc. All rights reserved.

  4. Organizational downsizing and age discrimination litigation: the influence of personnel practices and statistical evidence on litigation outcomes.

    Science.gov (United States)

    Wingate, Peter H; Thornton, George C; McIntyre, Kelly S; Frame, Jennifer H

    2003-02-01

    The present study examined relationships between reduction-in-force (RIF) personnel practices, presentation of statistical evidence, and litigation outcomes. Policy capturing methods were utilized to analyze the components of 115 federal district court opinions involving age discrimination disparate treatment allegations and organizational downsizing. Univariate analyses revealed meaningful links between RIF personnel practices, use of statistical evidence, and judicial verdict. The defendant organization was awarded summary judgment in 73% of the claims included in the study. Judicial decisions in favor of the defendant organization were found to be significantly related to such variables as formal performance appraisal systems, termination decision review within the organization, methods of employee assessment and selection for termination, and the presence of a concrete layoff policy. The use of statistical evidence in ADEA disparate treatment litigation was investigated and found to be a potentially persuasive type of indirect evidence. Legal, personnel, and evidentiary ramifications are reviewed, and a framework of downsizing mechanics emphasizing legal defensibility is presented.

  5. Explorations in Statistics: The Analysis of Ratios and Normalized Data

    Science.gov (United States)

    Curran-Everett, Douglas

    2013-01-01

    Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This ninth installment of "Explorations in Statistics" explores the analysis of ratios and normalized--or standardized--data. As researchers, we compute a ratio--a numerator divided by a denominator--to compute a…

  6. Correlation between histological outcome and surgical cartilage repair technique in the knee: A meta-analysis.

    Science.gov (United States)

    DiBartola, Alex C; Everhart, Joshua S; Magnussen, Robert A; Carey, James L; Brophy, Robert H; Schmitt, Laura C; Flanigan, David C

    2016-06-01

    Compare histological outcomes after microfracture (MF), autologous chondrocyte implantation (ACI), and osteochondral autograft transfer (OATS). Literature review using PubMed MEDLINE, SCOPUS, Cumulative Index for Nursing and Allied Health Literature (CINAHL), and Cochrane Collaboration Library. Inclusion criteria limited to English language studies International Cartilage Repair Society (ICRS) grading criteria for cartilage analysis after ACI (autologous chondrocyte implantation), MF (microfracture), or OATS (osteochondral autografting) repair techniques. Thirty-three studies investigating 1511 patients were identified. Thirty evaluated ACI or one of its subtypes, six evaluated MF, and seven evaluated OATS. There was no evidence of publication bias (Begg's p=0.48). No statistically significant correlation was found between percent change in clinical outcome and percent biopsies showing ICRS Excellent scores (R(2)=0.05, p=0.38). Percent change in clinical outcome and percent of biopsies showing only hyaline cartilage were significantly associated (R(2)=0.24, p=0.024). Mean lesion size and histological outcome were not correlated based either on percent ICRS Excellent (R(2)=0.03, p=0.50) or percent hyaline cartilage only (R(2)=0.01, p=0.67). Most common lesion location and histological outcome were not correlated based either on percent ICRS Excellent (R(2)=0.03, p=0.50) or percent hyaline cartilage only (R(2)=0.01, p=0.67). Microfracture has poorer histologic outcomes than other cartilage repair techniques. OATS repairs primarily are comprised of hyaline cartilage, followed closely by cell-based techniques, but no significant difference was found cartilage quality using ICRS grading criteria among OATS, ACI-C, MACI, and ACI-P. IV, meta-analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Statistical Energy Analysis (SEA) and Energy Finite Element Analysis (EFEA) Predictions for a Floor-Equipped Composite Cylinder

    Science.gov (United States)

    Grosveld, Ferdinand W.; Schiller, Noah H.; Cabell, Randolph H.

    2011-01-01

    Comet Enflow is a commercially available, high frequency vibroacoustic analysis software founded on Energy Finite Element Analysis (EFEA) and Energy Boundary Element Analysis (EBEA). Energy Finite Element Analysis (EFEA) was validated on a floor-equipped composite cylinder by comparing EFEA vibroacoustic response predictions with Statistical Energy Analysis (SEA) and experimental results. Statistical Energy Analysis (SEA) predictions were made using the commercial software program VA One 2009 from ESI Group. The frequency region of interest for this study covers the one-third octave bands with center frequencies from 100 Hz to 4000 Hz.

  8. Simulation Experiments in Practice : Statistical Design and Regression Analysis

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2007-01-01

    In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is

  9. Statistical analysis plan for the Pneumatic CompREssion for PreVENting Venous Thromboembolism (PREVENT) trial: a study protocol for a randomized controlled trial.

    Science.gov (United States)

    Arabi, Yaseen; Al-Hameed, Fahad; Burns, Karen E A; Mehta, Sangeeta; Alsolamy, Sami; Almaani, Mohammed; Mandourah, Yasser; Almekhlafi, Ghaleb A; Al Bshabshe, Ali; Finfer, Simon; Alshahrani, Mohammed; Khalid, Imran; Mehta, Yatin; Gaur, Atul; Hawa, Hassan; Buscher, Hergen; Arshad, Zia; Lababidi, Hani; Al Aithan, Abdulsalam; Jose, Jesna; Abdukahil, Sheryl Ann I; Afesh, Lara Y; Dbsawy, Maamoun; Al-Dawood, Abdulaziz

    2018-03-15

    The Pneumatic CompREssion for Preventing VENous Thromboembolism (PREVENT) trial evaluates the effect of adjunctive intermittent pneumatic compression (IPC) with pharmacologic thromboprophylaxis compared to pharmacologic thromboprophylaxis alone on venous thromboembolism (VTE) in critically ill adults. In this multicenter randomized trial, critically ill patients receiving pharmacologic thromboprophylaxis will be randomized to an IPC or a no IPC (control) group. The primary outcome is "incident" proximal lower-extremity deep vein thrombosis (DVT) within 28 days after randomization. Radiologists interpreting the lower-extremity ultrasonography will be blinded to intervention allocation, whereas the patients and treating team will be unblinded. The trial has 80% power to detect a 3% absolute risk reduction in the rate of proximal DVT from 7% to 4%. Consistent with international guidelines, we have developed a detailed plan to guide the analysis of the PREVENT trial. This plan specifies the statistical methods for the evaluation of primary and secondary outcomes, and defines covariates for adjusted analyses a priori. Application of this statistical analysis plan to the PREVENT trial will facilitate unbiased analyses of clinical data. ClinicalTrials.gov , ID: NCT02040103 . Registered on 3 November 2013; Current controlled trials, ID: ISRCTN44653506 . Registered on 30 October 2013.

  10. Statistical trend analysis methodology for rare failures in changing technical systems

    International Nuclear Information System (INIS)

    Ott, K.O.; Hoffmann, H.J.

    1983-07-01

    A methodology for a statistical trend analysis (STA) in failure rates is presented. It applies primarily to relatively rare events in changing technologies or components. The formulation is more general and the assumptions are less restrictive than in a previously published version. Relations of the statistical analysis and probabilistic assessment (PRA) are discussed in terms of categorization of decisions for action following particular failure events. The significance of tentatively identified trends is explored. In addition to statistical tests for trend significance, a combination of STA and PRA results quantifying the trend complement is proposed. The STA approach is compared with other concepts for trend characterization. (orig.)

  11. Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids.

    Science.gov (United States)

    Ali, S M; Mehmood, C A; Khan, B; Jawad, M; Farid, U; Jadoon, J K; Ali, M; Tareen, N K; Usman, S; Majid, M; Anwar, S M

    2016-01-01

    In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion.

  12. Analysis of thrips distribution: application of spatial statistics and Kriging

    Science.gov (United States)

    John Aleong; Bruce L. Parker; Margaret Skinner; Diantha Howard

    1991-01-01

    Kriging is a statistical technique that provides predictions for spatially and temporally correlated data. Observations of thrips distribution and density in Vermont soils are made in both space and time. Traditional statistical analysis of such data assumes that the counts taken over space and time are independent, which is not necessarily true. Therefore, to analyze...

  13. Does the extended Glasgow Outcome Scale add value to the conventional Glasgow Outcome Scale?

    Science.gov (United States)

    Weir, James; Steyerberg, Ewout W; Butcher, Isabella; Lu, Juan; Lingsma, Hester F; McHugh, Gillian S; Roozenbeek, Bob; Maas, Andrew I R; Murray, Gordon D

    2012-01-01

    The Glasgow Outcome Scale (GOS) is firmly established as the primary outcome measure for use in Phase III trials of interventions in traumatic brain injury (TBI). However, the GOS has been criticized for its lack of sensitivity to detect small but clinically relevant changes in outcome. The Glasgow Outcome Scale-Extended (GOSE) potentially addresses this criticism, and in this study we estimate the efficiency gain associated with using the GOSE in place of the GOS in ordinal analysis of 6-month outcome. The study uses both simulation and the reanalysis of existing data from two completed TBI studies, one an observational cohort study and the other a randomized controlled trial. As expected, the results show that using an ordinal technique to analyze the GOS gives a substantial gain in efficiency relative to the conventional analysis, which collapses the GOS onto a binary scale (favorable versus unfavorable outcome). We also found that using the GOSE gave a modest but consistent increase in efficiency relative to the GOS in both studies, corresponding to a reduction in the required sample size of the order of 3-5%. We recommend that the GOSE be used in place of the GOS as the primary outcome measure in trials of TBI, with an appropriate ordinal approach being taken to the statistical analysis.

  14. Statistical wind analysis for near-space applications

    Science.gov (United States)

    Roney, Jason A.

    2007-09-01

    Statistical wind models were developed based on the existing observational wind data for near-space altitudes between 60 000 and 100 000 ft (18 30 km) above ground level (AGL) at two locations, Akon, OH, USA, and White Sands, NM, USA. These two sites are envisioned as playing a crucial role in the first flights of high-altitude airships. The analysis shown in this paper has not been previously applied to this region of the stratosphere for such an application. Standard statistics were compiled for these data such as mean, median, maximum wind speed, and standard deviation, and the data were modeled with Weibull distributions. These statistics indicated, on a yearly average, there is a lull or a “knee” in the wind between 65 000 and 72 000 ft AGL (20 22 km). From the standard statistics, trends at both locations indicated substantial seasonal variation in the mean wind speed at these heights. The yearly and monthly statistical modeling indicated that Weibull distributions were a reasonable model for the data. Forecasts and hindcasts were done by using a Weibull model based on 2004 data and comparing the model with the 2003 and 2005 data. The 2004 distribution was also a reasonable model for these years. Lastly, the Weibull distribution and cumulative function were used to predict the 50%, 95%, and 99% winds, which are directly related to the expected power requirements of a near-space station-keeping airship. These values indicated that using only the standard deviation of the mean may underestimate the operational conditions.

  15. Statistical analysis plan for the Adjunctive Corticosteroid Treatment in Critically Ill Patients with Septic Shock (ADRENAL) trial

    DEFF Research Database (Denmark)

    Billot, Laurent; Venkatesh, Balasubramanian; Myburgh, John

    2017-01-01

    BACKGROUND: The Adjunctive Corticosteroid Treatment in Critically Ill Patients with Septic Shock (ADRENAL) trial, a 3800-patient, multicentre, randomised controlled trial, will be the largest study to date of corticosteroid therapy in patients with septic shock. OBJECTIVE: To describe a statistical...... and statisticians and approved by the ADRENAL management committee. All authors were blind to treatment allocation and to the unblinded data produced during two interim analyses conducted by the Data Safety and Monitoring Committee. The data shells were produced from a previously published protocol. Statistical...... analyses are described in broad detail. Trial outcomes were selected and categorised into primary, secondary and tertiary outcomes, and appropriate statistical comparisons between groups are planned and described in a way that is transparent, available to the public, verifiable and determined before...

  16. Analysis of photon statistics with Silicon Photomultiplier

    International Nuclear Information System (INIS)

    D'Ascenzo, N.; Saveliev, V.; Wang, L.; Xie, Q.

    2015-01-01

    The Silicon Photomultiplier (SiPM) is a novel silicon-based photodetector, which represents the modern perspective of low photon flux detection. The aim of this paper is to provide an introduction on the statistical analysis methods needed to understand and estimate in quantitative way the correct features and description of the response of the SiPM to a coherent source of light

  17. Development of statistical analysis code for meteorological data (W-View)

    International Nuclear Information System (INIS)

    Tachibana, Haruo; Sekita, Tsutomu; Yamaguchi, Takenori

    2003-03-01

    A computer code (W-View: Weather View) was developed to analyze the meteorological data statistically based on 'the guideline of meteorological statistics for the safety analysis of nuclear power reactor' (Nuclear Safety Commission on January 28, 1982; revised on March 29, 2001). The code gives statistical meteorological data to assess the public dose in case of normal operation and severe accident to get the license of nuclear reactor operation. This code was revised from the original code used in a large office computer code to enable a personal computer user to analyze the meteorological data simply and conveniently and to make the statistical data tables and figures of meteorology. (author)

  18. Statistical analysis of the Ft. Calhoun reactor coolant pump system

    International Nuclear Information System (INIS)

    Heising, Carolyn D.

    1998-01-01

    In engineering science, statistical quality control techniques have traditionally been applied to control manufacturing processes. An application to commercial nuclear power plant maintenance and control is presented that can greatly improve plant safety. As a demonstration of such an approach to plant maintenance and control, a specific system is analyzed: the reactor coolant pumps (RCPs) of the Ft. Calhoun nuclear power plant. This research uses capability analysis, Shewhart X-bar, R-charts, canonical correlation methods, and design of experiments to analyze the process for the state of statistical control. The results obtained show that six out of ten parameters are under control specifications limits and four parameters are not in the state of statistical control. The analysis shows that statistical process control methods can be applied as an early warning system capable of identifying significant equipment problems well in advance of traditional control room alarm indicators Such a system would provide operators with ample time to respond to possible emergency situations and thus improve plant safety and reliability. (author)

  19. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

    Science.gov (United States)

    Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N

    2016-01-01

    Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  20. Mediation Analysis with Survival Outcomes: Accelerated Failure Time Versus Proportional Hazards Models

    Directory of Open Access Journals (Sweden)

    Lois A Gelfand

    2016-03-01

    Full Text Available Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH and fully parametric accelerated failure time (AFT approaches for illustration.Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively under varied data conditions, some including censoring. A simulated data set illustrates the findings.Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome – underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG.Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  1. Propensity Score Analysis: An Alternative Statistical Approach for HRD Researchers

    Science.gov (United States)

    Keiffer, Greggory L.; Lane, Forrest C.

    2016-01-01

    Purpose: This paper aims to introduce matching in propensity score analysis (PSA) as an alternative statistical approach for researchers looking to make causal inferences using intact groups. Design/methodology/approach: An illustrative example demonstrated the varying results of analysis of variance, analysis of covariance and PSA on a heuristic…

  2. Simulation Experiments in Practice: Statistical Design and Regression Analysis

    OpenAIRE

    Kleijnen, J.P.C.

    2007-01-01

    In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic DOE and regression analysis assume a single simulation response that is normally and independen...

  3. Statistical analysis of thermal conductivity of nanofluid containing ...

    Indian Academy of Sciences (India)

    Thermal conductivity measurements of nanofluids were analysed via two-factor completely randomized design and comparison of data means is carried out with Duncan's multiple-range test. Statistical analysis of experimental data show that temperature and weight fraction have a reasonable impact on the thermal ...

  4. Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT Study.

    Directory of Open Access Journals (Sweden)

    Sara E Moore

    Full Text Available Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of highly variable patient populations, such as those of the PRospective, Observational, Multi-center Major Trauma Transfusion study. Ten US level I trauma centers enrolled a total of 1,245 trauma patients who survived at least 30 minutes after admission and received at least one unit of red blood cells. Outcomes included death, multiple organ failure, substantial bleeding, and transfusion of blood products. The centers involved were classified as either large or small-volume based on the number of massive transfusion patients enrolled during the study period. We focused on estimation of parameters inspired by causal inference, specifically estimated impacts on patient outcomes related to the volume of the trauma hospital that treated them. We defined this association as the change in mean outcomes of interest that would be observed if, contrary to fact, subjects from large-volume sites were treated at small-volume sites (the effect of treatment among the treated. We estimated this parameter using three different methods, some of which use data-adaptive machine learning tools to derive the outcome models, minimizing residual confounding by reducing model misspecification. Differences between unadjusted and adjusted estimators sometimes differed dramatically, demonstrating the need to account for differences in patient characteristics in clinic comparisons. In addition, the estimators based on robust adjustment methods showed potential impacts of hospital volume. For instance, we estimated a survival benefit for patients who were treated at large-volume sites, which was not apparent in simpler, unadjusted comparisons. By removing arbitrary modeling decisions from the estimation process and concentrating

  5. Longitudinal data analysis a handbook of modern statistical methods

    CERN Document Server

    Fitzmaurice, Garrett; Verbeke, Geert; Molenberghs, Geert

    2008-01-01

    Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data. After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint

  6. Mathematical statistics

    CERN Document Server

    Pestman, Wiebe R

    2009-01-01

    This textbook provides a broad and solid introduction to mathematical statistics, including the classical subjects hypothesis testing, normal regression analysis, and normal analysis of variance. In addition, non-parametric statistics and vectorial statistics are considered, as well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and density estimation. For students with some elementary mathematical background. With many exercises. Prerequisites from measure theory and linear algebra are presented.

  7. Bayesian Sensitivity Analysis of Statistical Models with Missing Data.

    Science.gov (United States)

    Zhu, Hongtu; Ibrahim, Joseph G; Tang, Niansheng

    2014-04-01

    Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures.

  8. Advanced data analysis in neuroscience integrating statistical and computational models

    CERN Document Server

    Durstewitz, Daniel

    2017-01-01

    This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering.  Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerfu...

  9. Quantitative analysis and IBM SPSS statistics a guide for business and finance

    CERN Document Server

    Aljandali, Abdulkader

    2016-01-01

    This guide is for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance. This is the first of a two-part guide to SPSS for Windows, introducing data entry into SPSS, along with elementary statistical and graphical methods for summarizing and presenting data. Part I also covers the rudiments of hypothesis testing and business forecasting while Part II will present multivariate statistical methods, more advanced forecasting methods, and multivariate methods. IBM SPSS Statistics offers a powerful set of statistical and information analysis systems that run on a wide variety of personal computers. The software is built around routines that have been developed, tested, and widely used for more than 20 years. As such, IBM SPSS Statistics is extensively used in industry, commerce, banking, local and national governments, and education. Just a small subset of users of the package include the major clearing banks, the BBC, British Gas, British Airway...

  10. What type of statistical model to choose for the analysis of radioimmunoassays

    International Nuclear Information System (INIS)

    Huet, S.

    1984-01-01

    The current techniques used for statistical analysis of radioimmunoassays are not very satisfactory for either the statistician or the biologist. They are based on an attempt to make the response curve linear to avoid complicated computations. The present article shows that this practice has considerable effects (often neglected) on the statistical assumptions which must be formulated. A more strict analysis is proposed by applying the four-parameter logistic model. The advantages of this method are: the statistical assumptions formulated are based on observed data, and the model can be applied to almost all radioimmunoassays [fr

  11. Methadone-maintenance outcomes for Hispanic and African-American men and women.

    Science.gov (United States)

    Mulvaney, F D; Brown, L S; Alterman, A I; Sage, R E; Cnaan, A; Cacciola, J; Rutherford, M

    1999-03-01

    Six-month methadone-maintenance response and outcome were examined for African-American and Hispanic men and women in a large urban sample. A consistent pattern of improvement was indicated for both races and genders on the addiction severity index (ASI). There were virtually no statistically significant differences in ASI outcomes between Hispanics and African-Americans and men and women using conventional analysis of variance (ANOVA) procedures. Results from an additional equivalence analysis, however, indicated that baseline to 6-month changes for the different groups were generally not similar enough to consider them equivalent. Urine toxicologies obtained during the 6-month treatment period were also not statistically equivalent by race and gender. Evaluating outcomes by gender and race are discussed, as are the implications of using equivalence tests when examining group differences.

  12. Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers.

    Science.gov (United States)

    Genser, Bernd; Fischer, Joachim E; Figueiredo, Camila A; Alcântara-Neves, Neuza; Barreto, Mauricio L; Cooper, Philip J; Amorim, Leila D; Saemann, Marcus D; Weichhart, Thomas; Rodrigues, Laura C

    2016-05-20

    Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated. We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. The proposed analytical approach may be especially useful to quantify complex immune

  13. Computerized statistical analysis with bootstrap method in nuclear medicine

    International Nuclear Information System (INIS)

    Zoccarato, O.; Sardina, M.; Zatta, G.; De Agostini, A.; Barbesti, S.; Mana, O.; Tarolo, G.L.

    1988-01-01

    Statistical analysis of data samples involves some hypothesis about the features of data themselves. The accuracy of these hypotheses can influence the results of statistical inference. Among the new methods of computer-aided statistical analysis, the bootstrap method appears to be one of the most powerful, thanks to its ability to reproduce many artificial samples starting from a single original sample and because it works without hypothesis about data distribution. The authors applied the bootstrap method to two typical situation of Nuclear Medicine Department. The determination of the normal range of serum ferritin, as assessed by radioimmunoassay and defined by the mean value ±2 standard deviations, starting from an experimental sample of small dimension, shows an unacceptable lower limit (ferritin plasmatic levels below zero). On the contrary, the results obtained by elaborating 5000 bootstrap samples gives ans interval of values (10.95 ng/ml - 72.87 ng/ml) corresponding to the normal ranges commonly reported. Moreover the authors applied the bootstrap method in evaluating the possible error associated with the correlation coefficient determined between left ventricular ejection fraction (LVEF) values obtained by first pass radionuclide angiocardiography with 99m Tc and 195m Au. The results obtained indicate a high degree of statistical correlation and give the range of r 2 values to be considered acceptable for this type of studies

  14. Software for statistical data analysis used in Higgs searches

    International Nuclear Information System (INIS)

    Gumpert, Christian; Moneta, Lorenzo; Cranmer, Kyle; Kreiss, Sven; Verkerke, Wouter

    2014-01-01

    The analysis and interpretation of data collected by the Large Hadron Collider (LHC) requires advanced statistical tools in order to quantify the agreement between observation and theoretical models. RooStats is a project providing a statistical framework for data analysis with the focus on discoveries, confidence intervals and combination of different measurements in both Bayesian and frequentist approaches. It employs the RooFit data modelling language where mathematical concepts such as variables, (probability density) functions and integrals are represented as C++ objects. RooStats and RooFit rely on the persistency technology of the ROOT framework. The usage of a common data format enables the concept of digital publishing of complicated likelihood functions. The statistical tools have been developed in close collaboration with the LHC experiments to ensure their applicability to real-life use cases. Numerous physics results have been produced using the RooStats tools, with the discovery of the Higgs boson by the ATLAS and CMS experiments being certainly the most popular among them. We will discuss tools currently used by LHC experiments to set exclusion limits, to derive confidence intervals and to estimate discovery significances based on frequentist statistics and the asymptotic behaviour of likelihood functions. Furthermore, new developments in RooStats and performance optimisation necessary to cope with complex models depending on more than 1000 variables will be reviewed

  15. PRECISE - pregabalin in addition to usual care: Statistical analysis plan

    NARCIS (Netherlands)

    S. Mathieson (Stephanie); L. Billot (Laurent); C. Maher (Chris); A.J. McLachlan (Andrew J.); J. Latimer (Jane); B.W. Koes (Bart); M.J. Hancock (Mark J.); I. Harris (Ian); R.O. Day (Richard O.); J. Pik (Justin); S. Jan (Stephen); C.-W.C. Lin (Chung-Wei Christine)

    2016-01-01

    textabstractBackground: Sciatica is a severe, disabling condition that lacks high quality evidence for effective treatment strategies. This a priori statistical analysis plan describes the methodology of analysis for the PRECISE study. Methods/design: PRECISE is a prospectively registered, double

  16. Statistical margin to DNB safety analysis approach for LOFT

    International Nuclear Information System (INIS)

    Atkinson, S.A.

    1982-01-01

    A method was developed and used for LOFT thermal safety analysis to estimate the statistical margin to DNB for the hot rod, and to base safety analysis on desired DNB probability limits. This method is an advanced approach using response surface analysis methods, a very efficient experimental design, and a 2nd-order response surface equation with a 2nd-order error propagation analysis to define the MDNBR probability density function. Calculations for limiting transients were used in the response surface analysis thereby including transient interactions and trip uncertainties in the MDNBR probability density

  17. Multivariate statistical analysis of atom probe tomography data

    International Nuclear Information System (INIS)

    Parish, Chad M.; Miller, Michael K.

    2010-01-01

    The application of spectrum imaging multivariate statistical analysis methods, specifically principal component analysis (PCA), to atom probe tomography (APT) data has been investigated. The mathematical method of analysis is described and the results for two example datasets are analyzed and presented. The first dataset is from the analysis of a PM 2000 Fe-Cr-Al-Ti steel containing two different ultrafine precipitate populations. PCA properly describes the matrix and precipitate phases in a simple and intuitive manner. A second APT example is from the analysis of an irradiated reactor pressure vessel steel. Fine, nm-scale Cu-enriched precipitates having a core-shell structure were identified and qualitatively described by PCA. Advantages, disadvantages, and future prospects for implementing these data analysis methodologies for APT datasets, particularly with regard to quantitative analysis, are also discussed.

  18. Development of statistical analysis code for meteorological data (W-View)

    Energy Technology Data Exchange (ETDEWEB)

    Tachibana, Haruo; Sekita, Tsutomu; Yamaguchi, Takenori [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    2003-03-01

    A computer code (W-View: Weather View) was developed to analyze the meteorological data statistically based on 'the guideline of meteorological statistics for the safety analysis of nuclear power reactor' (Nuclear Safety Commission on January 28, 1982; revised on March 29, 2001). The code gives statistical meteorological data to assess the public dose in case of normal operation and severe accident to get the license of nuclear reactor operation. This code was revised from the original code used in a large office computer code to enable a personal computer user to analyze the meteorological data simply and conveniently and to make the statistical data tables and figures of meteorology. (author)

  19. CORSSA: Community Online Resource for Statistical Seismicity Analysis

    Science.gov (United States)

    Zechar, J. D.; Hardebeck, J. L.; Michael, A. J.; Naylor, M.; Steacy, S.; Wiemer, S.; Zhuang, J.

    2011-12-01

    Statistical seismology is critical to the understanding of seismicity, the evaluation of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology-especially to those aspects with great impact on public policy-statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA, www.corssa.org). We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each will contain between four and eight articles. CORSSA now includes seven articles with an additional six in draft form along with forums for discussion, a glossary, and news about upcoming meetings, special issues, and recent papers. Each article is peer-reviewed and presents a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. We have also begun curating a collection of statistical seismology software packages.

  20. Recent advances in statistical energy analysis

    Science.gov (United States)

    Heron, K. H.

    1992-01-01

    Statistical Energy Analysis (SEA) has traditionally been developed using modal summation and averaging approach, and has led to the need for many restrictive SEA assumptions. The assumption of 'weak coupling' is particularly unacceptable when attempts are made to apply SEA to structural coupling. It is now believed that this assumption is more a function of the modal formulation rather than a necessary formulation of SEA. The present analysis ignores this restriction and describes a wave approach to the calculation of plate-plate coupling loss factors. Predictions based on this method are compared with results obtained from experiments using point excitation on one side of an irregular six-sided box structure. Conclusions show that the use and calculation of infinite transmission coefficients is the way forward for the development of a purely predictive SEA code.

  1. Statistical analysis of tourism destination competitiveness

    Directory of Open Access Journals (Sweden)

    Attilio Gardini

    2013-05-01

    Full Text Available The growing relevance of tourism industry for modern advanced economies has increased the interest among researchers and policy makers in the statistical analysis of destination competitiveness. In this paper we outline a new model of destination competitiveness based on sound theoretical grounds and we develop a statistical test of the model on sample data based on Italian tourist destination decisions and choices. Our model focuses on the tourism decision process which starts from the demand schedule for holidays and ends with the choice of a specific holiday destination. The demand schedule is a function of individual preferences and of destination positioning, while the final decision is a function of the initial demand schedule and the information concerning services for accommodation and recreation in the selected destinations. Moreover, we extend previous studies that focused on image or attributes (such as climate and scenery by paying more attention to the services for accommodation and recreation in the holiday destinations. We test the proposed model using empirical data collected from a sample of 1.200 Italian tourists interviewed in 2007 (October - December. Data analysis shows that the selection probability for the destination included in the consideration set is not proportional to the share of inclusion because the share of inclusion is determined by the brand image, while the selection of the effective holiday destination is influenced by the real supply conditions. The analysis of Italian tourists preferences underline the existence of a latent demand for foreign holidays which points out a risk of market share reduction for Italian tourism system in the global market. We also find a snow ball effect which helps the most popular destinations, mainly in the northern Italian regions.

  2. Visual and statistical analysis of 18F-FDG PET in primary progressive aphasia

    International Nuclear Information System (INIS)

    Matias-Guiu, Jordi A.; Moreno-Ramos, Teresa; Garcia-Ramos, Rocio; Fernandez-Matarrubia, Marta; Oreja-Guevara, Celia; Matias-Guiu, Jorge; Cabrera-Martin, Maria Nieves; Perez-Castejon, Maria Jesus; Rodriguez-Rey, Cristina; Ortega-Candil, Aida; Carreras, Jose Luis

    2015-01-01

    Diagnosing progressive primary aphasia (PPA) and its variants is of great clinical importance, and fluorodeoxyglucose (FDG) positron emission tomography (PET) may be a useful diagnostic technique. The purpose of this study was to evaluate interobserver variability in the interpretation of FDG PET images in PPA as well as the diagnostic sensitivity and specificity of the technique. We also aimed to compare visual and statistical analyses of these images. There were 10 raters who analysed 44 FDG PET scans from 33 PPA patients and 11 controls. Five raters analysed the images visually, while the other five used maps created using Statistical Parametric Mapping software. Two spatial normalization procedures were performed: global mean normalization and cerebellar normalization. Clinical diagnosis was considered the gold standard. Inter-rater concordance was moderate for visual analysis (Fleiss' kappa 0.568) and substantial for statistical analysis (kappa 0.756-0.881). Agreement was good for all three variants of PPA except for the nonfluent/agrammatic variant studied with visual analysis. The sensitivity and specificity of each rater's diagnosis of PPA was high, averaging 87.8 and 89.9 % for visual analysis and 96.9 and 90.9 % for statistical analysis using global mean normalization, respectively. In cerebellar normalization, sensitivity was 88.9 % and specificity 100 %. FDG PET demonstrated high diagnostic accuracy for the diagnosis of PPA and its variants. Inter-rater concordance was higher for statistical analysis, especially for the nonfluent/agrammatic variant. These data support the use of FDG PET to evaluate patients with PPA and show that statistical analysis methods are particularly useful for identifying the nonfluent/agrammatic variant of PPA. (orig.)

  3. A Bayesian network meta-analysis for binary outcome: how to do it.

    Science.gov (United States)

    Greco, Teresa; Landoni, Giovanni; Biondi-Zoccai, Giuseppe; D'Ascenzo, Fabrizio; Zangrillo, Alberto

    2016-10-01

    This study presents an overview of conceptual and practical issues of a network meta-analysis (NMA), particularly focusing on its application to randomised controlled trials with a binary outcome of interest. We start from general considerations on NMA to specifically appraise how to collect study data, structure the analytical network and specify the requirements for different models and parameter interpretations, with the ultimate goal of providing physicians and clinician-investigators a practical tool to understand pros and cons of NMA. Specifically, we outline the key steps, from the literature search to sensitivity analysis, necessary to perform a valid NMA of binomial data, exploiting Markov Chain Monte Carlo approaches. We also apply this analytical approach to a case study on the beneficial effects of volatile agents compared to total intravenous anaesthetics for surgery to further clarify the statistical details of the models, diagnostics and computations. Finally, datasets and models for the freeware WinBUGS package are presented for the anaesthetic agent example. © The Author(s) 2013.

  4. Measuring the Success of an Academic Development Programme: A Statistical Analysis

    Science.gov (United States)

    Smith, L. C.

    2009-01-01

    This study uses statistical analysis to estimate the impact of first-year academic development courses in microeconomics, statistics, accountancy, and information systems, offered by the University of Cape Town's Commerce Academic Development Programme, on students' graduation performance relative to that achieved by mainstream students. The data…

  5. Clopidogrel-Proton Pump Inhibitor Drug-Drug Interaction and Risk of Adverse Clinical Outcomes Among PCI-Treated ACS Patients: A Meta-analysis.

    Science.gov (United States)

    Serbin, Michael A; Guzauskas, Gregory F; Veenstra, David L

    2016-08-01

    Uncertainty regarding clopidogrel effectiveness attenuation because of a drug-drug interaction with proton pump inhibitors (PPI) has led to conflicting guidelines on concomitant therapy. In particular, the effect of this interaction in patients who undergo a percutaneous coronary intervention (PCI), a population known to have increased risk of adverse cardiovascular events, has not been systematically evaluated. To synthesize the evidence of the effect of clopidogrel-PPI drug interaction on adverse cardiovascular outcomes in a PCI patient population. We conducted a systematic literature review for studies reporting clinical outcomes in patients who underwent a PCI and were initiated on clopidogrel with or without a PPI. Studies were included in the analysis if they reported at least 1 of the clinical outcomes of interest (major adverse cardiovascular event [MACE], cardiovascular death, all-cause death, myocardial infarction, stroke, stent thrombosis, and bleed events). We excluded studies that were not exclusive to PCI patients or had no PCI subgroup analysis and/or did not report at least a 6-month follow-up. Statistical and clinical heterogeneity were evaluated and HRs and 95% CIs for adverse clinical events were pooled using the DerSimonian and Laird random-effects meta-analysis method. We identified 12 studies comprising 50,277 PCI patients that met our inclusion and exclusion criteria. Our analysis included retrospective analyses of randomized controlled trials (2), health registries (3), claims databases (2), and institutional records (5); no prospective studies of PCI patients were identified. On average, patients were in their mid-60s, male, and had an array of comorbidities, including hyperlipidemia, diabetes, hypertension, and smoking history. Concomitant therapy following PCI resulted in statistically significant increases in composite MACE (HR = 1.28; 95% CI = 1.24-1.32), myocardial infarction (HR = 1.51; 95% CI = 1.40-1.62), and stroke (HR = 1.46; 95

  6. Adult asthma disease management: an analysis of studies, approaches, outcomes, and methods.

    Science.gov (United States)

    Maciejewski, Matthew L; Chen, Shih-Yin; Au, David H

    2009-07-01

    Disease management has been implemented for patients with asthma in various ways. We describe the approaches to and components of adult asthma disease-management interventions, examine the outcomes evaluated, and assess the quality of published studies. We searched the MEDLINE, EMBASE, CINAHL, PsychInfo, and Cochrane databases for studies published in 1986 through 2008, on adult asthma management. With the studies that met our inclusion criteria, we examined the clinical, process, medication, economic, and patient-reported outcomes reported, and the study designs, provider collaboration during the studies, and statistical methods. Twenty-nine articles describing 27 studies satisfied our inclusion criteria. There was great variation in the content, extent of collaboration between physician and non-physician providers responsible for intervention delivery, and outcomes examined across the 27 studies. Because of limitations in the design of 22 of the 27 studies, the differences in outcomes assessed, and the lack of rigorous statistical adjustment, we could not draw definitive conclusions about the effectiveness or cost-effectiveness of the asthma disease-management programs or which approach was most effective. Few well-designed studies with rigorous evaluations have been conducted to evaluate disease-management interventions for adults with asthma. Current evidence is insufficient to recommend any particular intervention.

  7. WATER POLO GAME-RELATED STATISTICS IN WOMEN'S INTERNATIONAL CHAMPIONSHIPS: DIFFERENCES AND DISCRIMINATORY POWER

    Directory of Open Access Journals (Sweden)

    Yolanda Escalante

    2012-09-01

    Full Text Available The aims of this study were (i to compare women's water polo game-related statistics by match outcome (winning and losing teams and phase (preliminary, classificatory, and semi-final/bronze medal/gold medal, and (ii identify characteristics that discriminate performances for each phase. The game-related statistics of the 124 women's matches played in five International Championships (World and European Championships were analyzed. Differences between winning and losing teams in each phase were determined using the chi-squared. A discriminant analysis was then performed according to context in each of the three phases. It was found that the game-related statistics differentiate the winning from the losing teams in each phase of an international championship. The differentiating variables were both offensive (centre goals, power-play goals, counterattack goal, assists, offensive fouls, steals, blocked shots, and won sprints and defensive (goalkeeper-blocked shots, goalkeeper-blocked inferiority shots, and goalkeeper-blocked 5-m shots. The discriminant analysis showed the game-related statistics to discriminate performance in all phases: preliminary, classificatory, and final phases (92%, 90%, and 83%, respectively. Two variables were discriminatory by match outcome (winning or losing teams in all three phases: goals and goalkeeper-blocked shots

  8. Analysis of Variance in Statistical Image Processing

    Science.gov (United States)

    Kurz, Ludwik; Hafed Benteftifa, M.

    1997-04-01

    A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

  9. Study of relationship between MUF correlation and detection sensitivity of statistical analysis

    International Nuclear Information System (INIS)

    Tamura, Toshiaki; Ihara, Hitoshi; Yamamoto, Yoichi; Ikawa, Koji

    1989-11-01

    Various kinds of statistical analysis are proposed to NRTA (Near Real Time Materials Accountancy) which was devised to satisfy the timeliness goal of one of the detection goals of IAEA. It will be presumed that different statistical analysis results will occur between the case of considered rigorous error propagation (with MUF correlation) and the case of simplified error propagation (without MUF correlation). Therefore, measurement simulation and decision analysis were done using flow simulation of 800 MTHM/Y model reprocessing plant, and relationship between MUF correlation and detection sensitivity and false alarm of statistical analysis was studied. Specific character of material accountancy for 800 MTHM/Y model reprocessing plant was grasped by this simulation. It also became clear that MUF correlation decreases not only false alarm but also detection probability for protracted loss in case of CUMUF test and Page's test applied to NRTA. (author)

  10. 75 FR 24718 - Guidance for Industry on Documenting Statistical Analysis Programs and Data Files; Availability

    Science.gov (United States)

    2010-05-05

    ...] Guidance for Industry on Documenting Statistical Analysis Programs and Data Files; Availability AGENCY... documenting statistical analyses and data files submitted to the Center for Veterinary Medicine (CVM) for the... on Documenting Statistical Analysis Programs and Data Files; Availability'' giving interested persons...

  11. Effects of metformin on pregnancy outcomes in women with polycystic ovary syndrome: A meta-analysis.

    Science.gov (United States)

    Zeng, Xian-Ling; Zhang, Ya-Fei; Tian, Quan; Xue, Yan; An, Rui-Fang

    2016-09-01

    The aim of the study is to evaluate the effects of metformin on pregnancy outcomes in women with polycystic ovary syndrome (PCOS). We searched electronic databases and bibliographies of relevant papers to identify studies comparing the pregnancy outcomes in the metformin group with those in the placebo or blank control group. Then, we did this meta-analysis based on the PRISMA guidelines. The primary outcomes included early pregnancy loss (EPL), preterm delivery, term delivery, and gestational diabetes mellitus (GDM). Secondary outcomes included pregnancy-induced hypertension (PIH), intrauterine growth restriction (IUGR), fetal malformation, vaginal delivery (VD), cesarean section (CS), and metformin's side effects, such as nausea or gastrointestinal discomfort. Certainly, data about neonatal death and macrosomia were analyzed if data available. Finally, 13 studies including 5 randomized controlled trials (RCT) and 8 cohort studies involving 1606 pregnant women with PCOS were analyzed. The pooled OR of EPL was 0.19 with obvious statistical significance, manifesting that metformin help to lower the rate of EPL (95% CI 0.12-0.28, P metformin showed the advantage of reducing the prevalence of preterm delivery (OR 0.37, 95% CI 0.20-0.68, P = 0.002). In addition, metformin could promote term delivery greatly and the pooled OR was 5.23 with sharp statistical difference (95% CI 3.12-8.75, P Metformin treatment in women with PCOS throughout pregnancy could increase the possibility of term delivery, VD and reduce the risk of EPL, preterm labor, pregnancy complications such as GDM and PIH, with no serious side effects. Moreover, metformin was not teratogenic based on the limited data. So we may recommend metformin treatment for women with PCOS during the whole pregnancy period for it is quite beneficial and safe for both mothers and babies.

  12. Outcome analysis of retrograde nailing and less invasive stabilization system in distal femoral fractures: A retrospective analysis

    Directory of Open Access Journals (Sweden)

    Christian Hierholzer

    2011-01-01

    . Accumulative result of functional outcome using the Knee and Osteoarthritis Outcome (KOOS score demonstrated in type A fractures a score of 263 (RN and 260 (LISS, and in type C fractures 257 (RN and 218 (LISS. Differences between groups for type A were statistically insignificant, statistical analysis for type C fractures between the two groups are not possible, since in type C2 and C3 fractures only LISS plating was performed. Conclusion: Both retrograde IM nailing and angular stable plating are adequate treatment options for distal femur fractures. Locked plating can be used for all distal femur fractures including complex type C fractures, periprosthetic fractures, as well as osteoporotic fractures. IM nailing provides favorable stability and can be successfully implanted in bilateral or multisegmental fractures of the lower extremity as well as in extra-articular fractures. However, both systems require precise preoperative planning and advanced surgical experience to reduce the risk of revision surgery. Clinical outcome largely depends on surgical technique rather than on the choice of implant.

  13. Point defect characterization in HAADF-STEM images using multivariate statistical analysis

    International Nuclear Information System (INIS)

    Sarahan, Michael C.; Chi, Miaofang; Masiel, Daniel J.; Browning, Nigel D.

    2011-01-01

    Quantitative analysis of point defects is demonstrated through the use of multivariate statistical analysis. This analysis consists of principal component analysis for dimensional estimation and reduction, followed by independent component analysis to obtain physically meaningful, statistically independent factor images. Results from these analyses are presented in the form of factor images and scores. Factor images show characteristic intensity variations corresponding to physical structure changes, while scores relate how much those variations are present in the original data. The application of this technique is demonstrated on a set of experimental images of dislocation cores along a low-angle tilt grain boundary in strontium titanate. A relationship between chemical composition and lattice strain is highlighted in the analysis results, with picometer-scale shifts in several columns measurable from compositional changes in a separate column. -- Research Highlights: → Multivariate analysis of HAADF-STEM images. → Distinct structural variations among SrTiO 3 dislocation cores. → Picometer atomic column shifts correlated with atomic column population changes.

  14. Outcomes and Pharmacoeconomic Analysis of a Home Intravenous Antibiotic Infusion Program in Veterans.

    Science.gov (United States)

    Ruh, Christine A; Parameswaran, Ganapathi I; Wojciechowski, Amy L; Mergenhagen, Kari A

    2015-11-01

    The use of outpatient parenteral antibiotic therapy (OPAT) programs has become more frequent because of benefits in costs with equivalent clinical outcomes compared with inpatient care. The purpose of this study was to evaluate the outcomes of our program. A modified pharmacoeconomic analysis was performed to compare costs of our program with hospital or rehabilitation facility care. This was a retrospective chart review of 96 courses of OPAT between April 1, 2011, and July 31, 2013. Clinical failures were defined as readmission or death due to worsening infection or readmission secondary to adverse drug event (ADE) to antibiotic therapy. This does not include those patients readmitted for reasons not associated with OPAT therapy, including comorbidities or elective procedures. Baseline characteristics and program-specific data were analyzed. Statistically significant variables were built into a multivariate logistic regression model to determine predictors of failure. A pharmacoeconomic analysis was performed with the use of billing records. Of the total episodes evaluated, 17 (17.71%) clinically failed therapy, and 79 (82.29%) were considered a success. In the multivariate analysis, number of laboratory draws (P = 0.02) and occurrence of drug reaction were significant in the final model, P = 0.02 and P = 0.001, respectively. The presence an adverse drug reaction increases the odds of failure (OR = 10.10; 95% CI, 2.69-44.90). Compared with inpatient or rehabilitation care, the cost savings was $6,932,552.03 or $2,649,870.68, respectively. In our study, patients tolerated OPAT well, with a low number of failures due to ADE. The clinical outcomes and cost savings of our program indicate that OPAT can be a viable alternative to long-term inpatient antimicrobial therapy. Published by Elsevier Inc.

  15. Sigsearch: a new term for post hoc unplanned search for statistically significant relationships with the intent to create publishable findings.

    Science.gov (United States)

    Hashim, Muhammad Jawad

    2010-09-01

    Post-hoc secondary data analysis with no prespecified hypotheses has been discouraged by textbook authors and journal editors alike. Unfortunately no single term describes this phenomenon succinctly. I would like to coin the term "sigsearch" to define this practice and bring it within the teaching lexicon of statistics courses. Sigsearch would include any unplanned, post-hoc search for statistical significance using multiple comparisons of subgroups. It would also include data analysis with outcomes other than the prespecified primary outcome measure of a study as well as secondary data analyses of earlier research.

  16. STATCAT, Statistical Analysis of Parametric and Non-Parametric Data

    International Nuclear Information System (INIS)

    David, Hugh

    1990-01-01

    1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required

  17. How the Mastery Rubric for Statistical Literacy Can Generate Actionable Evidence about Statistical and Quantitative Learning Outcomes

    Directory of Open Access Journals (Sweden)

    Rochelle E. Tractenberg

    2016-12-01

    Full Text Available Statistical literacy is essential to an informed citizenry; and two emerging trends highlight a growing need for training that achieves this literacy. The first trend is towards “big” data: while automated analyses can exploit massive amounts of data, the interpretation—and possibly more importantly, the replication—of results are challenging without adequate statistical literacy. The second trend is that science and scientific publishing are struggling with insufficient/inappropriate statistical reasoning in writing, reviewing, and editing. This paper describes a model for statistical literacy (SL and its development that can support modern scientific practice. An established curriculum development and evaluation tool—the Mastery Rubric—is integrated with a new, developmental, model of statistical literacy that reflects the complexity of reasoning and habits of mind that scientists need to cultivate in order to recognize, choose, and interpret statistical methods. This developmental model provides actionable evidence, and explicit opportunities for consequential assessment that serves students, instructors, developers/reviewers/accreditors of a curriculum, and institutions. By supporting the enrichment, rather than increasing the amount, of statistical training in the basic and life sciences, this approach supports curriculum development, evaluation, and delivery to promote statistical literacy for students and a collective quantitative proficiency more broadly.

  18. FADTTS: functional analysis of diffusion tensor tract statistics.

    Science.gov (United States)

    Zhu, Hongtu; Kong, Linglong; Li, Runze; Styner, Martin; Gerig, Guido; Lin, Weili; Gilmore, John H

    2011-06-01

    The aim of this paper is to present a functional analysis of a diffusion tensor tract statistics (FADTTS) pipeline for delineating the association between multiple diffusion properties along major white matter fiber bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these white matter tract properties in various diffusion tensor imaging studies. The FADTTS integrates five statistical tools: (i) a multivariate varying coefficient model for allowing the varying coefficient functions in terms of arc length to characterize the varying associations between fiber bundle diffusion properties and a set of covariates, (ii) a weighted least squares estimation of the varying coefficient functions, (iii) a functional principal component analysis to delineate the structure of the variability in fiber bundle diffusion properties, (iv) a global test statistic to test hypotheses of interest, and (v) a simultaneous confidence band to quantify the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FADTTS. We apply FADTTS to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment. FADTTS can be used to facilitate the understanding of normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. The advantages of FADTTS compared with the other existing approaches are that they are capable of modeling the structured inter-subject variability, testing the joint effects, and constructing their simultaneous confidence bands. However, FADTTS is not crucial for estimation and reduces to the functional analysis method for the single measure. Copyright © 2011 Elsevier Inc. All rights reserved.

  19. Statistical process control methods allow the analysis and improvement of anesthesia care.

    Science.gov (United States)

    Fasting, Sigurd; Gisvold, Sven E

    2003-10-01

    Quality aspects of the anesthetic process are reflected in the rate of intraoperative adverse events. The purpose of this report is to illustrate how the quality of the anesthesia process can be analyzed using statistical process control methods, and exemplify how this analysis can be used for quality improvement. We prospectively recorded anesthesia-related data from all anesthetics for five years. The data included intraoperative adverse events, which were graded into four levels, according to severity. We selected four adverse events, representing important quality and safety aspects, for statistical process control analysis. These were: inadequate regional anesthesia, difficult emergence from general anesthesia, intubation difficulties and drug errors. We analyzed the underlying process using 'p-charts' for statistical process control. In 65,170 anesthetics we recorded adverse events in 18.3%; mostly of lesser severity. Control charts were used to define statistically the predictable normal variation in problem rate, and then used as a basis for analysis of the selected problems with the following results: Inadequate plexus anesthesia: stable process, but unacceptably high failure rate; Difficult emergence: unstable process, because of quality improvement efforts; Intubation difficulties: stable process, rate acceptable; Medication errors: methodology not suited because of low rate of errors. By applying statistical process control methods to the analysis of adverse events, we have exemplified how this allows us to determine if a process is stable, whether an intervention is required, and if quality improvement efforts have the desired effect.

  20. Statistical analysis plan for the family-led rehabilitation after stroke in India (ATTEND) trial: A multicenter randomized controlled trial of a new model of stroke rehabilitation compared to usual care.

    Science.gov (United States)

    Billot, Laurent; Lindley, Richard I; Harvey, Lisa A; Maulik, Pallab K; Hackett, Maree L; Murthy, Gudlavalleti Vs; Anderson, Craig S; Shamanna, Bindiganavale R; Jan, Stephen; Walker, Marion; Forster, Anne; Langhorne, Peter; Verma, Shweta J; Felix, Cynthia; Alim, Mohammed; Gandhi, Dorcas Bc; Pandian, Jeyaraj Durai

    2017-02-01

    Background In low- and middle-income countries, few patients receive organized rehabilitation after stroke, yet the burden of chronic diseases such as stroke is increasing in these countries. Affordable models of effective rehabilitation could have a major impact. The ATTEND trial is evaluating a family-led caregiver delivered rehabilitation program after stroke. Objective To publish the detailed statistical analysis plan for the ATTEND trial prior to trial unblinding. Methods Based upon the published registration and protocol, the blinded steering committee and management team, led by the trial statistician, have developed a statistical analysis plan. The plan has been informed by the chosen outcome measures, the data collection forms and knowledge of key baseline data. Results The resulting statistical analysis plan is consistent with best practice and will allow open and transparent reporting. Conclusions Publication of the trial statistical analysis plan reduces potential bias in trial reporting, and clearly outlines pre-specified analyses. Clinical Trial Registrations India CTRI/2013/04/003557; Australian New Zealand Clinical Trials Registry ACTRN1261000078752; Universal Trial Number U1111-1138-6707.

  1. Effect of the absolute statistic on gene-sampling gene-set analysis methods.

    Science.gov (United States)

    Nam, Dougu

    2017-06-01

    Gene-set enrichment analysis and its modified versions have commonly been used for identifying altered functions or pathways in disease from microarray data. In particular, the simple gene-sampling gene-set analysis methods have been heavily used for datasets with only a few sample replicates. The biggest problem with this approach is the highly inflated false-positive rate. In this paper, the effect of absolute gene statistic on gene-sampling gene-set analysis methods is systematically investigated. Thus far, the absolute gene statistic has merely been regarded as a supplementary method for capturing the bidirectional changes in each gene set. Here, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was investigated by power, false-positive rate, and receiver operating curve for a number of simulated and real datasets. The performances of gene-set analysis methods in one-tailed (genome-wide association study) and two-tailed (gene expression data) tests were also compared and discussed.

  2. An improved method for statistical analysis of raw accelerator mass spectrometry data

    International Nuclear Information System (INIS)

    Gutjahr, A.; Phillips, F.; Kubik, P.W.; Elmore, D.

    1987-01-01

    Hierarchical statistical analysis is an appropriate method for statistical treatment of raw accelerator mass spectrometry (AMS) data. Using Monte Carlo simulations we show that this method yields more accurate estimates of isotope ratios and analytical uncertainty than the generally used propagation of errors approach. The hierarchical analysis is also useful in design of experiments because it can be used to identify sources of variability. 8 refs., 2 figs

  3. Statistical Image Analysis of Tomograms with Application to Fibre Geometry Characterisation

    DEFF Research Database (Denmark)

    Emerson, Monica Jane

    The goal of this thesis is to develop statistical image analysis tools to characterise the micro-structure of complex materials used in energy technologies, with a strong focus on fibre composites. These quantification tools are based on extracting geometrical parameters defining structures from 2D...... with high resolution both in space and time to observe fast micro-structural changes. This thesis demonstrates that statistical image analysis combined with X-ray CT opens up numerous possibilities for understanding the behaviour of fibre composites under real life conditions. Besides enabling...

  4. The art of data analysis how to answer almost any question using basic statistics

    CERN Document Server

    Jarman, Kristin H

    2013-01-01

    A friendly and accessible approach to applying statistics in the real worldWith an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way.Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool.  In addition, light-hearted case studies

  5. Statistics in experimental design, preprocessing, and analysis of proteomics data.

    Science.gov (United States)

    Jung, Klaus

    2011-01-01

    High-throughput experiments in proteomics, such as 2-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS), yield usually high-dimensional data sets of expression values for hundreds or thousands of proteins which are, however, observed on only a relatively small number of biological samples. Statistical methods for the planning and analysis of experiments are important to avoid false conclusions and to receive tenable results. In this chapter, the most frequent experimental designs for proteomics experiments are illustrated. In particular, focus is put on studies for the detection of differentially regulated proteins. Furthermore, issues of sample size planning, statistical analysis of expression levels as well as methods for data preprocessing are covered.

  6. Application of Multivariable Statistical Techniques in Plant-wide WWTP Control Strategies Analysis

    DEFF Research Database (Denmark)

    Flores Alsina, Xavier; Comas, J.; Rodríguez-Roda, I.

    2007-01-01

    The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant...... analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii......) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation...

  7. The Statistical Analysis Techniques to Support the NGNP Fuel Performance Experiments

    International Nuclear Information System (INIS)

    Pham, Bihn T.; Einerson, Jeffrey J.

    2010-01-01

    This paper describes the development and application of statistical analysis techniques to support the AGR experimental program on NGNP fuel performance. The experiments conducted in the Idaho National Laboratory's Advanced Test Reactor employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule. The tests are instrumented with thermocouples embedded in graphite blocks and the target quantity (fuel/graphite temperature) is regulated by the He-Ne gas mixture that fills the gap volume. Three techniques for statistical analysis, namely control charting, correlation analysis, and regression analysis, are implemented in the SAS-based NGNP Data Management and Analysis System (NDMAS) for automated processing and qualification of the AGR measured data. The NDMAS also stores daily neutronic (power) and thermal (heat transfer) code simulation results along with the measurement data, allowing for their combined use and comparative scrutiny. The ultimate objective of this work includes (a) a multi-faceted system for data monitoring and data accuracy testing, (b) identification of possible modes of diagnostics deterioration and changes in experimental conditions, (c) qualification of data for use in code validation, and (d) identification and use of data trends to support effective control of test conditions with respect to the test target. Analysis results and examples given in the paper show the three statistical analysis techniques providing a complementary capability to warn of thermocouple failures. It also suggests that the regression analysis models relating calculated fuel temperatures and thermocouple readings can enable online regulation of experimental parameters (i.e. gas mixture content), to effectively maintain the target quantity (fuel temperature) within a given range.

  8. The statistical analysis techniques to support the NGNP fuel performance experiments

    Energy Technology Data Exchange (ETDEWEB)

    Pham, Binh T., E-mail: Binh.Pham@inl.gov; Einerson, Jeffrey J.

    2013-10-15

    This paper describes the development and application of statistical analysis techniques to support the Advanced Gas Reactor (AGR) experimental program on Next Generation Nuclear Plant (NGNP) fuel performance. The experiments conducted in the Idaho National Laboratory’s Advanced Test Reactor employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule. The tests are instrumented with thermocouples embedded in graphite blocks and the target quantity (fuel temperature) is regulated by the He–Ne gas mixture that fills the gap volume. Three techniques for statistical analysis, namely control charting, correlation analysis, and regression analysis, are implemented in the NGNP Data Management and Analysis System for automated processing and qualification of the AGR measured data. The neutronic and thermal code simulation results are used for comparative scrutiny. The ultimate objective of this work includes (a) a multi-faceted system for data monitoring and data accuracy testing, (b) identification of possible modes of diagnostics deterioration and changes in experimental conditions, (c) qualification of data for use in code validation, and (d) identification and use of data trends to support effective control of test conditions with respect to the test target. Analysis results and examples given in the paper show the three statistical analysis techniques providing a complementary capability to warn of thermocouple failures. It also suggests that the regression analysis models relating calculated fuel temperatures and thermocouple readings can enable online regulation of experimental parameters (i.e. gas mixture content), to effectively maintain the fuel temperature within a given range.

  9. Statistical Challenges of Big Data Analysis in Medicine

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2015-01-01

    Roč. 3, č. 1 (2015), s. 24-27 ISSN 1805-8698 R&D Projects: GA ČR GA13-23940S Grant - others:CESNET Development Fund(CZ) 494/2013 Institutional support: RVO:67985807 Keywords : big data * variable selection * classification * cluster analysis Subject RIV: BB - Applied Statistics, Operational Research http://www.ijbh.org/ijbh2015-1.pdf

  10. A scan statistic for binary outcome based on hypergeometric probability model, with an application to detecting spatial clusters of Japanese encephalitis.

    Science.gov (United States)

    Zhao, Xing; Zhou, Xiao-Hua; Feng, Zijian; Guo, Pengfei; He, Hongyan; Zhang, Tao; Duan, Lei; Li, Xiaosong

    2013-01-01

    As a useful tool for geographical cluster detection of events, the spatial scan statistic is widely applied in many fields and plays an increasingly important role. The classic version of the spatial scan statistic for the binary outcome is developed by Kulldorff, based on the Bernoulli or the Poisson probability model. In this paper, we apply the Hypergeometric probability model to construct the likelihood function under the null hypothesis. Compared with existing methods, the likelihood function under the null hypothesis is an alternative and indirect method to identify the potential cluster, and the test statistic is the extreme value of the likelihood function. Similar with Kulldorff's methods, we adopt Monte Carlo test for the test of significance. Both methods are applied for detecting spatial clusters of Japanese encephalitis in Sichuan province, China, in 2009, and the detected clusters are identical. Through a simulation to independent benchmark data, it is indicated that the test statistic based on the Hypergeometric model outweighs Kulldorff's statistics for clusters of high population density or large size; otherwise Kulldorff's statistics are superior.

  11. Statistical Analysis of Hypercalcaemia Data related to Transferability

    DEFF Research Database (Denmark)

    Frølich, Anne; Nielsen, Bo Friis

    2005-01-01

    In this report we describe statistical analysis related to a study of hypercalcaemia carried out in the Copenhagen area in the ten year period from 1984 to 1994. Results from the study have previously been publised in a number of papers [3, 4, 5, 6, 7, 8, 9] and in various abstracts and posters...... at conferences during the late eighties and early nineties. In this report we give a more detailed description of many of the analysis and provide some new results primarily by simultaneous studies of several databases....

  12. Statistical analysis of questionnaires a unified approach based on R and Stata

    CERN Document Server

    Bartolucci, Francesco; Gnaldi, Michela

    2015-01-01

    Statistical Analysis of Questionnaires: A Unified Approach Based on R and Stata presents special statistical methods for analyzing data collected by questionnaires. The book takes an applied approach to testing and measurement tasks, mirroring the growing use of statistical methods and software in education, psychology, sociology, and other fields. It is suitable for graduate students in applied statistics and psychometrics and practitioners in education, health, and marketing.The book covers the foundations of classical test theory (CTT), test reliability, va

  13. Reducing bias in the analysis of counting statistics data

    International Nuclear Information System (INIS)

    Hammersley, A.P.; Antoniadis, A.

    1997-01-01

    In the analysis of counting statistics data it is common practice to estimate the variance of the measured data points as the data points themselves. This practice introduces a bias into the results of further analysis which may be significant, and under certain circumstances lead to false conclusions. In the case of normal weighted least squares fitting this bias is quantified and methods to avoid it are proposed. (orig.)

  14. Benchmark validation of statistical models: Application to mediation analysis of imagery and memory.

    Science.gov (United States)

    MacKinnon, David P; Valente, Matthew J; Wurpts, Ingrid C

    2018-03-29

    This article describes benchmark validation, an approach to validating a statistical model. According to benchmark validation, a valid model generates estimates and research conclusions consistent with a known substantive effect. Three types of benchmark validation-(a) benchmark value, (b) benchmark estimate, and (c) benchmark effect-are described and illustrated with examples. Benchmark validation methods are especially useful for statistical models with assumptions that are untestable or very difficult to test. Benchmark effect validation methods were applied to evaluate statistical mediation analysis in eight studies using the established effect that increasing mental imagery improves recall of words. Statistical mediation analysis led to conclusions about mediation that were consistent with established theory that increased imagery leads to increased word recall. Benchmark validation based on established substantive theory is discussed as a general way to investigate characteristics of statistical models and a complement to mathematical proof and statistical simulation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  15. Bayesian statistics applied to neutron activation data for reactor flux spectrum analysis

    International Nuclear Information System (INIS)

    Chiesa, Davide; Previtali, Ezio; Sisti, Monica

    2014-01-01

    Highlights: • Bayesian statistics to analyze the neutron flux spectrum from activation data. • Rigorous statistical approach for accurate evaluation of the neutron flux groups. • Cross section and activation data uncertainties included for the problem solution. • Flexible methodology applied to analyze different nuclear reactor flux spectra. • The results are in good agreement with the MCNP simulations of neutron fluxes. - Abstract: In this paper, we present a statistical method, based on Bayesian statistics, to analyze the neutron flux spectrum from the activation data of different isotopes. The experimental data were acquired during a neutron activation experiment performed at the TRIGA Mark II reactor of Pavia University (Italy) in four irradiation positions characterized by different neutron spectra. In order to evaluate the neutron flux spectrum, subdivided in energy groups, a system of linear equations, containing the group effective cross sections and the activation rate data, has to be solved. However, since the system’s coefficients are experimental data affected by uncertainties, a rigorous statistical approach is fundamental for an accurate evaluation of the neutron flux groups. For this purpose, we applied the Bayesian statistical analysis, that allows to include the uncertainties of the coefficients and the a priori information about the neutron flux. A program for the analysis of Bayesian hierarchical models, based on Markov Chain Monte Carlo (MCMC) simulations, was used to define the problem statistical model and solve it. The first analysis involved the determination of the thermal, resonance-intermediate and fast flux components and the dependence of the results on the Prior distribution choice was investigated to confirm the reliability of the Bayesian analysis. After that, the main resonances of the activation cross sections were analyzed to implement multi-group models with finer energy subdivisions that would allow to determine the

  16. Reactor noise analysis by statistical pattern recognition methods

    International Nuclear Information System (INIS)

    Howington, L.C.; Gonzalez, R.C.

    1976-01-01

    A multivariate statistical pattern recognition system for reactor noise analysis is presented. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, updating, and data compacting capabilities. System design emphasizes control of the false-alarm rate. Its abilities to learn normal patterns, to recognize deviations from these patterns, and to reduce the dimensionality of data with minimum error were evaluated by experiments at the Oak Ridge National Laboratory (ORNL) High-Flux Isotope Reactor. Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the pattern recognition system

  17. Data analysis using the Gnu R system for statistical computation

    Energy Technology Data Exchange (ETDEWEB)

    Simone, James; /Fermilab

    2011-07-01

    R is a language system for statistical computation. It is widely used in statistics, bioinformatics, machine learning, data mining, quantitative finance, and the analysis of clinical drug trials. Among the advantages of R are: it has become the standard language for developing statistical techniques, it is being actively developed by a large and growing global user community, it is open source software, it is highly portable (Linux, OS-X and Windows), it has a built-in documentation system, it produces high quality graphics and it is easily extensible with over four thousand extension library packages available covering statistics and applications. This report gives a very brief introduction to R with some examples using lattice QCD simulation results. It then discusses the development of R packages designed for chi-square minimization fits for lattice n-pt correlation functions.

  18. Application of a statistical thermal design procedure to evaluate the PWR DNBR safety analysis limits

    International Nuclear Information System (INIS)

    Robeyns, J.; Parmentier, F.; Peeters, G.

    2001-01-01

    In the framework of safety analysis for the Belgian nuclear power plants and for the reload compatibility studies, Tractebel Energy Engineering (TEE) has developed, to define a 95/95 DNBR criterion, a statistical thermal design method based on the analytical full statistical approach: the Statistical Thermal Design Procedure (STDP). In that methodology, each DNBR value in the core assemblies is calculated with an adapted CHF (Critical Heat Flux) correlation implemented in the sub-channel code Cobra for core thermal hydraulic analysis. The uncertainties of the correlation are represented by the statistical parameters calculated from an experimental database. The main objective of a sub-channel analysis is to prove that in all class 1 and class 2 situations, the minimum DNBR (Departure from Nucleate Boiling Ratio) remains higher than the Safety Analysis Limit (SAL). The SAL value is calculated from the Statistical Design Limit (SDL) value adjusted with some penalties and deterministic factors. The search of a realistic value for the SDL is the objective of the statistical thermal design methods. In this report, we apply a full statistical approach to define the DNBR criterion or SDL (Statistical Design Limit) with the strict observance of the design criteria defined in the Standard Review Plan. The same statistical approach is used to define the expected number of rods experiencing DNB. (author)

  19. Analytical and statistical analysis of elemental composition of lichens

    International Nuclear Information System (INIS)

    Calvelo, S.; Baccala, N.; Bubach, D.; Arribere, M.A.; Riberio Guevara, S.

    1997-01-01

    The elemental composition of lichens from remote southern South America regions has been studied with analytical and statistical techniques to determine if the values obtained reflect species, growth forms or habitat characteristics. The enrichment factors are calculated discriminated by species and collection site and compared with data available in the literature. The elemental concentrations are standardized and compared for different species. The information was statistically processed, a cluster analysis was performed using the three first principal axes of the PCA; the three groups formed are presented. Their relationship with the species, collection sites and the lichen growth forms are interpreted. (author)

  20. The Fusion of Financial Analysis and Seismology: Statistical Methods from Financial Market Analysis Applied to Earthquake Data

    Science.gov (United States)

    Ohyanagi, S.; Dileonardo, C.

    2013-12-01

    As a natural phenomenon earthquake occurrence is difficult to predict. Statistical analysis of earthquake data was performed using candlestick chart and Bollinger Band methods. These statistical methods, commonly used in the financial world to analyze market trends were tested against earthquake data. Earthquakes above Mw 4.0 located on shore of Sanriku (37.75°N ~ 41.00°N, 143.00°E ~ 144.50°E) from February 1973 to May 2013 were selected for analysis. Two specific patterns in earthquake occurrence were recognized through the analysis. One is a spread of candlestick prior to the occurrence of events greater than Mw 6.0. A second pattern shows convergence in the Bollinger Band, which implies a positive or negative change in the trend of earthquakes. Both patterns match general models for the buildup and release of strain through the earthquake cycle, and agree with both the characteristics of the candlestick chart and Bollinger Band analysis. These results show there is a high correlation between patterns in earthquake occurrence and trend analysis by these two statistical methods. The results of this study agree with the appropriateness of the application of these financial analysis methods to the analysis of earthquake occurrence.

  1. Parametric analysis of the statistical model of the stick-slip process

    Science.gov (United States)

    Lima, Roberta; Sampaio, Rubens

    2017-06-01

    In this paper it is performed a parametric analysis of the statistical model of the response of a dry-friction oscillator. The oscillator is a spring-mass system which moves over a base with a rough surface. Due to this roughness, the mass is subject to a dry-frictional force modeled as a Coulomb friction. The system is stochastically excited by an imposed bang-bang base motion. The base velocity is modeled by a Poisson process for which a probabilistic model is fully specified. The excitation induces in the system stochastic stick-slip oscillations. The system response is composed by a random sequence alternating stick and slip-modes. With realizations of the system, a statistical model is constructed for this sequence. In this statistical model, the variables of interest of the sequence are modeled as random variables, as for example, the number of time intervals in which stick or slip occur, the instants at which they begin, and their duration. Samples of the system response are computed by integration of the dynamic equation of the system using independent samples of the base motion. Statistics and histograms of the random variables which characterize the stick-slip process are estimated for the generated samples. The objective of the paper is to analyze how these estimated statistics and histograms vary with the system parameters, i.e., to make a parametric analysis of the statistical model of the stick-slip process.

  2. Introduction to applied statistical signal analysis guide to biomedical and electrical engineering applications

    CERN Document Server

    Shiavi, Richard

    2007-01-01

    Introduction to Applied Statistical Signal Analysis is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech.Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical

  3. Visual and statistical analysis of {sup 18}F-FDG PET in primary progressive aphasia

    Energy Technology Data Exchange (ETDEWEB)

    Matias-Guiu, Jordi A.; Moreno-Ramos, Teresa; Garcia-Ramos, Rocio; Fernandez-Matarrubia, Marta; Oreja-Guevara, Celia; Matias-Guiu, Jorge [Hospital Clinico San Carlos, Department of Neurology, Madrid (Spain); Cabrera-Martin, Maria Nieves; Perez-Castejon, Maria Jesus; Rodriguez-Rey, Cristina; Ortega-Candil, Aida; Carreras, Jose Luis [San Carlos Health Research Institute (IdISSC) Complutense University of Madrid, Department of Nuclear Medicine, Hospital Clinico San Carlos, Madrid (Spain)

    2015-05-01

    Diagnosing progressive primary aphasia (PPA) and its variants is of great clinical importance, and fluorodeoxyglucose (FDG) positron emission tomography (PET) may be a useful diagnostic technique. The purpose of this study was to evaluate interobserver variability in the interpretation of FDG PET images in PPA as well as the diagnostic sensitivity and specificity of the technique. We also aimed to compare visual and statistical analyses of these images. There were 10 raters who analysed 44 FDG PET scans from 33 PPA patients and 11 controls. Five raters analysed the images visually, while the other five used maps created using Statistical Parametric Mapping software. Two spatial normalization procedures were performed: global mean normalization and cerebellar normalization. Clinical diagnosis was considered the gold standard. Inter-rater concordance was moderate for visual analysis (Fleiss' kappa 0.568) and substantial for statistical analysis (kappa 0.756-0.881). Agreement was good for all three variants of PPA except for the nonfluent/agrammatic variant studied with visual analysis. The sensitivity and specificity of each rater's diagnosis of PPA was high, averaging 87.8 and 89.9 % for visual analysis and 96.9 and 90.9 % for statistical analysis using global mean normalization, respectively. In cerebellar normalization, sensitivity was 88.9 % and specificity 100 %. FDG PET demonstrated high diagnostic accuracy for the diagnosis of PPA and its variants. Inter-rater concordance was higher for statistical analysis, especially for the nonfluent/agrammatic variant. These data support the use of FDG PET to evaluate patients with PPA and show that statistical analysis methods are particularly useful for identifying the nonfluent/agrammatic variant of PPA. (orig.)

  4. PVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool

    KAUST Repository

    AlTurki, Musab

    2011-01-01

    Statistical model checking is an attractive formal analysis method for probabilistic systems such as, for example, cyber-physical systems which are often probabilistic in nature. This paper is about drastically increasing the scalability of statistical model checking, and making such scalability of analysis available to tools like Maude, where probabilistic systems can be specified at a high level as probabilistic rewrite theories. It presents PVeStA, an extension and parallelization of the VeStA statistical model checking tool [10]. PVeStA supports statistical model checking of probabilistic real-time systems specified as either: (i) discrete or continuous Markov Chains; or (ii) probabilistic rewrite theories in Maude. Furthermore, the properties that it can model check can be expressed in either: (i) PCTL/CSL, or (ii) the QuaTEx quantitative temporal logic. As our experiments show, the performance gains obtained from parallelization can be very high. © 2011 Springer-Verlag.

  5. Statistical analysis of extreme values from insurance, finance, hydrology and other fields

    CERN Document Server

    Reiss, Rolf-Dieter

    1997-01-01

    The statistical analysis of extreme data is important for various disciplines, including hydrology, insurance, finance, engineering and environmental sciences. This book provides a self-contained introduction to the parametric modeling, exploratory analysis and statistical interference for extreme values. The entire text of this third edition has been thoroughly updated and rearranged to meet the new requirements. Additional sections and chapters, elaborated on more than 100 pages, are particularly concerned with topics like dependencies, the conditional analysis and the multivariate modeling of extreme data. Parts I–III about the basic extreme value methodology remain unchanged to some larger extent, yet notable are, e.g., the new sections about "An Overview of Reduced-Bias Estimation" (co-authored by M.I. Gomes), "The Spectral Decomposition Methodology", and "About Tail Independence" (co-authored by M. Frick), and the new chapter about "Extreme Value Statistics of Dependent Random Variables" (co-authored ...

  6. Power flow as a complement to statistical energy analysis and finite element analysis

    Science.gov (United States)

    Cuschieri, J. M.

    1987-01-01

    Present methods of analysis of the structural response and the structure-borne transmission of vibrational energy use either finite element (FE) techniques or statistical energy analysis (SEA) methods. The FE methods are a very useful tool at low frequencies where the number of resonances involved in the analysis is rather small. On the other hand SEA methods can predict with acceptable accuracy the response and energy transmission between coupled structures at relatively high frequencies where the structural modal density is high and a statistical approach is the appropriate solution. In the mid-frequency range, a relatively large number of resonances exist which make finite element method too costly. On the other hand SEA methods can only predict an average level form. In this mid-frequency range a possible alternative is to use power flow techniques, where the input and flow of vibrational energy to excited and coupled structural components can be expressed in terms of input and transfer mobilities. This power flow technique can be extended from low to high frequencies and this can be integrated with established FE models at low frequencies and SEA models at high frequencies to form a verification of the method. This method of structural analysis using power flo and mobility methods, and its integration with SEA and FE analysis is applied to the case of two thin beams joined together at right angles.

  7. Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems

    Science.gov (United States)

    He, Yuning; Davies, Misty Dawn

    2014-01-01

    The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.

  8. Maternal satisfaction as an outcome criterion in research on labor analgesia: data analysis from the recent literature.

    Science.gov (United States)

    Dualé, Christian; Nicolas-Courbon, Aurélie; Gerbaud, Laurent; Lemery, Didier; Bonnin, Martine; Pereira, Bruno

    2015-03-01

    To investigate whether maternal satisfaction (MS) is taken into consideration as an outcome criterion in clinical research on analgesia for labor. A systematic review of articles reporting analgesia for labor from a panel of 17 influential journals was undertaken. A total of 116 articles were analyzed, including 282 within-study groups. The scope of MS, the type of outcome measure used, and the time of measurement were noted. Each available observation was assigned an ordinal value of MS (ordMS), according to data distribution. The factors influencing ordMS were identified by multivariable analysis. The methods used to assess MS were very variable, even within the different measurement tools reported. The weighted distribution of ordMS was 17.8%, 21.8%, 31.2%, and 29.3% for levels "poor," "fair," "good," and "excellent," respectively. In comparative studies, statistical differences for analgesia were related to statistical differences for MS (Pvalue was high (0.87). Power to detect a difference in MS between treatment groups was low in general, but it influenced reporting of a significant difference for MS (Pinitial cervical dilatation, and the within-study percentage of nulliparous women. The techniques alternative to epidural analgesia negatively influenced ordMS. A standard and validated tool to assess MS in clinical research on analgesia for labor is still to be developed. Power should be improved by acting on sample sizes or sensitivity of the outcome.

  9. Validation of statistical models for creep rupture by parametric analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bolton, J., E-mail: john.bolton@uwclub.net [65, Fisher Ave., Rugby, Warks CV22 5HW (United Kingdom)

    2012-01-15

    Statistical analysis is an efficient method for the optimisation of any candidate mathematical model of creep rupture data, and for the comparative ranking of competing models. However, when a series of candidate models has been examined and the best of the series has been identified, there is no statistical criterion to determine whether a yet more accurate model might be devised. Hence there remains some uncertainty that the best of any series examined is sufficiently accurate to be considered reliable as a basis for extrapolation. This paper proposes that models should be validated primarily by parametric graphical comparison to rupture data and rupture gradient data. It proposes that no mathematical model should be considered reliable for extrapolation unless the visible divergence between model and data is so small as to leave no apparent scope for further reduction. This study is based on the data for a 12% Cr alloy steel used in BS PD6605:1998 to exemplify its recommended statistical analysis procedure. The models considered in this paper include a) a relatively simple model, b) the PD6605 recommended model and c) a more accurate model of somewhat greater complexity. - Highlights: Black-Right-Pointing-Pointer The paper discusses the validation of creep rupture models derived from statistical analysis. Black-Right-Pointing-Pointer It demonstrates that models can be satisfactorily validated by a visual-graphic comparison of models to data. Black-Right-Pointing-Pointer The method proposed utilises test data both as conventional rupture stress and as rupture stress gradient. Black-Right-Pointing-Pointer The approach is shown to be more reliable than a well-established and widely used method (BS PD6605).

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

    Science.gov (United States)

    Kruschke, John K; Liddell, Torrin M

    2018-02-01

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

  11. Prediction of surgical outcome in compressive cervical myelopathy: A novel clinicoradiological prognostic score

    Directory of Open Access Journals (Sweden)

    Rishi Anil Aggarwal

    2016-01-01

    Full Text Available Context: Preoperative severity of myelopathy, age, and duration of symptoms have been shown to be highly predictive of the outcome in compressive cervical myelopathy (CCM. The role of radiological parameters is still controversial. Aims: Define the prognostic factors in CCM and formulate a prognostic score to predict the outcome following surgery in CCM. Settings and Design: Retrospective. Materials and Methods: This study included 78 consecutive patients with CCM treated surgically. The modified Japanese Orthopaedic Association (mJOA scale was used to quantify severity of myelopathy at admission and at 12-month follow-up. The outcome was defined as "good" if the patient had mJOA score ≥16 and "poor" if the score was <16. Age, sex, duration of symptoms, comorbidities, intrinsic hand muscle wasting (IHMW, diagnosis, surgical technique, Torg ratio, instability on dynamic radiographs, and magnetic resonance imaging (MRI signal intensity changes were assessed. Statistics: Statistical Package for the Social Sciences (SPSS (version 20.0 was used for statistical analysis. The association was assessed amongst variables using logistic regression analysis. Parameters having a statistically significant correlation with the outcome were included in formulating a prognostic score. Results: Severity of myelopathy, IHMW, age, duration, diabetes, and instability on radiographs were predictive of the outcome with a P value <0.01. Genders, diagnosis, surgical procedure, Torg ratio, and intensity changes on MRI were not significantly related to the outcome. A 8-point scoring system was devised incorporating the significant clinicoradiological parameters, and it was found that nearly all patients (97.82% with a score below 5 had good outcome and all patients (100% with a score above 5 had poor outcome. The outcome is difficult to predict with a score of 5. Conclusions: Clinical parameters are better predictors of the outcome as compared to radiological findings

  12. Statistical analysis of solar proton events

    Directory of Open Access Journals (Sweden)

    V. Kurt

    2004-06-01

    Full Text Available A new catalogue of 253 solar proton events (SPEs with energy >10MeV and peak intensity >10 protons/cm2.s.sr (pfu at the Earth's orbit for three complete 11-year solar cycles (1970-2002 is given. A statistical analysis of this data set of SPEs and their associated flares that occurred during this time period is presented. It is outlined that 231 of these proton events are flare related and only 22 of them are not associated with Ha flares. It is also noteworthy that 42 of these events are registered as Ground Level Enhancements (GLEs in neutron monitors. The longitudinal distribution of the associated flares shows that a great number of these events are connected with west flares. This analysis enables one to understand the long-term dependence of the SPEs and the related flare characteristics on the solar cycle which are useful for space weather prediction.

  13. STATISTICAL ANALYSIS OF THE HEAVY NEUTRAL ATOMS MEASURED BY IBEX

    International Nuclear Information System (INIS)

    Park, Jeewoo; Kucharek, Harald; Möbius, Eberhard; Galli, André; Livadiotis, George; Fuselier, Steve A.; McComas, David J.

    2015-01-01

    We investigate the directional distribution of heavy neutral atoms in the heliosphere by using heavy neutral maps generated with the IBEX-Lo instrument over three years from 2009 to 2011. The interstellar neutral (ISN) O and Ne gas flow was found in the first-year heavy neutral map at 601 keV and its flow direction and temperature were studied. However, due to the low counting statistics, researchers have not treated the full sky maps in detail. The main goal of this study is to evaluate the statistical significance of each pixel in the heavy neutral maps to get a better understanding of the directional distribution of heavy neutral atoms in the heliosphere. Here, we examine three statistical analysis methods: the signal-to-noise filter, the confidence limit method, and the cluster analysis method. These methods allow us to exclude background from areas where the heavy neutral signal is statistically significant. These methods also allow the consistent detection of heavy neutral atom structures. The main emission feature expands toward lower longitude and higher latitude from the observational peak of the ISN O and Ne gas flow. We call this emission the extended tail. It may be an imprint of the secondary oxygen atoms generated by charge exchange between ISN hydrogen atoms and oxygen ions in the outer heliosheath

  14. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models

    Science.gov (United States)

    Gelfand, Lois A.; MacKinnon, David P.; DeRubeis, Robert J.; Baraldi, Amanda N.

    2016-01-01

    Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results. PMID:27065906

  15. Explorations in statistics: the analysis of ratios and normalized data.

    Science.gov (United States)

    Curran-Everett, Douglas

    2013-09-01

    Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This ninth installment of Explorations in Statistics explores the analysis of ratios and normalized-or standardized-data. As researchers, we compute a ratio-a numerator divided by a denominator-to compute a proportion for some biological response or to derive some standardized variable. In each situation, we want to control for differences in the denominator when the thing we really care about is the numerator. But there is peril lurking in a ratio: only if the relationship between numerator and denominator is a straight line through the origin will the ratio be meaningful. If not, the ratio will misrepresent the true relationship between numerator and denominator. In contrast, regression techniques-these include analysis of covariance-are versatile: they can accommodate an analysis of the relationship between numerator and denominator when a ratio is useless.

  16. Renal mass anatomic characteristics and perioperative outcomes of laparoscopic partial nephrectomy: a critical analysis.

    Science.gov (United States)

    Tsivian, Matvey; Ulusoy, Said; Abern, Michael; Wandel, Ayelet; Sidi, A Ami; Tsivian, Alexander

    2012-10-01

    Anatomic parameters determining renal mass complexity have been used in a number of proposed scoring systems despite lack of a critical analysis of their independent contributions. We sought to assess the independent contribution of anatomic parameters on perioperative outcomes of laparoscopic partial nephrectomy (LPN). Preoperative imaging studies were reviewed for 147 consecutive patients undergoing LPN for a single renal mass. Renal mass anatomy was recorded: Size, growth pattern (endo-/meso-/exophytic), centrality (central/hilar/peripheral), anterior/posterior, lateral/medial, polar location. Multivariable models were used to determine associations of anatomic parameters with warm ischemia time (WIT), operative time (OT), estimated blood loss (EBL), intra- and postoperative complications, as well as renal function. All models were adjusted for the learning curve and relevant confounders. Median (range) tumor size was 3.3 cm (1.5-11 cm); 52% were central and 14% hilar. While 44% were exophytic, 23% and 33% were mesophytic and endophytic, respectively. Anatomic parameters did not uniformly predict perioperative outcomes. WIT was associated with tumor size (P=0.068), centrality (central, P=0.016; hilar, P=0.073), and endophytic growth pattern (P=0.017). OT was only associated with tumor size (Panatomic parameter predicted EBL. Tumor centrality increased the odds of overall and intraoperative complications, without reaching statistical significance. Postoperative renal function was not associated with any of the anatomic parameters considered after adjustment for baseline function and WIT. Learning curve, considered as a confounder, was independently associated with reduced WIT and OT as well as reduced odds of intraoperative complications. This study provides a detailed analysis of the independent impact of renal mass anatomic parameters on perioperative outcomes. Our findings suggest diverse independent contributions of the anatomic parameters to the

  17. Parametric statistical change point analysis

    CERN Document Server

    Chen, Jie

    2000-01-01

    This work is an in-depth study of the change point problem from a general point of view and a further examination of change point analysis of the most commonly used statistical models Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several The exposition is clear and systematic, with a great deal of introductory material included Different models are presented in each chapter, including gamma and exponential models, rarely examined thus far in the literature Other models covered in detail are the multivariate normal, univariate normal, regression, and discrete models Extensive examples throughout the text emphasize key concepts and different methodologies are used, namely the likelihood ratio criterion, and the Bayesian and information criterion approaches A comprehensive bibliography and two indices complete the study

  18. Perceptual and statistical analysis of cardiac phase and amplitude images

    International Nuclear Information System (INIS)

    Houston, A.; Craig, A.

    1991-01-01

    A perceptual experiment was conducted using cardiac phase and amplitude images. Estimates of statistical parameters were derived from the images and the diagnostic potential of human and statistical decisions compared. Five methods were used to generate the images from 75 gated cardiac studies, 39 of which were classified as pathological. The images were presented to 12 observers experienced in nuclear medicine. The observers rated the images using a five-category scale based on their confidence of an abnormality presenting. Circular and linear statistics were used to analyse phase and amplitude image data, respectively. Estimates of mean, standard deviation (SD), skewness, kurtosis and the first term of the spatial correlation function were evaluated in the region of the left ventricle. A receiver operating characteristic analysis was performed on both sets of data and the human and statistical decisions compared. For phase images, circular SD was shown to discriminate better between normal and abnormal than experienced observers, but no single statistic discriminated as well as the human observer for amplitude images. (orig.)

  19. Role of statistics in characterizing nuclear waste package behavior

    International Nuclear Information System (INIS)

    Bowen, W.M.

    1984-11-01

    The characterization of nuclear waste package behavior is primarily based on the outcome of laboratory tests, where components of a proposed waste package are either individually or simultaneously subjected to simulated repository conditions. At each step of a testing method, both controllable and uncontrollable factors contribute to the overall uncertainty in the final outcome of the test. If not dealt with correctly, these sources of uncertainty could obscure or distort important information that might otherwise be gleaned from the test data. This could result in misleading or erroneous conclusions about the behavior characteristic being studied. It could also preclude estimation of the individual contributions of the major sources of uncertainty to the overall uncertainty. Statistically designed experiments and sampling plans, followed by correctly applied statistical analysis and estimation methods will yield the most information possible for the time and resources spent on experimentation, and they can eliminate the above concerns. Conclusions reached on the basis of such information will be sound and defensible. This presentation is intended to emphasize the importance of correctly applied, theoretically sound statistical methodology in characterizing nuclear waste package behavior. 8 references, 1 table

  20. Role of statistics in characterizing nuclear waste package behavior

    International Nuclear Information System (INIS)

    Bowen, W.M.

    1984-01-01

    The characterization of nuclear waste package behavior is primarily based on the outcome of laboratory tests, where components of a proposed waste package are either individually or simultaneously subjected to simulated repository conditions. At each step of a testing method, both controllable and uncontrollable factors contribute to the overall uncertainty in the final outcome of the test. If not dealt with correctly, these sources of uncertainty could obscure or distort important information that might otherwise be gleaned form the test data. This could result in misleading or erroneous conclusions about the behavior characteristic being studied. It could also preclude estimation of the individual contributions of the major sources of uncertainty to the overall uncertainty. Statistically designed experiments and sampling plans, followed by correctly applied statistical analysis and estimation methods will yield the most information possible for the time and resources spent on experimentation, and they can eliminate the above concerns. Conclusions reached on the basis of such information will be sound and defensible. This presentation is intended to emphasize the importance of correctly applied, theoretically sound statistical methodology in characterizing nuclear waste package behavior

  1. Statistical analysis of the count and profitability of air conditioners.

    Science.gov (United States)

    Rady, El Houssainy A; Mohamed, Salah M; Abd Elmegaly, Alaa A

    2018-08-01

    This article presents the statistical analysis of the number and profitability of air conditioners in an Egyptian company. Checking the same distribution for each categorical variable has been made using Kruskal-Wallis test.

  2. metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.

    Science.gov (United States)

    Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

    2016-07-01

    A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  3. Statistical Analysis of the Exchange Rate of Bitcoin.

    Science.gov (United States)

    Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen

    2015-01-01

    Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.

  4. Statistical analysis and Monte Carlo simulation of growing self-avoiding walks on percolation

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Yuxia [Department of Physics, Wuhan University, Wuhan 430072 (China); Sang Jianping [Department of Physics, Wuhan University, Wuhan 430072 (China); Department of Physics, Jianghan University, Wuhan 430056 (China); Zou Xianwu [Department of Physics, Wuhan University, Wuhan 430072 (China)]. E-mail: xwzou@whu.edu.cn; Jin Zhunzhi [Department of Physics, Wuhan University, Wuhan 430072 (China)

    2005-09-26

    The two-dimensional growing self-avoiding walk on percolation was investigated by statistical analysis and Monte Carlo simulation. We obtained the expression of the mean square displacement and effective exponent as functions of time and percolation probability by statistical analysis and made a comparison with simulations. We got a reduced time to scale the motion of walkers in growing self-avoiding walks on regular and percolation lattices.

  5. General specifications for the development of a USL NASA PC R and D statistical analysis support package

    Science.gov (United States)

    Dominick, Wayne D. (Editor); Bassari, Jinous; Triantafyllopoulos, Spiros

    1984-01-01

    The University of Southwestern Louisiana (USL) NASA PC R and D statistical analysis support package is designed to be a three-level package to allow statistical analysis for a variety of applications within the USL Data Base Management System (DBMS) contract work. The design addresses usage of the statistical facilities as a library package, as an interactive statistical analysis system, and as a batch processing package.

  6. Conceptual basis of outcome measures.

    Science.gov (United States)

    Keith, R A

    1995-01-01

    Because of its treatment configuration and the assumption of long-term benefit, rehabilitation has had a continuing interest in the measurement of outcomes. The utility of outcome indicators rests on their conceptual foundations, the technical development of measures and validation research. Some measures, particularly of functional status, have become increasingly sophisticated with the application of psychometric and statistical analysis techniques. Less effort has been devoted to an elaboration of their theoretical basis. A first step is an examination of the assumptions underlying outcome measures, the purpose of this article. Central to an understanding is clarification of definitions of key terms such as outcomes, independence, impairment, disability and handicap. All outcome measures must be seen as part of a social context of norms and expectations. However, most norms in rehabilitation are implied rather than explicit. The assumptions behind several common outcomes are examined with suggestions for ways to increase their utility. The ability of rehabilitation to compete in the current climate, stressing cost-effectiveness, will depend heavily on the robustness of outcome measures.

  7. A method for statistical steady state thermal analysis of reactor cores

    International Nuclear Information System (INIS)

    Whetton, P.A.

    1981-01-01

    In a previous publication the author presented a method for undertaking statistical steady state thermal analyses of reactor cores. The present paper extends the technique to an assessment of confidence limits for the resulting probability functions which define the probability that a given thermal response value will be exceeded in a reactor core. Establishing such confidence limits is considered an integral part of any statistical thermal analysis and essential if such analysis are to be considered in any regulatory process. In certain applications the use of a best estimate probability function may be justifiable but it is recognised that a demonstrably conservative probability function is required for any regulatory considerations. (orig.)

  8. A statistical test for outlier identification in data envelopment analysis

    Directory of Open Access Journals (Sweden)

    Morteza Khodabin

    2010-09-01

    Full Text Available In the use of peer group data to assess individual, typical or best practice performance, the effective detection of outliers is critical for achieving useful results. In these ‘‘deterministic’’ frontier models, statistical theory is now mostly available. This paper deals with the statistical pared sample method and its capability of detecting outliers in data envelopment analysis. In the presented method, each observation is deleted from the sample once and the resulting linear program is solved, leading to a distribution of efficiency estimates. Based on the achieved distribution, a pared test is designed to identify the potential outlier(s. We illustrate the method through a real data set. The method could be used in a first step, as an exploratory data analysis, before using any frontier estimation.

  9. Radar Derived Spatial Statistics of Summer Rain. Volume 2; Data Reduction and Analysis

    Science.gov (United States)

    Konrad, T. G.; Kropfli, R. A.

    1975-01-01

    Data reduction and analysis procedures are discussed along with the physical and statistical descriptors used. The statistical modeling techniques are outlined and examples of the derived statistical characterization of rain cells in terms of the several physical descriptors are presented. Recommendations concerning analyses which can be pursued using the data base collected during the experiment are included.

  10. Quality in statistics education : Determinants of course outcomes in methods & statistics education at universities and colleges

    NARCIS (Netherlands)

    Verhoeven, P.S.

    2009-01-01

    Although Statistics is not a very popular course according to most students, a majority of students still take it, as it is mandatory at most Social Science departments. Therefore it takes special teacher’s skills to teach statistics. In order to do so it is essential for teachers to know what

  11. Analysis of clinical features and visual outcomes of pars planitis.

    Science.gov (United States)

    Berker, Nilufer; Sen, Emine; Elgin, Ufuk; Atilgan, Cemile Ucgul; Dursun, Erdem; Yilmazbas, Pelin

    2018-04-01

    To evaluate the demographic characteristics, clinical features, treatment and outcomes of patients with pars planitis in a tertiary referral center in Turkey. Medical records of patients with pars planitis were retrospectively reviewed. The data including demographic and ocular features and treatment outcomes were recorded. The distribution of clinical findings and complications were evaluated according to age and gender groups. The changes in final BCVA compared to the initial BCVA were noted. Statistical analysis was performed using SPSS software (Version 18.0, SPSS Inc., Chicago, USA). Twenty-seven patients (54 eyes) were included in this study. 16 patients were male (59.3%), and 11 were female (40.7%). Mean age at diagnosis was 12.84 ± 8.26 (range 4-36) years. Mean follow-up period was 61.3 ± 52.15 (range 9-172) months. Mean BCVA was 0.58 ± 0.36 (range 0.03-1.00) (0.40 ± 0.45 logMAR) at presentation, and 0.81 ± 0.28 (range 0.10-1.00) (0.14 ± 0.27 logMAR) at final visit (P = 0.001). Vitreous inflammation (100%), vitreous haze (92.6%), snowballs (74.1%), snowbanks (66.7%), anterior chamber cells (66.7%) and peripheral retinal vascular sheathing (48.1%) were the most common presentations. Ocular complications included vitreous condensation (51.9%), cystoid macular edema (22.2%), cataract (18.5%), inferior peripheral retinal detachment (11.1%), glaucoma (5.6%) and vitreous hemorrhage (3.7%). Treatments included topical, periocular, intravitreal and systemic corticosteroids, immunosuppressives, peripheral laser photocoagulation and pars plana vitrectomy when needed. Pars planitis is an idiopathic chronic intermediate uveitis mostly affecting children and adolescents. In spite of its chronic nature with high potential of causing ocular complications, adequate treatment and close follow-up lead to favorable visual outcomes.

  12. Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance

    Science.gov (United States)

    Glascock, M. D.; Neff, H.; Vaughn, K. J.

    2004-06-01

    The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.

  13. Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance

    International Nuclear Information System (INIS)

    Glascock, M. D.; Neff, H.; Vaughn, K. J.

    2004-01-01

    The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.

  14. Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance

    Energy Technology Data Exchange (ETDEWEB)

    Glascock, M. D.; Neff, H. [University of Missouri, Research Reactor Center (United States); Vaughn, K. J. [Pacific Lutheran University, Department of Anthropology (United States)

    2004-06-15

    The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.

  15. Statistical analysis and data management

    International Nuclear Information System (INIS)

    Anon.

    1981-01-01

    This report provides an overview of the history of the WIPP Biology Program. The recommendations of the American Institute of Biological Sciences (AIBS) for the WIPP biology program are summarized. The data sets available for statistical analyses and problems associated with these data sets are also summarized. Biological studies base maps are presented. A statistical model is presented to evaluate any correlation between climatological data and small mammal captures. No statistically significant relationship between variance in small mammal captures on Dr. Gennaro's 90m x 90m grid and precipitation records from the Duval Potash Mine were found

  16. Detecting errors in micro and trace analysis by using statistics

    DEFF Research Database (Denmark)

    Heydorn, K.

    1993-01-01

    By assigning a standard deviation to each step in an analytical method it is possible to predict the standard deviation of each analytical result obtained by this method. If the actual variability of replicate analytical results agrees with the expected, the analytical method is said...... to be in statistical control. Significant deviations between analytical results from different laboratories reveal the presence of systematic errors, and agreement between different laboratories indicate the absence of systematic errors. This statistical approach, referred to as the analysis of precision, was applied...

  17. Multiple thrombophilic single nucleotide polymorphisms lack a significant effect on outcomes in fresh IVF cycles: an analysis of 1717 patients.

    Science.gov (United States)

    Patounakis, George; Bergh, Eric; Forman, Eric J; Tao, Xin; Lonczak, Agnieszka; Franasiak, Jason M; Treff, Nathan; Scott, Richard T

    2016-01-01

    The aim of the study is to determine if thrombophilic single nucleotide polymorphisms (SNPs) affect outcomes in fresh in vitro fertilization (IVF) cycles in a large general infertility population. A prospective cohort analysis was performed at a university-affiliated private IVF center of female patients undergoing fresh non-donor IVF cycles. The effect of the following thrombophilic SNPs on IVF outcomes were explored: factor V (Leiden and H1299R), prothrombin (G20210A), factor XIII (V34L), β-fibrinogen (-455G → A), plasminogen activator inhibitor-1 (4G/5G), human platelet antigen-1 (a/b9L33P), and methylenetetrahydrofolate reductase (C677T and A1298C). The main outcome measures included positive pregnancy test, clinical pregnancy, embryo implantation, live birth, and pregnancy loss. Patients (1717) were enrolled in the study, and a total of 4169 embryos were transferred. There were no statistically significant differences in positive pregnancy test, clinical pregnancy, embryo implantation, live birth, or pregnancy loss in the analysis of 1717 patients attempting their first cycle of IVF. Receiver operator characteristics and logistic regression analyses showed that outcomes cannot be predicted by the cumulative number of thrombophilic mutations present in the patient. Individual and cumulative thrombophilic SNPs do not affect IVF outcomes. Therefore, initial screening for these SNPs is not indicated.

  18. Rosiglitazone evaluated for cardiovascular outcomes--an interim analysis

    DEFF Research Database (Denmark)

    Home, Philip D; Pocock, Stuart J; Beck-Nielsen, Henning

    2007-01-01

    BACKGROUND: A recent meta-analysis raised concern regarding an increased risk of myocardial infarction and death from cardiovascular causes associated with rosiglitazone treatment of type 2 diabetes. METHODS: We conducted an unplanned interim analysis of a randomized, multicenter, open...... group). The primary end point was hospitalization or death from cardiovascular causes. RESULTS: Because the mean follow-up was only 3.75 years, our interim analysis had limited statistical power to detect treatment differences. A total of 217 patients in the rosiglitazone group and 202 patients...... in the control group had the adjudicated primary end point (hazard ratio, 1.08; 95% confidence interval [CI], 0.89 to 1.31). After the inclusion of end points pending adjudication, the hazard ratio was 1.11 (95% CI, 0.93 to 1.32). There were no statistically significant differences between the rosiglitazone...

  19. Statistical analysis of the BOIL program in RSYST-III

    International Nuclear Information System (INIS)

    Beck, W.; Hausch, H.J.

    1978-11-01

    The paper describes a statistical analysis in the RSYST-III program system. Using the example of the BOIL program, it is shown how the effects of inaccurate input data on the output data can be discovered. The existing possibilities of data generation, data handling, and data evaluation are outlined. (orig.) [de

  20. Continuous Acetylsalicylic Acid Treatment Does Not Influence Bleeding Pattern or Outcome of Aneurysmal Subarachnoid Hemorrhage: A Matched-Pair Analysis.

    Science.gov (United States)

    Bruder, Markus; Won, Sae-Yeon; Wagner, Marlies; Brawanski, Nina; Dinc, Nazife; Kashefiolasl, Sepide; Seifert, Volker; Konczalla, Juergen

    2018-05-01

    Demographic changes are leading to an aging society with a growing number of patients with cardiovascular diseases, relying on antiplatelet drugs like acetylsalicylic acid (ASA). Although antiplatelet agents are suspected to be protective not only in the cardiologic but in the neurovascular field, the alteration of the coagulating process could have a major impact on the course and outcome after rupture of intracranial aneurysms. Between June 1999 and December 2014, 1422 patients were treated for aneurysmal SAH in our institution, 144 (10.1%) with continuous ASA at the time of aneurysm rupture. A matched-pair analysis was performed. The rate of patients with continuous ASA treatment while rupture of the aneurysm is rising significantly (P bleeding pattern. Outcome was not different in the matched-pair analysis. There was no statistical difference in treatment related-complication rates of microsurgical and endovascular procedures. Therefore, ASA use should not influence treatment decision of the ruptured aneurysm. Copyright © 2018 Elsevier Inc. All rights reserved.

  1. Multivariate statistical analysis of precipitation chemistry in Northwestern Spain

    International Nuclear Information System (INIS)

    Prada-Sanchez, J.M.; Garcia-Jurado, I.; Gonzalez-Manteiga, W.; Fiestras-Janeiro, M.G.; Espada-Rios, M.I.; Lucas-Dominguez, T.

    1993-01-01

    149 samples of rainwater were collected in the proximity of a power station in northwestern Spain at three rainwater monitoring stations. The resulting data are analyzed using multivariate statistical techniques. Firstly, the Principal Component Analysis shows that there are three main sources of pollution in the area (a marine source, a rural source and an acid source). The impact from pollution from these sources on the immediate environment of the stations is studied using Factorial Discriminant Analysis. 8 refs., 7 figs., 11 tabs

  2. Multivariate statistical analysis of precipitation chemistry in Northwestern Spain

    Energy Technology Data Exchange (ETDEWEB)

    Prada-Sanchez, J.M.; Garcia-Jurado, I.; Gonzalez-Manteiga, W.; Fiestras-Janeiro, M.G.; Espada-Rios, M.I.; Lucas-Dominguez, T. (University of Santiago, Santiago (Spain). Faculty of Mathematics, Dept. of Statistics and Operations Research)

    1993-07-01

    149 samples of rainwater were collected in the proximity of a power station in northwestern Spain at three rainwater monitoring stations. The resulting data are analyzed using multivariate statistical techniques. Firstly, the Principal Component Analysis shows that there are three main sources of pollution in the area (a marine source, a rural source and an acid source). The impact from pollution from these sources on the immediate environment of the stations is studied using Factorial Discriminant Analysis. 8 refs., 7 figs., 11 tabs.

  3. SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

    Science.gov (United States)

    Kiang, Julie E.; Flynn, Kate; Zhai, Tong; Hummel, Paul; Granato, Gregory

    2018-03-07

    This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.

  4. Daniel Goodman’s empirical approach to Bayesian statistics

    Science.gov (United States)

    Gerrodette, Tim; Ward, Eric; Taylor, Rebecca L.; Schwarz, Lisa K.; Eguchi, Tomoharu; Wade, Paul; Himes Boor, Gina

    2016-01-01

    Bayesian statistics, in contrast to classical statistics, uses probability to represent uncertainty about the state of knowledge. Bayesian statistics has often been associated with the idea that knowledge is subjective and that a probability distribution represents a personal degree of belief. Dr. Daniel Goodman considered this viewpoint problematic for issues of public policy. He sought to ground his Bayesian approach in data, and advocated the construction of a prior as an empirical histogram of “similar” cases. In this way, the posterior distribution that results from a Bayesian analysis combined comparable previous data with case-specific current data, using Bayes’ formula. Goodman championed such a data-based approach, but he acknowledged that it was difficult in practice. If based on a true representation of our knowledge and uncertainty, Goodman argued that risk assessment and decision-making could be an exact science, despite the uncertainties. In his view, Bayesian statistics is a critical component of this science because a Bayesian analysis produces the probabilities of future outcomes. Indeed, Goodman maintained that the Bayesian machinery, following the rules of conditional probability, offered the best legitimate inference from available data. We give an example of an informative prior in a recent study of Steller sea lion spatial use patterns in Alaska.

  5. Anomalous heat transfer modes of nanofluids: a review based on statistical analysis

    Science.gov (United States)

    2011-01-01

    This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids. PMID:21711932

  6. Anomalous heat transfer modes of nanofluids: a review based on statistical analysis

    Science.gov (United States)

    Sergis, Antonis; Hardalupas, Yannis

    2011-05-01

    This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids.

  7. Anomalous heat transfer modes of nanofluids: a review based on statistical analysis

    Directory of Open Access Journals (Sweden)

    Sergis Antonis

    2011-01-01

    Full Text Available Abstract This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids.

  8. Modeling of asphalt-rubber rotational viscosity by statistical analysis and neural networks

    Directory of Open Access Journals (Sweden)

    Luciano Pivoto Specht

    2007-03-01

    Full Text Available It is of a great importance to know binders' viscosity in order to perform handling, mixing, application processes and asphalt mixes compaction in highway surfacing. This paper presents the results of viscosity measurement in asphalt-rubber binders prepared in laboratory. The binders were prepared varying the rubber content, rubber particle size, duration and temperature of mixture, all following a statistical design plan. The statistical analysis and artificial neural networks were used to create mathematical models for prediction of the binders viscosity. The comparison between experimental data and simulated results with the generated models showed best performance of the neural networks analysis in contrast to the statistic models. The results indicated that the rubber content and duration of mixture have major influence on the observed viscosity for the considered interval of parameters variation.

  9. Statistical Analysis of the Exchange Rate of Bitcoin.

    Directory of Open Access Journals (Sweden)

    Jeffrey Chu

    Full Text Available Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.

  10. Statistical Analysis of the Exchange Rate of Bitcoin

    Science.gov (United States)

    Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen

    2015-01-01

    Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate. PMID:26222702

  11. Statistical characterisation of COSMO Sky-Med X-SAR retrieved precipitation fields by scale-invariance analysis

    Science.gov (United States)

    Deidda, Roberto; Mascaro, Giuseppe; Hellies, Matteo; Baldini, Luca; Roberto, Nicoletta

    2013-04-01

    COSMO Sky-Med (CSK) is an important programme of the Italian Space Agency aiming at supporting environmental monitoring and management of exogenous, endogenous and anthropogenic risks through X-band Synthetic Aperture Radar (X-SAR) on board of 4 satellites forming a constellation. Most of typical SAR applications are focused on land or ocean observation. However, X-band SAR can be detect precipitation that results in a specific signature caused by the combination of attenuation of surface returns induced by precipitation and enhancement of backscattering determined by the hydrometeors in the SAR resolution volume. Within CSK programme, we conducted an intercomparison between the statistical properties of precipitation fields derived by CSK SARs and those derived by the CNR Polar 55C (C-band) ground based weather radar located in Rome (Italy). This contribution presents main results of this research which was aimed at the robust characterisation of rainfall statistical properties across different scales by means of scale-invariance analysis and multifractal theory. The analysis was performed on a dataset of more two years of precipitation observations collected by the CNR Polar 55C radar and rainfall fields derived from available images collected by the CSK satellites during intense rainfall events. Scale-invariance laws and multifractal properties were detected on the most intense rainfall events derived from the CNR Polar 55C radar for spatial scales from 4 km to 64 km. The analysis on X-SAR retrieved rainfall fields, although based on few images, leaded to similar results and confirmed the existence of scale-invariance and multifractal properties for scales larger than 4 km. These outcomes encourage investigating SAR methodologies for future development of meteo-hydrological forecasting models based on multifractal theory.

  12. Neurological outcomes following suicidal hanging: A prospective study of 101 patients

    Directory of Open Access Journals (Sweden)

    Mohammed Turab Jawaid

    2017-01-01

    Full Text Available Context: Survivors of suicidal hanging can have variable neurological outcomes – from complete recovery to irreversible brain damage. Literature on the neurological outcomes in these patients is confined to retrospective studies and case series. Hence, this prospective study was carried out. Aims: The aim is to study the neurological outcomes in suicidal hanging. Settings and Design: This was a prospective observational study carried out from July 2014 to July 2016. Subjects and Methods: Consecutive patients admitted to the emergency and medicine wards were included in the study. Details of the clinical and radiological findings, course in hospital and at 1 month postdischarge were analyzed. Statistical Analysis Used: Statistical analysis was performed using IBM SPSS advanced statistics 20.0 (SPSS Inc., Chicago, USA. Univariate analysis was performed using Chi-square test for significance and Odd's ratio was calculated. Results: Of the 101 patients, 6 died and 4 had residual neuro deficits. Cervical spine injury was seen in 3 patients. Interestingly, 39 patients could not remember the act of hanging (retrograde amnesia. Hypotension, pulmonary edema, Glasgow coma scale (GCS score <8 at admission, need for mechanical ventilation, and cerebral edema on plain computed tomography were more in those with amnesia as compared to those with normal memory and these findings were statistically significant. Conclusions: Majority of patients recovered without any sequelae. Routine imaging of cervical spine may not be warranted in all patients, even in those with poor GCS. Retrograde amnesia might be more common than previously believed and further studies are needed to analyze this peculiar feature.

  13. Cost and outcome analysis of two alcohol detoxification services.

    Science.gov (United States)

    Parrott, Steve; Godfrey, Christine; Heather, Nick; Clark, Jenny; Ryan, Tony

    2006-01-01

    To examine the relationship between service use and outcomes (individual and wider consequences) using an economic analysis of a direct-access alcohol detoxification service in Manchester (the Smithfield Centre) and an NHS partial hospitalization programme in Newcastle upon Tyne (Newcastle and North Tyneside Drug and Alcohol Service, Plummer Court). A total of 145 direct-access admissions to the Smithfield Centre and 77 admissions to Plummer Court completed a battery of questionnaires shortly after intake and were followed up 6 months after discharge. Full economic data at follow-up were available for 54 Smithfield admissions and 49 Plummer Court admissions. Mean total cost of treatment per patient was pound1113 at the Smithfield Centre and pound1054 at Plummer Court in 2003-04 prices. Comparing the 6 months before treatment with the 6 months before follow-up, social costs fell by pound331 on average for each patient at Plummer Court but rose by pound1047 for each patient at the Smithfield Centre. When treatment costs and wider social costs were combined, the total cost to society at Smithfield was on average pound2159 per patient whilst at Plummer Court it was pound723 per patient. Combining the cost of treatment with drinking outcomes yielded a net cost per unit reduction in alcohol consumption of pound1.79 at Smithfield and pound1.68 at Plummer Court. Both services delivered a flexible needs-based service to very disadvantaged population at a reasonable cost and were associated with statistically significant reductions in drinking. For some patients, there was evidence of public sector resource savings but for others these detoxification services allowed those not previously in contact with services to meet health and social care needs. These patterns of cost through time are more complex than in previous evaluations of less severely dependent patients and difficult to predict from drinking patterns or patient characteristics. More research is required to judge

  14. Innovative statistical methods for public health data

    CERN Document Server

    Wilson, Jeffrey

    2015-01-01

    The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference, and it can be used in graduate level classes.

  15. Analysis of Variance with Summary Statistics in Microsoft® Excel®

    Science.gov (United States)

    Larson, David A.; Hsu, Ko-Cheng

    2010-01-01

    Students regularly are asked to solve Single Factor Analysis of Variance problems given only the sample summary statistics (number of observations per category, category means, and corresponding category standard deviations). Most undergraduate students today use Excel for data analysis of this type. However, Excel, like all other statistical…

  16. Statistical Analysis Of Tank 19F Floor Sample Results

    International Nuclear Information System (INIS)

    Harris, S.

    2010-01-01

    Representative sampling has been completed for characterization of the residual material on the floor of Tank 19F as per the statistical sampling plan developed by Harris and Shine. Samples from eight locations have been obtained from the tank floor and two of the samples were archived as a contingency. Six samples, referred to in this report as the current scrape samples, have been submitted to and analyzed by SRNL. This report contains the statistical analysis of the floor sample analytical results to determine if further data are needed to reduce uncertainty. Included are comparisons with the prior Mantis samples results to determine if they can be pooled with the current scrape samples to estimate the upper 95% confidence limits (UCL95%) for concentration. Statistical analysis revealed that the Mantis and current scrape sample results are not compatible. Therefore, the Mantis sample results were not used to support the quantification of analytes in the residual material. Significant spatial variability among the current scrape sample results was not found. Constituent concentrations were similar between the North and South hemispheres as well as between the inner and outer regions of the tank floor. The current scrape sample results from all six samples fall within their 3-sigma limits. In view of the results from numerous statistical tests, the data were pooled from all six current scrape samples. As such, an adequate sample size was provided for quantification of the residual material on the floor of Tank 19F. The uncertainty is quantified in this report by an UCL95% on each analyte concentration. The uncertainty in analyte concentration was calculated as a function of the number of samples, the average, and the standard deviation of the analytical results. The UCL95% was based entirely on the six current scrape sample results (each averaged across three analytical determinations).

  17. [Design and implementation of online statistical analysis function in information system of air pollution and health impact monitoring].

    Science.gov (United States)

    Lü, Yiran; Hao, Shuxin; Zhang, Guoqing; Liu, Jie; Liu, Yue; Xu, Dongqun

    2018-01-01

    To implement the online statistical analysis function in information system of air pollution and health impact monitoring, and obtain the data analysis information real-time. Using the descriptive statistical method as well as time-series analysis and multivariate regression analysis, SQL language and visual tools to implement online statistical analysis based on database software. Generate basic statistical tables and summary tables of air pollution exposure and health impact data online; Generate tendency charts of each data part online and proceed interaction connecting to database; Generate butting sheets which can lead to R, SAS and SPSS directly online. The information system air pollution and health impact monitoring implements the statistical analysis function online, which can provide real-time analysis result to its users.

  18. Introduction to statistics and data analysis with exercises, solutions and applications in R

    CERN Document Server

    Heumann, Christian; Shalabh

    2016-01-01

    This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital. The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R as well as supplementary material that will enable the reader to quickly adapt all methods to their own applications.

  19. Methodology сomparative statistical analysis of Russian industry based on cluster analysis

    Directory of Open Access Journals (Sweden)

    Sergey S. Shishulin

    2017-01-01

    Full Text Available The article is devoted to researching of the possibilities of applying multidimensional statistical analysis in the study of industrial production on the basis of comparing its growth rates and structure with other developed and developing countries of the world. The purpose of this article is to determine the optimal set of statistical methods and the results of their application to industrial production data, which would give the best access to the analysis of the result.Data includes such indicators as output, output, gross value added, the number of employed and other indicators of the system of national accounts and operational business statistics. The objects of observation are the industry of the countrys of the Customs Union, the United States, Japan and Erope in 2005-2015. As the research tool used as the simplest methods of transformation, graphical and tabular visualization of data, and methods of statistical analysis. In particular, based on a specialized software package (SPSS, the main components method, discriminant analysis, hierarchical methods of cluster analysis, Ward’s method and k-means were applied.The application of the method of principal components to the initial data makes it possible to substantially and effectively reduce the initial space of industrial production data. Thus, for example, in analyzing the structure of industrial production, the reduction was from fifteen industries to three basic, well-interpreted factors: the relatively extractive industries (with a low degree of processing, high-tech industries and consumer goods (medium-technology sectors. At the same time, as a result of comparison of the results of application of cluster analysis to the initial data and data obtained on the basis of the principal components method, it was established that clustering industrial production data on the basis of new factors significantly improves the results of clustering.As a result of analyzing the parameters of

  20. Data analysis for radiological characterisation: Geostatistical and statistical complementarity

    International Nuclear Information System (INIS)

    Desnoyers, Yvon; Dubot, Didier

    2012-01-01

    Radiological characterisation may cover a large range of evaluation objectives during a decommissioning and dismantling (D and D) project: removal of doubt, delineation of contaminated materials, monitoring of the decontamination work and final survey. At each stage, collecting relevant data to be able to draw the conclusions needed is quite a big challenge. In particular two radiological characterisation stages require an advanced sampling process and data analysis, namely the initial categorization and optimisation of the materials to be removed and the final survey to demonstrate compliance with clearance levels. On the one hand the latter is widely used and well developed in national guides and norms, using random sampling designs and statistical data analysis. On the other hand a more complex evaluation methodology has to be implemented for the initial radiological characterisation, both for sampling design and for data analysis. The geostatistical framework is an efficient way to satisfy the radiological characterisation requirements providing a sound decision-making approach for the decommissioning and dismantling of nuclear premises. The relevance of the geostatistical methodology relies on the presence of a spatial continuity for radiological contamination. Thus geo-statistics provides reliable methods for activity estimation, uncertainty quantification and risk analysis, leading to a sound classification of radiological waste (surfaces and volumes). This way, the radiological characterization of contaminated premises can be divided into three steps. First, the most exhaustive facility analysis provides historical and qualitative information. Then, a systematic (exhaustive or not) surface survey of the contamination is implemented on a regular grid. Finally, in order to assess activity levels and contamination depths, destructive samples are collected at several locations within the premises (based on the surface survey results) and analysed. Combined with

  1. Multivariate statistical pattern recognition system for reactor noise analysis

    International Nuclear Information System (INIS)

    Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.

    1976-01-01

    A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system

  2. Multivariate statistical pattern recognition system for reactor noise analysis

    International Nuclear Information System (INIS)

    Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.

    1975-01-01

    A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system. 19 references

  3. Multiple Statistical Models Based Analysis of Causative Factors and Loess Landslides in Tianshui City, China

    Science.gov (United States)

    Su, Xing; Meng, Xingmin; Ye, Weilin; Wu, Weijiang; Liu, Xingrong; Wei, Wanhong

    2018-03-01

    Tianshui City is one of the mountainous cities that are threatened by severe geo-hazards in Gansu Province, China. Statistical probability models have been widely used in analyzing and evaluating geo-hazards such as landslide. In this research, three approaches (Certainty Factor Method, Weight of Evidence Method and Information Quantity Method) were adopted to quantitively analyze the relationship between the causative factors and the landslides, respectively. The source data used in this study are including the SRTM DEM and local geological maps in the scale of 1:200,000. 12 causative factors (i.e., altitude, slope, aspect, curvature, plan curvature, profile curvature, roughness, relief amplitude, and distance to rivers, distance to faults, distance to roads, and the stratum lithology) were selected to do correlation analysis after thorough investigation of geological conditions and historical landslides. The results indicate that the outcomes of the three models are fairly consistent.

  4. RESEARCH OF THE DATA BANK OF STATISTICAL ANALYSIS OF THE ADVERTISING MARKET

    Directory of Open Access Journals (Sweden)

    Ekaterina F. Devochkina

    2014-01-01

    Full Text Available The article contains the description of the process of making statistical accounting of the Russian advertising market. The author pays attention to the forms of state statistical accounting of different years, marks their different features and shortage. Also the article contains analysis of alternative sources of numerical information of Russian advertising market.

  5. Statistical Analysis for High-Dimensional Data : The Abel Symposium 2014

    CERN Document Server

    Bühlmann, Peter; Glad, Ingrid; Langaas, Mette; Richardson, Sylvia; Vannucci, Marina

    2016-01-01

    This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on...

  6. Halo statistics analysis within medium volume cosmological N-body simulation

    Directory of Open Access Journals (Sweden)

    Martinović N.

    2015-01-01

    Full Text Available In this paper we present halo statistics analysis of a ΛCDM N body cosmological simulation (from first halo formation until z = 0. We study mean major merger rate as a function of time, where for time we consider both per redshift and per Gyr dependence. For latter we find that it scales as the well known power law (1 + zn for which we obtain n = 2.4. The halo mass function and halo growth function are derived and compared both with analytical and empirical fits. We analyse halo growth through out entire simulation, making it possible to continuously monitor evolution of halo number density within given mass ranges. The halo formation redshift is studied exploring possibility for a new simple preliminary analysis during the simulation run. Visualization of the simulation is portrayed as well. At redshifts z = 0−7 halos from simulation have good statistics for further analysis especially in mass range of 1011 − 1014 M./h. [176021 ’Visible and invisible matter in nearby galaxies: theory and observations

  7. SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.

    Science.gov (United States)

    Chu, Annie; Cui, Jenny; Dinov, Ivo D

    2009-03-01

    The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most

  8. Outcomes of care for 16,924 planned home births in the United States: the Midwives Alliance of North America Statistics Project, 2004 to 2009.

    Science.gov (United States)

    Cheyney, Melissa; Bovbjerg, Marit; Everson, Courtney; Gordon, Wendy; Hannibal, Darcy; Vedam, Saraswathi

    2014-01-01

    Between 2004 and 2010, the number of home births in the United States rose by 41%, increasing the need for accurate assessment of the safety of planned home birth. This study examines outcomes of planned home births in the United States between 2004 and 2009. We calculated descriptive statistics for maternal demographics, antenatal risk profiles, procedures, and outcomes of planned home births in the Midwives Alliance of North American Statistics Project (MANA Stats) 2.0 data registry. Data were analyzed according to intended and actual place of birth. Among 16,924 women who planned home births at the onset of labor, 89.1% gave birth at home. The majority of intrapartum transfers were for failure to progress, and only 4.5% of the total sample required oxytocin augmentation and/or epidural analgesia. The rates of spontaneous vaginal birth, assisted vaginal birth, and cesarean were 93.6%, 1.2%, and 5.2%, respectively. Of the 1054 women who attempted a vaginal birth after cesarean, 87% were successful. Low Apgar scores (home births in the United States, outcomes are congruent with the best available data from population-based, observational studies that evaluated outcomes by intended place of birth and perinatal risk factors. Low-risk women in this cohort experienced high rates of physiologic birth and low rates of intervention without an increase in adverse outcomes. © 2014 by the American College of Nurse-Midwives.

  9. Education of staff in preschool aged classrooms in child care centers and child outcomes: A meta-analysis and systematic review.

    Science.gov (United States)

    Falenchuk, Olesya; Perlman, Michal; McMullen, Evelyn; Fletcher, Brooke; Shah, Prakesh S

    2017-01-01

    Staff education is considered key to quality of early childhood education and care (ECEC) programs. However, findings about associations between staff education and children's outcomes have been inconsistent. We conducted a systematic review and meta-analysis of associations between ECEC staff education and child outcomes. Searches of Medline, PsycINFO, and ERIC, websites of large datasets and reference sections of all retrieved articles were conducted. Eligible studies provided a statistical link between staff education and child outcomes for preschool-aged children in ECEC programs. Titles, abstracts and paper reviews as well as all data extraction were conducted by two independent raters. Of the 823 studies reviewed for eligibility, 39 met our inclusion criteria. Research in this area is observational in nature and subject to the inherent biases of that research design. Results from our systematic review were hampered by heterogeneity in how staff education was defined, variability in whose education was measured and the child outcomes that were assessed. However, overall the qualitative summary indicates that associations between staff education and childhood outcomes are non-existent to very borderline positive. In our meta-analysis of more homogeneous studies we identified certain positive, albeit very weak, associations between staff education and children's language outcomes (specifically, vocabulary and letter word identification) and no significant association with a mathematics outcome (WJ Applied Problems). Thus, our findings suggest that within the range of education levels found in the existing literature, education is not a key driver of child outcomes. However, since we only explored levels of education that were reported in the literature, our findings cannot be used to argue for lowering education standards in ECEC settings.

  10. Statistical grand rounds: understanding the mechanism: mediation analysis in randomized and nonrandomized studies.

    Science.gov (United States)

    Mascha, Edward J; Dalton, Jarrod E; Kurz, Andrea; Saager, Leif

    2013-10-01

    In comparative clinical studies, a common goal is to assess whether an exposure, or intervention, affects the outcome of interest. However, just as important is to understand the mechanism(s) for how the intervention affects outcome. For example, if preoperative anemia was shown to increase the risk of postoperative complications by 15%, it would be important to quantify how much of that effect was due to patients receiving intraoperative transfusions. Mediation analysis attempts to quantify how much, if any, of the effect of an intervention on outcome goes though prespecified mediator, or "mechanism" variable(s), that is, variables sitting on the causal pathway between exposure and outcome. Effects of an exposure on outcome can thus be divided into direct and indirect, or mediated, effects. Mediation is claimed when 2 conditions are true: the exposure affects the mediator and the mediator (adjusting for the exposure) affects the outcome. Understanding how an intervention affects outcome can validate or invalidate one's original hypothesis and also facilitate further research to modify the responsible factors, and thus improve patient outcome. We discuss the proper design and analysis of studies investigating mediation, including the importance of distinguishing mediator variables from confounding variables, the challenge of identifying potential mediators when the exposure is chronic versus acute, and the requirements for claiming mediation. Simple designs are considered, as well as those containing multiple mediators, multiple outcomes, and mixed data types. Methods are illustrated with data collected by the National Surgical Quality Improvement Project (NSQIP) and utilized in a companion paper which assessed the effects of preoperative anemic status on postoperative outcomes.

  11. Short-run and Current Analysis Model in Statistics

    Directory of Open Access Journals (Sweden)

    Constantin Anghelache

    2006-01-01

    Full Text Available Using the short-run statistic indicators is a compulsory requirement implied in the current analysis. Therefore, there is a system of EUROSTAT indicators on short run which has been set up in this respect, being recommended for utilization by the member-countries. On the basis of these indicators, there are regular, usually monthly, analysis being achieved in respect of: the production dynamic determination; the evaluation of the short-run investment volume; the development of the turnover; the wage evolution: the employment; the price indexes and the consumer price index (inflation; the volume of exports and imports and the extent to which the imports are covered by the exports and the sold of trade balance. The EUROSTAT system of indicators of conjuncture is conceived as an open system, so that it can be, at any moment extended or restricted, allowing indicators to be amended or even removed, depending on the domestic users requirements as well as on the specific requirements of the harmonization and integration. For the short-run analysis, there is also the World Bank system of indicators of conjuncture, which is utilized, relying on the data sources offered by the World Bank, The World Institute for Resources or other international organizations statistics. The system comprises indicators of the social and economic development and focuses on the indicators for the following three fields: human resources, environment and economic performances. At the end of the paper, there is a case study on the situation of Romania, for which we used all these indicators.

  12. Short-run and Current Analysis Model in Statistics

    Directory of Open Access Journals (Sweden)

    Constantin Mitrut

    2006-03-01

    Full Text Available Using the short-run statistic indicators is a compulsory requirement implied in the current analysis. Therefore, there is a system of EUROSTAT indicators on short run which has been set up in this respect, being recommended for utilization by the member-countries. On the basis of these indicators, there are regular, usually monthly, analysis being achieved in respect of: the production dynamic determination; the evaluation of the short-run investment volume; the development of the turnover; the wage evolution: the employment; the price indexes and the consumer price index (inflation; the volume of exports and imports and the extent to which the imports are covered by the exports and the sold of trade balance. The EUROSTAT system of indicators of conjuncture is conceived as an open system, so that it can be, at any moment extended or restricted, allowing indicators to be amended or even removed, depending on the domestic users requirements as well as on the specific requirements of the harmonization and integration. For the short-run analysis, there is also the World Bank system of indicators of conjuncture, which is utilized, relying on the data sources offered by the World Bank, The World Institute for Resources or other international organizations statistics. The system comprises indicators of the social and economic development and focuses on the indicators for the following three fields: human resources, environment and economic performances. At the end of the paper, there is a case study on the situation of Romania, for which we used all these indicators.

  13. Statistical analysis of proteomics, metabolomics, and lipidomics data using mass spectrometry

    CERN Document Server

    Mertens, Bart

    2017-01-01

    This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies. Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass ...

  14. Three-Dimensional Assembly Tolerance Analysis Based on the Jacobian-Torsor Statistical Model

    Directory of Open Access Journals (Sweden)

    Peng Heping

    2017-01-01

    Full Text Available The unified Jacobian-Torsor model has been developed for deterministic (worst case tolerance analysis. This paper presents a comprehensive model for performing statistical tolerance analysis by integrating the unified Jacobian-Torsor model and Monte Carlo simulation. In this model, an assembly is sub-divided into surfaces, the Small Displacements Torsor (SDT parameters are used to express the relative position between any two surfaces of the assembly. Then, 3D dimension-chain can be created by using a surface graph of the assembly and the unified Jacobian-Torsor model is developed based on the effect of each functional element on the whole functional requirements of products. Finally, Monte Carlo simulation is implemented for the statistical tolerance analysis. A numerical example is given to demonstrate the capability of the proposed method in handling three-dimensional assembly tolerance analysis.

  15. SAS and R data management, statistical analysis, and graphics

    CERN Document Server

    Kleinman, Ken

    2009-01-01

    An All-in-One Resource for Using SAS and R to Carry out Common TasksProvides a path between languages that is easier than reading complete documentationSAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and the creation of graphics, along with more complex applicat

  16. Statistical methods for data analysis in particle physics

    CERN Document Server

    AUTHOR|(CDS)2070643

    2015-01-01

    This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data

  17. Statistical Analysis of 30 Years Rainfall Data: A Case Study

    Science.gov (United States)

    Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.

    2017-07-01

    Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.

  18. Statistical strategies to reveal potential vibrational markers for in vivo analysis by confocal Raman spectroscopy

    Science.gov (United States)

    Oliveira Mendes, Thiago de; Pinto, Liliane Pereira; Santos, Laurita dos; Tippavajhala, Vamshi Krishna; Téllez Soto, Claudio Alberto; Martin, Airton Abrahão

    2016-07-01

    The analysis of biological systems by spectroscopic techniques involves the evaluation of hundreds to thousands of variables. Hence, different statistical approaches are used to elucidate regions that discriminate classes of samples and to propose new vibrational markers for explaining various phenomena like disease monitoring, mechanisms of action of drugs, food, and so on. However, the technical statistics are not always widely discussed in applied sciences. In this context, this work presents a detailed discussion including the various steps necessary for proper statistical analysis. It includes univariate parametric and nonparametric tests, as well as multivariate unsupervised and supervised approaches. The main objective of this study is to promote proper understanding of the application of various statistical tools in these spectroscopic methods used for the analysis of biological samples. The discussion of these methods is performed on a set of in vivo confocal Raman spectra of human skin analysis that aims to identify skin aging markers. In the Appendix, a complete routine of data analysis is executed in a free software that can be used by the scientific community involved in these studies.

  19. A method for statistical steady state thermal analysis of reactor cores

    International Nuclear Information System (INIS)

    Whetton, P.A.

    1980-01-01

    This paper presents a method for performing a statistical steady state thermal analysis of a reactor core. The technique is only outlined here since detailed thermal equations are dependent on the core geometry. The method has been applied to a pressurised water reactor core and the results are presented for illustration purposes. Random hypothetical cores are generated using the Monte-Carlo method. The technique shows that by splitting the parameters into two types, denoted core-wise and in-core, the Monte Carlo method may be used inexpensively. The idea of using extremal statistics to characterise the low probability events (i.e. the tails of a distribution) is introduced together with a method of forming the final probability distribution. After establishing an acceptable probability of exceeding a thermal design criterion, the final probability distribution may be used to determine the corresponding thermal response value. If statistical and deterministic (i.e. conservative) thermal response values are compared, information on the degree of pessimism in the deterministic method of analysis may be inferred and the restrictive performance limitations imposed by this method relieved. (orig.)

  20. Statistical analysis of first period of operation of FTU Tokamak

    International Nuclear Information System (INIS)

    Crisanti, F.; Apruzzese, G.; Frigione, D.; Kroegler, H.; Lovisetto, L.; Mazzitelli, G.; Podda, S.

    1996-09-01

    On the FTU Tokamak the plasma physics operations started on the 20/4/90. The first plasma had a plasma current Ip=0.75 MA for about a second. The experimental phase lasted until 7/7/94, when a long shut-down begun for installing the toroidal limiter in the inner side of the vacuum vessel. In these four years of operations plasma experiments have been successfully exploited, e.g. experiments of single and multiple pellet injections; full current drive up to Ip=300 KA was obtained by using waves at the frequency of the Lower Hybrid; analysis of ohmic plasma parameters with different materials (from the low Z silicon to high Z tungsten) as plasma facing element was performed. In this work a statistical analysis of the full period of operation is presented. Moreover, a comparison with the statistical data from other Tokamaks is attempted

  1. Head First Statistics

    CERN Document Server

    Griffiths, Dawn

    2009-01-01

    Wouldn't it be great if there were a statistics book that made histograms, probability distributions, and chi square analysis more enjoyable than going to the dentist? Head First Statistics brings this typically dry subject to life, teaching you everything you want and need to know about statistics through engaging, interactive, and thought-provoking material, full of puzzles, stories, quizzes, visual aids, and real-world examples. Whether you're a student, a professional, or just curious about statistical analysis, Head First's brain-friendly formula helps you get a firm grasp of statistics

  2. Comparison of untreated adolescent idiopathic scoliosis with normal controls: a review and statistical analysis of the literature.

    Science.gov (United States)

    Rushton, Paul R P; Grevitt, Michael P

    2013-04-20

    Review and statistical analysis of studies evaluating health-related quality of life (HRQOL) in adolescents with untreated adolescent idiopathic scoliosis (AIS) using Scoliosis Research Society (SRS) outcomes. To apply normative values and minimum clinical important differences for the SRS-22r to the literature. Identify whether the HRQOL of adolescents with untreated AIS differs from unaffected peers and whether any differences are clinically relevant. The effect of untreated AIS on adolescent HRQOL is uncertain. The lack of published normative values and minimum clinical important difference for the SRS-22r has so far hindered our interpretation of previous studies. The publication of this background data allows these studies to be re-examined. Using suitable inclusion criteria, a literature search identified studies examining HRQOL in untreated adolescents with AIS. Each cohort was analyzed individually. Statistically significant differences were identified by using 95% confidence intervals for the difference in SRS-22r domain mean scores between the cohorts with AIS and the published data for unaffected adolescents. If the lower bound of the confidence interval was greater than the minimum clinical important difference, the difference was considered clinically significant. Of the 21 included patient cohorts, 81% reported statistically worse pain than those unaffected. Yet in only 5% of cohorts was this difference clinically important. Of the 11 cohorts included examining patient self-image, 91% reported statistically worse scores than those unaffected. In 73% of cohorts this difference was clinically significant. Affected cohorts tended to score well in function/activity and mental health domains and differences from those unaffected rarely reached clinically significant values. Pain and self-image tend to be statistically lower among cohorts with AIS than those unaffected. The literature to date suggests that it is only self-image which consistently differs

  3. Using R and RStudio for data management, statistical analysis and graphics

    CERN Document Server

    Horton, Nicholas J

    2015-01-01

    This is the second edition of the popular book on using R for statistical analysis and graphics. The authors, who run a popular blog supplementing their books, have focused on adding many new examples to this new edition. These examples are presented primarily in new chapters based on the following themes: simulation, probability, statistics, mathematics/computing, and graphics. The authors have also added many other updates, including a discussion of RStudio-a very popular development environment for R.

  4. Statistical analysis of absorptive laser damage in dielectric thin films

    International Nuclear Information System (INIS)

    Budgor, A.B.; Luria-Budgor, K.F.

    1978-01-01

    The Weibull distribution arises as an example of the theory of extreme events. It is commonly used to fit statistical data arising in the failure analysis of electrical components and in DC breakdown of materials. This distribution is employed to analyze time-to-damage and intensity-to-damage statistics obtained when irradiating thin film coated samples of SiO 2 , ZrO 2 , and Al 2 O 3 with tightly focused laser beams. The data used is furnished by Milam. The fit to the data is excellent; and least squared correlation coefficients greater than 0.9 are often obtained

  5. Statistical analysis of failure time in stress corrosion cracking of fuel tube in light water reactor

    International Nuclear Information System (INIS)

    Hirao, Keiichi; Yamane, Toshimi; Minamino, Yoritoshi

    1991-01-01

    This report is to show how the life due to stress corrosion cracking breakdown of fuel cladding tubes is evaluated by applying the statistical techniques to that examined by a few testing methods. The statistical distribution of the limiting values of constant load stress corrosion cracking life, the statistical analysis by making the probabilistic interpretation of constant load stress corrosion cracking life, and the statistical analysis of stress corrosion cracking life by the slow strain rate test (SSRT) method are described. (K.I.)

  6. Implementation and statistical analysis of Metropolis algorithm for SU(3)

    International Nuclear Information System (INIS)

    Katznelson, E.; Nobile, A.

    1984-12-01

    In this paper we study the statistical properties of an implementation of the Metropolis algorithm for SU(3) gauge theory. It is shown that the results have normal distribution. We demonstrate that in this case error analysis can be carried on in a simple way and we show that applying it to both the measurement strategy and the output data analysis has an important influence on the performance and reliability of the simulation. (author)

  7. Empirical comparison of four baseline covariate adjustment methods in analysis of continuous outcomes in randomized controlled trials

    Directory of Open Access Journals (Sweden)

    Zhang S

    2014-07-01

    .38 and percent change (–0.019; 95% CI: -0.087, 0.050; P=0.58.Conclusion: ANCOVA, through both simulation and empirical studies, provides the best statistical estimation for analyzing continuous outcomes requiring covariate adjustment. Our empirical findings support the use of ANCOVA as an optimal method in both design and analysis of trials with a continuous primary outcome.Keywords: ANOVA, ANCOVA, change score, knee arthroplasty

  8. To be certain about the uncertainty: Bayesian statistics for 13 C metabolic flux analysis.

    Science.gov (United States)

    Theorell, Axel; Leweke, Samuel; Wiechert, Wolfgang; Nöh, Katharina

    2017-11-01

    13 C Metabolic Fluxes Analysis ( 13 C MFA) remains to be the most powerful approach to determine intracellular metabolic reaction rates. Decisions on strain engineering and experimentation heavily rely upon the certainty with which these fluxes are estimated. For uncertainty quantification, the vast majority of 13 C MFA studies relies on confidence intervals from the paradigm of Frequentist statistics. However, it is well known that the confidence intervals for a given experimental outcome are not uniquely defined. As a result, confidence intervals produced by different methods can be different, but nevertheless equally valid. This is of high relevance to 13 C MFA, since practitioners regularly use three different approximate approaches for calculating confidence intervals. By means of a computational study with a realistic model of the central carbon metabolism of E. coli, we provide strong evidence that confidence intervals used in the field depend strongly on the technique with which they were calculated and, thus, their use leads to misinterpretation of the flux uncertainty. In order to provide a better alternative to confidence intervals in 13 C MFA, we demonstrate that credible intervals from the paradigm of Bayesian statistics give more reliable flux uncertainty quantifications which can be readily computed with high accuracy using Markov chain Monte Carlo. In addition, the widely applied chi-square test, as a means of testing whether the model reproduces the data, is examined closer. © 2017 Wiley Periodicals, Inc.

  9. Long-Term Neuropsychological Outcome in Preterm Twins

    Directory of Open Access Journals (Sweden)

    Giovanni Iannone

    2006-01-01

    Full Text Available Few long-term studies have yet described neuropsychological outcome in preterm twins. Our aim was to assess, by long-term evaluation, neuropsychological outcome in preterm twins in order to define a correct follow-up program. Our study was a cohort one, with an index and a comparison group. Neonatal medical records of all preterm newborns admitted to our centre between 1991 and 1997 were reviewed and selected patients were recalled. The sample population included two matched groups of children aged 6—12 years, 86 twins and 86 singletons, submitted to paediatric, neurological, psychological, and ophthalmological examinations. Inclusion criteria were twin pregnancy and gestational age 27—36 weeks for index group; same gestational age, but single pregnancy, for the comparison group. All children underwent paediatric and neuropsychiatric examinations, cognitive assessment, and psychological evaluation by standardized tests for screening of learning specific disorders and language difficulties, and finally, ophthalmological examination. In order to study their role in predicting neuropsychological outcome, we examined some perinatal prognostic factors by statistical analysis. Unfavourable neuropsychological outcome was observed in 55/172 (32% children, with different prevalence in the two groups, 42/172 (24% in twins and 13/172 (8% in singletons. Statistical analysis performed for examined prognostic factors showed significant differences in neuropsychological outcome with regard only to gestational age < 32 weeks, low birth weight, intraventricular haemorrhage, and periventricular leukomalacia. The incidence of neuropsychological diseases in the two groups showed significant difference about language and learning difficulties. Our data suggest that preterm twins represent a particular high-risk category of premature babies, mostly regarding the risk of so-called “minimal brain dysfunction”, so a careful follow-up is recommended.

  10. Analysis of Statistical Distributions Used for Modeling Reliability and Failure Rate of Temperature Alarm Circuit

    International Nuclear Information System (INIS)

    EI-Shanshoury, G.I.

    2011-01-01

    Several statistical distributions are used to model various reliability and maintainability parameters. The applied distribution depends on the' nature of the data being analyzed. The presented paper deals with analysis of some statistical distributions used in reliability to reach the best fit of distribution analysis. The calculations rely on circuit quantity parameters obtained by using Relex 2009 computer program. The statistical analysis of ten different distributions indicated that Weibull distribution gives the best fit distribution for modeling the reliability of the data set of Temperature Alarm Circuit (TAC). However, the Exponential distribution is found to be the best fit distribution for modeling the failure rate

  11. Statistical mechanical analysis of LMFBR fuel cladding tubes

    International Nuclear Information System (INIS)

    Poncelet, J.-P.; Pay, A.

    1977-01-01

    The most important design requirement on fuel pin cladding for LMFBR's is its mechanical integrity. Disruptive factors include internal pressure from mixed oxide fuel fission gas release, thermal stresses and high temperature creep, neutron-induced differential void-swelling as a source of stress in the cladding and irradiation creep of stainless steel material, corrosion by fission products. Under irradiation these load-restraining mechanisms are accentuated by stainless steel embrittlement and strength alterations. To account for the numerous uncertainties involved in the analysis by theoretical models and computer codes statistical tools are unavoidably requested, i.e. Monte Carlo simulation methods. Thanks to these techniques, uncertainties in nominal characteristics, material properties and environmental conditions can be linked up in a correct way and used for a more accurate conceptual design. First, a thermal creep damage index is set up through a sufficiently sophisticated clad physical analysis including arbitrary time dependence of power and neutron flux as well as effects of sodium temperature, burnup and steel mechanical behavior. Although this strain limit approach implies a more general but time consuming model., on the counterpart the net output is improved and e.g. clad temperature, stress and strain maxima may be easily assessed. A full spectrum of variables are statistically treated to account for their probability distributions. Creep damage probability may be obtained and can contribute to a quantitative fuel probability estimation

  12. A robust statistical method for association-based eQTL analysis.

    Directory of Open Access Journals (Sweden)

    Ning Jiang

    Full Text Available It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS is statistical inference of linkage disequilibrium (LD between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation.We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations.The analyses show that the new method confers an improved statistical power for detecting genuine genetic association in subpopulations and an effective control of spurious associations stemmed from population structure when compared with other two popularly implemented methods in the literature of GWAS.

  13. Statistical and Machine-Learning Data Mining Techniques for Better Predictive Modeling and Analysis of Big Data

    CERN Document Server

    Ratner, Bruce

    2011-01-01

    The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has

  14. Constitution of an incident database suited to statistical analysis and examples

    International Nuclear Information System (INIS)

    Verpeaux, J.L.

    1990-01-01

    The Nuclear Protection and Safety Institute (IPSN) has set up and is developing an incidents database, which is used for the management and analysis of incidents encountered in French PWR plants. IPSN has already carried out several incidents or safety important events statistical analysis, and is improving its database on the basis of the experience it gained from this various studies. A description of the analysis method and of the developed database is presented

  15. A new statistic for the analysis of circular data in gamma-ray astronomy

    Science.gov (United States)

    Protheroe, R. J.

    1985-01-01

    A new statistic is proposed for the analysis of circular data. The statistic is designed specifically for situations where a test of uniformity is required which is powerful against alternatives in which a small fraction of the observations is grouped in a small range of directions, or phases.

  16. Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

    Directory of Open Access Journals (Sweden)

    E. V. Thomas

    2009-01-01

    Full Text Available Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.

  17. Statistical Compilation of the ICT Sector and Policy Analysis | CRDI ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Statistical Compilation of the ICT Sector and Policy Analysis. As the presence and influence of information and communication technologies (ICTs) continues to widen and deepen, so too does its impact on economic development. However, much work needs to be done before the linkages between economic development ...

  18. Statistical Compilation of the ICT Sector and Policy Analysis | IDRC ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Statistical Compilation of the ICT Sector and Policy Analysis. As the presence and influence of information and communication technologies (ICTs) continues to widen and deepen, so too does its impact on economic development. However, much work needs to be done before the linkages between economic development ...

  19. IVF/ICSI outcomes after culture of human embryos at low oxygen tension: a meta-analysis

    Directory of Open Access Journals (Sweden)

    Gomes Sobrinho David B

    2011-11-01

    Full Text Available Abstract Background Improved pregnancy, implantation, and birth rates have been reported after the use of reduced O2 concentration during embryo culture, mainly due to a reduction of the cumulative detrimental effects of reactive oxygen species. However, some studies have failed to report any positive effects. The objective of this meta-analysis was to evaluate the effect of a low-O2 environment on IVF/intracytoplasmic sperm injection (ICSI outcomes. Methods All available published and ongoing randomised trials that compared the effects of low (~5%; OC~5 and atmospheric (~20%; OC~20 oxygen concentrations on IVF/ICSI outcomes were included. Search strategies included online surveys of databases from 1980 to 2011. The outcomes measured were fertilisation rate, implantation rate and ongoing pregnancy rates. The fixed effects model was used to calculate the odds ratio. Results Seven studies were included in this analysis. The pooled fertilisation rate did not differ significantly (P = 0.54 between the group of oocytes cultured at low O2 tension and the group at atmospheric O2 tension. Concerning all cycles, the implantation (P = 0.06 and ongoing pregnancy (P = 0.051 rates were not significantly different between the group receiving transferred sets containing only OC~5 embryos and the group receiving transferred sets with only OC~20 embryos. In a meta-analysis performed for only those trials in which embryos were transferred on day 2/3, implantation (P = 0.63 and ongoing pregnancy (P = 0.19 rates were not significantly different between the groups. In contrast, when a meta-analysis was performed using only trials in which embryos were transferred on days 5 and 6 (at the blastocyst stage, the group with transferred sets of only OC~5 embryos showed a statistically significantly higher implantation rate (P = 0.006 than the group receiving transferred sets with only OC~20 embryos, although the ongoing pregnancy (P = 0.19 rates were not significantly

  20. A critical discussion of null hypothesis significance testing and statistical power analysis within psychological research

    DEFF Research Database (Denmark)

    Jones, Allan; Sommerlund, Bo

    2007-01-01

    The uses of null hypothesis significance testing (NHST) and statistical power analysis within psychological research are critically discussed. The article looks at the problems of relying solely on NHST when dealing with small and large sample sizes. The use of power-analysis in estimating...... the potential error introduced by small and large samples is advocated. Power analysis is not recommended as a replacement to NHST but as an additional source of information about the phenomena under investigation. Moreover, the importance of conceptual analysis in relation to statistical analysis of hypothesis...

  1. Abdominal Wall Reconstruction with Concomitant Ostomy-Associated Hernia Repair: Outcomes and Propensity Score Analysis.

    Science.gov (United States)

    Mericli, Alexander F; Garvey, Patrick B; Giordano, Salvatore; Liu, Jun; Baumann, Donald P; Butler, Charles E

    2017-03-01

    The optimal strategy for abdominal wall reconstruction in the presence of a stomal-site hernia is unclear. We hypothesized that the rate of ventral hernia recurrence in patients undergoing a combined ventral hernia repair and stomal-site herniorraphy would not differ clinically from the ventral hernia recurrence rate in patients undergoing an isolated ventral hernia repair. We also hypothesized that bridged ventral hernia repairs result in worse outcomes compared with reinforced repairs, regardless of stomal hernia. We retrospectively reviewed prospectively collected data from consecutive abdominal wall reconstructions performed with acellular dermal matrix (ADM) at a single center between 2000 and 2015. We compared patients who underwent a ventral hernia repair alone (AWR) and those who underwent both a ventral hernia repair and ostomy-associated herniorraphy (AWR+O). We conducted a propensity score matched analysis to compare the outcomes between the 2 groups. Multivariable Cox proportional hazards and logistic regression models were used to study associations between potential predictive or protective reconstructive strategies and surgical outcomes. We included 499 patients (median follow-up 27.2 months; interquartile range [IQR] 12.4 to 46.6 months), 118 AWR+O and 381 AWR. After propensity score matching, 91 pairs were obtained. Ventral hernia recurrence was not statistically associated with ostomy-associated herniorraphy (adjusted hazard ratio [HR] 0.7; 95% CI 0.3 to 1.5; p = 0.34). However, the AWR+O group experienced a significantly higher percentage of surgical site occurrences (34.1%) than the AWR group (18.7%; adjusted odds ratio 2.3; 95% CI 1.4 to 3.7; p < 0.001). In the AWR group, there were significantly fewer ventral hernia recurrences when the repair was reinforced compared with bridged (5.3% vs 38.5%; p < 0.001). There was no statistically significant difference in ventral hernia recurrence between the AWR and AWR+O groups. Bridging was associated

  2. Dataset on statistical analysis of editorial board composition of Hindawi journals indexed in Emerging sources citation index

    Directory of Open Access Journals (Sweden)

    Hilary I. Okagbue

    2018-04-01

    Full Text Available This data article contains the statistical analysis of the total, percentage and distribution of editorial board composition of 111 Hindawi journals indexed in Emerging Sources Citation Index (ESCI across the continents. The reliability of the data was shown using correlation, goodness-of-fit test, analysis of variance and statistical variability tests. Keywords: Hindawi, Bibliometrics, Data analysis, ESCI, Random, Smart campus, Web of science, Ranking analytics, Statistics

  3. Statistical analysis of the determinations of the Sun's Galactocentric distance

    Science.gov (United States)

    Malkin, Zinovy

    2013-02-01

    Based on several tens of R0 measurements made during the past two decades, several studies have been performed to derive the best estimate of R0. Some used just simple averaging to derive a result, whereas others provided comprehensive analyses of possible errors in published results. In either case, detailed statistical analyses of data used were not performed. However, a computation of the best estimates of the Galactic rotation constants is not only an astronomical but also a metrological task. Here we perform an analysis of 53 R0 measurements (published in the past 20 years) to assess the consistency of the data. Our analysis shows that they are internally consistent. It is also shown that any trend in the R0 estimates from the last 20 years is statistically negligible, which renders the presence of a bandwagon effect doubtful. On the other hand, the formal errors in the published R0 estimates improve significantly with time.

  4. Predictions of outcomes of renal stones after extracorporeal shock wave lithotripsy from stone characteristics determined by unenhanced helical computed tomography: a multivariate analysis

    International Nuclear Information System (INIS)

    Wang, Li-Jen; Wong, Yon-Cheong; Chuang, Cheng-Keng; Chu, Sheng-Hsien; Chen, Chih-Shou; Chiang, Yang-Jen; See, Lai-Chu

    2005-01-01

    The aim of our study is to analyze the relationships between the characteristics of renal stones determined by unenhanced helical computed tomography (UHCT) and their outcomes after extracorporeal shock wave lithotripsy (ESWL) as well as to predict ESWL outcomes of renal stones by their UHCT characteristics with the use of multivariate analysis. During a 7-month period, 80 adult patients with renal stones underwent ESWL as well as UHCT both before and 3 months after ESWL. Of the 80 patients, 42 patients were classified as ESWL successes and 38 as ESWL failures based on their post-ESWL UHCT findings. For pre-ESWL UHCT, a stone number of more than 2 (P=0.0236), a maximal stone size of greater than 12 mm (P 3 (P 3 (P=0.0003), the presence of nonround/oval stones (P=0.0072) and a maximal stone density of more than 900 HU (P=0.0430) were statistically significant predictors of a failure outcome for ESWL. Thus, the analysis of stone characteristics of renal stones by UHCT is helpful in selecting appropriate patients undergoing ESWL for favorable outcomes and reduces the overall costs of the treatment of renal stones. (orig.)

  5. Statistical analysis of global horizontal solar irradiation GHI in Fez city, Morocco

    Science.gov (United States)

    Bounoua, Z.; Mechaqrane, A.

    2018-05-01

    An accurate knowledge of the solar energy reaching the ground is necessary for sizing and optimizing the performances of solar installations. This paper describes a statistical analysis of the global horizontal solar irradiation (GHI) at Fez city, Morocco. For better reliability, we have first applied a set of check procedures to test the quality of hourly GHI measurements. We then eliminate the erroneous values which are generally due to measurement or the cosine effect errors. Statistical analysis show that the annual mean daily values of GHI is of approximately 5 kWh/m²/day. Daily monthly mean values and other parameter are also calculated.

  6. Statistical inference from imperfect photon detection

    International Nuclear Information System (INIS)

    Audenaert, Koenraad M R; Scheel, Stefan

    2009-01-01

    We consider the statistical properties of photon detection with imperfect detectors that exhibit dark counts and less than unit efficiency, in the context of tomographic reconstruction. In this context, the detectors are used to implement certain positive operator-valued measures (POVMs) that would allow us to reconstruct the quantum state or quantum process under consideration. Here we look at the intermediate step of inferring outcome probabilities from measured outcome frequencies, and show how this inference can be performed in a statistically sound way in the presence of detector imperfections. Merging outcome probabilities for different sets of POVMs into a consistent quantum state picture has been treated elsewhere (Audenaert and Scheel 2009 New J. Phys. 11 023028). Single-photon pulsed measurements as well as continuous wave measurements are covered.

  7. Statistical and machine learning approaches for network analysis

    CERN Document Server

    Dehmer, Matthias

    2012-01-01

    Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation

  8. Analysis of spectral data with rare events statistics

    International Nuclear Information System (INIS)

    Ilyushchenko, V.I.; Chernov, N.I.

    1990-01-01

    The case is considered of analyzing experimental data, when the results of individual experimental runs cannot be summed due to large systematic errors. A statistical analysis of the hypothesis about the persistent peaks in the spectra has been performed by means of the Neyman-Pearson test. The computations demonstrate the confidence level for the hypothesis about the presence of a persistent peak in the spectrum is proportional to the square root of the number of independent experimental runs, K. 5 refs

  9. STATISTICAL ANALYSIS OF TANK 18F FLOOR SAMPLE RESULTS

    Energy Technology Data Exchange (ETDEWEB)

    Harris, S.

    2010-09-02

    Representative sampling has been completed for characterization of the residual material on the floor of Tank 18F as per the statistical sampling plan developed by Shine [1]. Samples from eight locations have been obtained from the tank floor and two of the samples were archived as a contingency. Six samples, referred to in this report as the current scrape samples, have been submitted to and analyzed by SRNL [2]. This report contains the statistical analysis of the floor sample analytical results to determine if further data are needed to reduce uncertainty. Included are comparisons with the prior Mantis samples results [3] to determine if they can be pooled with the current scrape samples to estimate the upper 95% confidence limits (UCL{sub 95%}) for concentration. Statistical analysis revealed that the Mantis and current scrape sample results are not compatible. Therefore, the Mantis sample results were not used to support the quantification of analytes in the residual material. Significant spatial variability among the current sample results was not found. Constituent concentrations were similar between the North and South hemispheres as well as between the inner and outer regions of the tank floor. The current scrape sample results from all six samples fall within their 3-sigma limits. In view of the results from numerous statistical tests, the data were pooled from all six current scrape samples. As such, an adequate sample size was provided for quantification of the residual material on the floor of Tank 18F. The uncertainty is quantified in this report by an upper 95% confidence limit (UCL{sub 95%}) on each analyte concentration. The uncertainty in analyte concentration was calculated as a function of the number of samples, the average, and the standard deviation of the analytical results. The UCL{sub 95%} was based entirely on the six current scrape sample results (each averaged across three analytical determinations).

  10. Limitations of Using Microsoft Excel Version 2016 (MS Excel 2016) for Statistical Analysis for Medical Research.

    Science.gov (United States)

    Tanavalee, Chotetawan; Luksanapruksa, Panya; Singhatanadgige, Weerasak

    2016-06-01

    Microsoft Excel (MS Excel) is a commonly used program for data collection and statistical analysis in biomedical research. However, this program has many limitations, including fewer functions that can be used for analysis and a limited number of total cells compared with dedicated statistical programs. MS Excel cannot complete analyses with blank cells, and cells must be selected manually for analysis. In addition, it requires multiple steps of data transformation and formulas to plot survival analysis graphs, among others. The Megastat add-on program, which will be supported by MS Excel 2016 soon, would eliminate some limitations of using statistic formulas within MS Excel.

  11. A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis.

    Science.gov (United States)

    Lin, Johnny; Bentler, Peter M

    2012-01-01

    Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's asymptotically distribution-free method and Satorra Bentler's mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler's statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby's study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic.

  12. Statistical Analysis of CFD Solutions from the Fourth AIAA Drag Prediction Workshop

    Science.gov (United States)

    Morrison, Joseph H.

    2010-01-01

    A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from the U.S., Europe, Asia, and Russia using a variety of grid systems and turbulence models for the June 2009 4th Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was a new subsonic transport model, the Common Research Model, designed using a modern approach for the wing and included a horizontal tail. The fourth workshop focused on the prediction of both absolute and incremental drag levels for wing-body and wing-body-horizontal tail configurations. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with earlier workshops using the statistical framework.

  13. Error analysis of terrestrial laser scanning data by means of spherical statistics and 3D graphs.

    Science.gov (United States)

    Cuartero, Aurora; Armesto, Julia; Rodríguez, Pablo G; Arias, Pedro

    2010-01-01

    This paper presents a complete analysis of the positional errors of terrestrial laser scanning (TLS) data based on spherical statistics and 3D graphs. Spherical statistics are preferred because of the 3D vectorial nature of the spatial error. Error vectors have three metric elements (one module and two angles) that were analyzed by spherical statistics. A study case has been presented and discussed in detail. Errors were calculating using 53 check points (CP) and CP coordinates were measured by a digitizer with submillimetre accuracy. The positional accuracy was analyzed by both the conventional method (modular errors analysis) and the proposed method (angular errors analysis) by 3D graphics and numerical spherical statistics. Two packages in R programming language were performed to obtain graphics automatically. The results indicated that the proposed method is advantageous as it offers a more complete analysis of the positional accuracy, such as angular error component, uniformity of the vector distribution, error isotropy, and error, in addition the modular error component by linear statistics.

  14. CFAssay: statistical analysis of the colony formation assay

    International Nuclear Information System (INIS)

    Braselmann, Herbert; Michna, Agata; Heß, Julia; Unger, Kristian

    2015-01-01

    Colony formation assay is the gold standard to determine cell reproductive death after treatment with ionizing radiation, applied for different cell lines or in combination with other treatment modalities. Associated linear-quadratic cell survival curves can be calculated with different methods. For easy code exchange and methodological standardisation among collaborating laboratories a software package CFAssay for R (R Core Team, R: A Language and Environment for Statistical Computing, 2014) was established to perform thorough statistical analysis of linear-quadratic cell survival curves after treatment with ionizing radiation and of two-way designs of experiments with chemical treatments only. CFAssay offers maximum likelihood and related methods by default and the least squares or weighted least squares method can be optionally chosen. A test for comparision of cell survival curves and an ANOVA test for experimental two-way designs are provided. For the two presented examples estimated parameters do not differ much between maximum-likelihood and least squares. However the dispersion parameter of the quasi-likelihood method is much more sensitive for statistical variation in the data than the multiple R 2 coefficient of determination from the least squares method. The dispersion parameter for goodness of fit and different plot functions in CFAssay help to evaluate experimental data quality. As open source software interlaboratory code sharing between users is facilitated

  15. Procedure for statistical analysis of one-parameter discrepant experimental data

    International Nuclear Information System (INIS)

    Badikov, Sergey A.; Chechev, Valery P.

    2012-01-01

    A new, Mandel–Paule-type procedure for statistical processing of one-parameter discrepant experimental data is described. The procedure enables one to estimate a contribution of unrecognized experimental errors into the total experimental uncertainty as well as to include it in analysis. A definition of discrepant experimental data for an arbitrary number of measurements is introduced as an accompanying result. In the case of negligible unrecognized experimental errors, the procedure simply reduces to the calculation of the weighted average and its internal uncertainty. The procedure was applied to the statistical analysis of half-life experimental data; Mean half-lives for 20 actinides were calculated and results were compared to the ENSDF and DDEP evaluations. On the whole, the calculated half-lives are consistent with the ENSDF and DDEP evaluations. However, the uncertainties calculated in this work essentially exceed the ENSDF and DDEP evaluations for discrepant experimental data. This effect can be explained by adequately taking into account unrecognized experimental errors. - Highlights: ► A new statistical procedure for processing one-parametric discrepant experimental data has been presented. ► Procedure estimates a contribution of unrecognized errors in the total experimental uncertainty. ► Procedure was applied for processing half-life discrepant experimental data. ► Results of the calculations are compared to the ENSDF and DDEP evaluations.

  16. Noise removing in encrypted color images by statistical analysis

    Science.gov (United States)

    Islam, N.; Puech, W.

    2012-03-01

    Cryptographic techniques are used to secure confidential data from unauthorized access but these techniques are very sensitive to noise. A single bit change in encrypted data can have catastrophic impact over the decrypted data. This paper addresses the problem of removing bit error in visual data which are encrypted using AES algorithm in the CBC mode. In order to remove the noise, a method is proposed which is based on the statistical analysis of each block during the decryption. The proposed method exploits local statistics of the visual data and confusion/diffusion properties of the encryption algorithm to remove the errors. Experimental results show that the proposed method can be used at the receiving end for the possible solution for noise removing in visual data in encrypted domain.

  17. Statistical Analysis of Radio Propagation Channel in Ruins Environment

    Directory of Open Access Journals (Sweden)

    Jiao He

    2015-01-01

    Full Text Available The cellphone based localization system for search and rescue in complex high density ruins has attracted a great interest in recent years, where the radio channel characteristics are critical for design and development of such a system. This paper presents a spatial smoothing estimation via rotational invariance technique (SS-ESPRIT for radio channel characterization of high density ruins. The radio propagations at three typical mobile communication bands (0.9, 1.8, and 2 GHz are investigated in two different scenarios. Channel parameters, such as arrival time, delays, and complex amplitudes, are statistically analyzed. Furthermore, a channel simulator is built based on these statistics. By comparison analysis of average excess delay and delay spread, the validation results show a good agreement between the measurements and channel modeling results.

  18. Statistical Analysis of Sport Movement Observations: the Case of Orienteering

    Science.gov (United States)

    Amouzandeh, K.; Karimipour, F.

    2017-09-01

    Study of movement observations is becoming more popular in several applications. Particularly, analyzing sport movement time series has been considered as a demanding area. However, most of the attempts made on analyzing movement sport data have focused on spatial aspects of movement to extract some movement characteristics, such as spatial patterns and similarities. This paper proposes statistical analysis of sport movement observations, which refers to analyzing changes in the spatial movement attributes (e.g. distance, altitude and slope) and non-spatial movement attributes (e.g. speed and heart rate) of athletes. As the case study, an example dataset of movement observations acquired during the "orienteering" sport is presented and statistically analyzed.

  19. Predictions of outcomes of renal stones after extracorporeal shock wave lithotripsy from stone characteristics determined by unenhanced helical computed tomography: a multivariate analysis

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Li-Jen; Wong, Yon-Cheong [Chang Gung University, Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Taipei (Taiwan); Chuang, Cheng-Keng; Chu, Sheng-Hsien; Chen, Chih-Shou; Chiang, Yang-Jen [Chang Gung University, Department of Urology, Chang Gung Memorial Hospital, Taipei (Taiwan); See, Lai-Chu [Chang Gung University, Department of Biostatistics Center, Chang Gung Memorial Hospital, Taipei (Taiwan)

    2005-11-01

    The aim of our study is to analyze the relationships between the characteristics of renal stones determined by unenhanced helical computed tomography (UHCT) and their outcomes after extracorporeal shock wave lithotripsy (ESWL) as well as to predict ESWL outcomes of renal stones by their UHCT characteristics with the use of multivariate analysis. During a 7-month period, 80 adult patients with renal stones underwent ESWL as well as UHCT both before and 3 months after ESWL. Of the 80 patients, 42 patients were classified as ESWL successes and 38 as ESWL failures based on their post-ESWL UHCT findings. For pre-ESWL UHCT, a stone number of more than 2 (P=0.0236), a maximal stone size of greater than 12 mm (P<0.0001), a stone burden of more than 700 mm{sup 3} (P<0.0001), a maximal stone density of more than 900 HU (P=0.0008) and nonround/oval stones (P=0.0007) were associated with ESWL failure outcomes. Multivariate analysis demonstrated that a stone burden of more than 700 mm{sup 3} (P=0.0003), the presence of nonround/oval stones (P=0.0072) and a maximal stone density of more than 900 HU (P=0.0430) were statistically significant predictors of a failure outcome for ESWL. Thus, the analysis of stone characteristics of renal stones by UHCT is helpful in selecting appropriate patients undergoing ESWL for favorable outcomes and reduces the overall costs of the treatment of renal stones. (orig.)

  20. SeDA: A software package for the statistical analysis of the instrument drift

    International Nuclear Information System (INIS)

    Lee, H. J.; Jang, S. C.; Lim, T. J.

    2006-01-01

    The setpoints for safety-related equipment are affected by many sources of an uncertainty. ANSI/ISA-S67.04.01-2000 [1] and ISA-RP6 7.04.02-2000 [2] suggested the statistical approaches for ensuring that the safety-related instrument setpoints were established and maintained within the technical specification limits [3]. However, Jang et al. [4] indicated that the preceding methodologies for a setpoint drift analysis might be insufficient to manage a setpoint drift on an instrumentation device and proposed new statistical analysis procedures for the management of a setpoint drift, based on the plant specific as-found/as-left data. Although IHPA (Instrument History Performance Analysis) is a widely known commercial software package to analyze an instrument setpoint drift, several steps in the new procedure cannot be performed by using it because it is based on the statistical approaches suggested in the ANSI/ISA-S67.04.01 -2000 [1] and ISA-RP67.04.02-2000 [2], In this paper we present a software package (SeDA: Setpoint Drift Analysis) that implements new methodologies, and which is easy to use, as it is accompanied by powerful graphical tools. (authors)

  1. Statistical analysis in MSW collection performance assessment.

    Science.gov (United States)

    Teixeira, Carlos Afonso; Avelino, Catarina; Ferreira, Fátima; Bentes, Isabel

    2014-09-01

    The increase of Municipal Solid Waste (MSW) generated over the last years forces waste managers pursuing more effective collection schemes, technically viable, environmentally effective and economically sustainable. The assessment of MSW services using performance indicators plays a crucial role for improving service quality. In this work, we focus on the relevance of regular system monitoring as a service assessment tool. In particular, we select and test a core-set of MSW collection performance indicators (effective collection distance, effective collection time and effective fuel consumption) that highlights collection system strengths and weaknesses and supports pro-active management decision-making and strategic planning. A statistical analysis was conducted with data collected in mixed collection system of Oporto Municipality, Portugal, during one year, a week per month. This analysis provides collection circuits' operational assessment and supports effective short-term municipality collection strategies at the level of, e.g., collection frequency and timetables, and type of containers. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Implementation of statistical analysis methods for medical physics data

    International Nuclear Information System (INIS)

    Teixeira, Marilia S.; Pinto, Nivia G.P.; Barroso, Regina C.; Oliveira, Luis F.

    2009-01-01

    The objective of biomedical research with different radiation natures is to contribute for the understanding of the basic physics and biochemistry of the biological systems, the disease diagnostic and the development of the therapeutic techniques. The main benefits are: the cure of tumors through the therapy, the anticipated detection of diseases through the diagnostic, the using as prophylactic mean for blood transfusion, etc. Therefore, for the better understanding of the biological interactions occurring after exposure to radiation, it is necessary for the optimization of therapeutic procedures and strategies for reduction of radioinduced effects. The group pf applied physics of the Physics Institute of UERJ have been working in the characterization of biological samples (human tissues, teeth, saliva, soil, plants, sediments, air, water, organic matrixes, ceramics, fossil material, among others) using X-rays diffraction and X-ray fluorescence. The application of these techniques for measurement, analysis and interpretation of the biological tissues characteristics are experimenting considerable interest in the Medical and Environmental Physics. All quantitative data analysis must be initiated with descriptive statistic calculation (means and standard deviations) in order to obtain a previous notion on what the analysis will reveal. It is well known que o high values of standard deviation found in experimental measurements of biologicals samples can be attributed to biological factors, due to the specific characteristics of each individual (age, gender, environment, alimentary habits, etc). This work has the main objective the development of a program for the use of specific statistic methods for the optimization of experimental data an analysis. The specialized programs for this analysis are proprietary, another objective of this work is the implementation of a code which is free and can be shared by the other research groups. As the program developed since the

  3. Statistical analysis of AFM topographic images of self-assembled quantum dots

    Energy Technology Data Exchange (ETDEWEB)

    Sevriuk, V. A.; Brunkov, P. N., E-mail: brunkov@mail.ioffe.ru; Shalnev, I. V.; Gutkin, A. A.; Klimko, G. V.; Gronin, S. V.; Sorokin, S. V.; Konnikov, S. G. [Russian Academy of Sciences, Ioffe Physical-Technical Institute (Russian Federation)

    2013-07-15

    To obtain statistical data on quantum-dot sizes, AFM topographic images of the substrate on which the dots under study are grown are analyzed. Due to the nonideality of the substrate containing height differences on the order of the size of nanoparticles at distances of 1-10 {mu}m and the insufficient resolution of closely arranged dots due to the finite curvature radius of the AFM probe, automation of the statistical analysis of their large dot array requires special techniques for processing topographic images to eliminate the loss of a particle fraction during conventional processing. As such a technique, convolution of the initial matrix of the AFM image with a specially selected matrix is used. This makes it possible to determine the position of each nanoparticle and, using the initial matrix, to measure their geometrical parameters. The results of statistical analysis by this method of self-assembled InAs quantum dots formed on the surface of an AlGaAs epitaxial layer are presented. It is shown that their concentration, average size, and half-width of height distribution depend strongly on the In flow and total amount of deposited InAs which are varied within insignificant limits.

  4. Statistical Analysis of Environmental Tritium around Wolsong Site

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Ju Youl [FNC Technology Co., Yongin (Korea, Republic of)

    2010-04-15

    To find the relationship among airborne tritium, tritium in rainwater, TFWT (Tissue Free Water Tritium) and TBT (Tissue Bound Tritium), statistical analysis is conducted based on tritium data measured at KHNP employees' house around Wolsong nuclear power plants during 10 years from 1999 to 2008. The results show that tritium in such media exhibits a strong seasonal and annual periodicity. Tritium concentration in rainwater is observed to be highly correlated with TFWT and directly transmitted to TFWT without delay. The response of environmental radioactivity of tritium around Wolsong site is analyzed using time-series technique and non-parametric trend analysis. Tritium in the atmosphere and rainwater is strongly auto-correlated by seasonal and annual periodicity. TFWT concentration in pine needle is proven to be more sensitive to rainfall phenomenon than other weather variables. Non-parametric trend analysis of TFWT concentration within pine needle shows a increasing slope in terms of confidence level of 95%. This study demonstrates a usefulness of time-series and trend analysis for the interpretation of environmental radioactivity relationship with various environmental media.

  5. Statistical Analysis of the Polarimetric Cloud Analysis and Seeding Test (POLCAST) Field Projects

    Science.gov (United States)

    Ekness, Jamie Lynn

    The North Dakota farming industry brings in more than $4.1 billion annually in cash receipts. Unfortunately, agriculture sales vary significantly from year to year, which is due in large part to weather events such as hail storms and droughts. One method to mitigate drought is to use hygroscopic seeding to increase the precipitation efficiency of clouds. The North Dakota Atmospheric Research Board (NDARB) sponsored the Polarimetric Cloud Analysis and Seeding Test (POLCAST) research project to determine the effectiveness of hygroscopic seeding in North Dakota. The POLCAST field projects obtained airborne and radar observations, while conducting randomized cloud seeding. The Thunderstorm Identification Tracking and Nowcasting (TITAN) program is used to analyze radar data (33 usable cases) in determining differences in the duration of the storm, rain rate and total rain amount between seeded and non-seeded clouds. The single ratio of seeded to non-seeded cases is 1.56 (0.28 mm/0.18 mm) or 56% increase for the average hourly rainfall during the first 60 minutes after target selection. A seeding effect is indicated with the lifetime of the storms increasing by 41 % between seeded and non-seeded clouds for the first 60 minutes past seeding decision. A double ratio statistic, a comparison of radar derived rain amount of the last 40 minutes of a case (seed/non-seed), compared to the first 20 minutes (seed/non-seed), is used to account for the natural variability of the cloud system and gives a double ratio of 1.85. The Mann-Whitney test on the double ratio of seeded to non-seeded cases (33 cases) gives a significance (p-value) of 0.063. Bootstrapping analysis of the POLCAST set indicates that 50 cases would provide statistically significant results based on the Mann-Whitney test of the double ratio. All the statistical analysis conducted on the POLCAST data set show that hygroscopic seeding in North Dakota does increase precipitation. While an additional POLCAST field

  6. The Effects of Smoking and Obesity on ICSI Outcomes: A Retrospective Analysis

    Directory of Open Access Journals (Sweden)

    Bülent Haydardedeoğlu

    2010-04-01

    Full Text Available Cigarette smoking and obesity are both common health problems in developed and developing countries and are associated with an increased morbidity and mortality. The fecundity rate is found to be decreased by both smoking and obesity in unassisted reproduction in large epidemiologic studies. In the literature, the effects of obesity and smoking on ICSI are demonstrated separately. Our current study aims to reveal the effects of smoking together with obesity on ICSI outcomes. Our result showed that there was no statistically significant difference of outcomes between smokers and nonsmokers in all BMI groups which scheduled to GnRH Agonist ICSI cycle.

  7. Evaluation of trauma care using TRISS method: the role of adjusted misclassification rate and adjusted w-statistic.

    Science.gov (United States)

    Llullaku, Sadik S; Hyseni, Nexhmi Sh; Bytyçi, Cen I; Rexhepi, Sylejman K

    2009-01-15

    Major trauma is a leading cause of death worldwide. Evaluation of trauma care using Trauma Injury and Injury Severity Score (TRISS) method is focused in trauma outcome (deaths and survivors). For testing TRISS method TRISS misclassification rate is used. Calculating w-statistic, as a difference between observed and TRISS expected survivors, we compare our trauma care results with the TRISS standard. The aim of this study is to analyze interaction between misclassification rate and w-statistic and to adjust these parameters to be closer to the truth. Analysis of components of TRISS misclassification rate and w-statistic and actual trauma outcome. The component of false negative (FN) (by TRISS method unexpected deaths) has two parts: preventable (Pd) and non-preventable (nonPd) trauma deaths. Pd represents inappropriate trauma care of an institution; otherwise nonpreventable trauma deaths represents errors in TRISS method. Removing patients with preventable trauma deaths we get an Adjusted misclassification rate: (FP + FN - Pd)/N or (b+c-Pd)/N. Substracting nonPd from FN value in w-statistic formula we get an Adjusted w-statistic: [FP-(FN - nonPd)]/N, respectively (FP-Pd)/N, or (b-Pd)/N). Because adjusted formulas clean method from inappropriate trauma care, and clean trauma care from the methods error, TRISS adjusted misclassification rate and adjusted w-statistic gives more realistic results and may be used in researches of trauma outcome.

  8. Real-World Outcomes and Critical Thinking: Differential Analysis by Academic Major and Gender

    Directory of Open Access Journals (Sweden)

    Amanda Franco

    2015-08-01

    Full Text Available The Real-World Outcomes is an inventory that measures everyday problematic behaviors that represent decisions where critical thinking is presumably absent; assessing the negative outcomes of poor daily decisions helps to infer the degree of critical thinking that mediates everyday reasoning. In the present paper, we describe the process of translation and cultural adaptation of this inventory to Portuguese. We present evidence of its administration to 259 college students concerning reliability, and differences based on academic major and gender. No statistically significant differences were found, either due to academic major or gender. Results suggest the value of this instrument to assessing daily decision making and life outcomes, and also, to estimate the quality of critical thinking in everyday life.

  9. Evaluation of standardized and applied variables in predicting treatment outcomes of polytrauma patients.

    Science.gov (United States)

    Aksamija, Goran; Mulabdic, Adi; Rasic, Ismar; Muhovic, Samir; Gavric, Igor

    2011-01-01

    Polytrauma is defined as an injury where they are affected by at least two different organ systems or body, with at least one life-threatening injuries. Given the multilevel model care of polytrauma patients within KCUS are inevitable weaknesses in the management of this category of patients. To determine the dynamics of existing procedures in treatment of polytrauma patients on admission to KCUS, and based on statistical analysis of variables applied to determine and define the factors that influence the final outcome of treatment, and determine their mutual relationship, which may result in eliminating the flaws in the approach to the problem. The study was based on 263 polytrauma patients. Parametric and non-parametric statistical methods were used. Basic statistics were calculated, based on the calculated parameters for the final achievement of research objectives, multicoleration analysis, image analysis, discriminant analysis and multifactorial analysis were used. From the universe of variables for this study we selected sample of n = 25 variables, of which the first two modular, others belong to the common measurement space (n = 23) and in this paper defined as a system variable methods, procedures and assessments of polytrauma patients. After the multicoleration analysis, since the image analysis gave a reliable measurement results, we started the analysis of eigenvalues, that is defining the factors upon which they obtain information about the system solve the problem of the existing model and its correlation with treatment outcome. The study singled out the essential factors that determine the current organizational model of care, which may affect the treatment and better outcome of polytrauma patients. This analysis has shown the maximum correlative relationships between these practices and contributed to development guidelines that are defined by isolated factors.

  10. Statistical Analysis of Designed Experiments Theory and Applications

    CERN Document Server

    Tamhane, Ajit C

    2012-01-01

    A indispensable guide to understanding and designing modern experiments The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences. The book supplies a foundation for the

  11. Multivariate statistical analysis of major and trace element data for ...

    African Journals Online (AJOL)

    Multivariate statistical analysis of major and trace element data for niobium exploration in the peralkaline granites of the anorogenic ring-complex province of Nigeria. PO Ogunleye, EC Ike, I Garba. Abstract. No Abstract Available Journal of Mining and Geology Vol.40(2) 2004: 107-117. Full Text: EMAIL FULL TEXT EMAIL ...

  12. Statistical shape analysis using 3D Poisson equation--A quantitatively validated approach.

    Science.gov (United States)

    Gao, Yi; Bouix, Sylvain

    2016-05-01

    Statistical shape analysis has been an important area of research with applications in biology, anatomy, neuroscience, agriculture, paleontology, etc. Unfortunately, the proposed methods are rarely quantitatively evaluated, and as shown in recent studies, when they are evaluated, significant discrepancies exist in their outputs. In this work, we concentrate on the problem of finding the consistent location of deformation between two population of shapes. We propose a new shape analysis algorithm along with a framework to perform a quantitative evaluation of its performance. Specifically, the algorithm constructs a Signed Poisson Map (SPoM) by solving two Poisson equations on the volumetric shapes of arbitrary topology, and statistical analysis is then carried out on the SPoMs. The method is quantitatively evaluated on synthetic shapes and applied on real shape data sets in brain structures. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. For the Love of Statistics: Appreciating and Learning to Apply Experimental Analysis and Statistics through Computer Programming Activities

    Science.gov (United States)

    Mascaró, Maite; Sacristán, Ana Isabel; Rufino, Marta M.

    2016-01-01

    For the past 4 years, we have been involved in a project that aims to enhance the teaching and learning of experimental analysis and statistics, of environmental and biological sciences students, through computational programming activities (using R code). In this project, through an iterative design, we have developed sequences of R-code-based…

  14. Systematic review and meta-analysis of the effect of equine assisted activities and therapies on gross motor outcome in children with cerebral palsy.

    Science.gov (United States)

    Tseng, Sung-Hui; Chen, Hung-Chou; Tam, Ka-Wai

    2013-01-01

    To evaluate the literature on the efficacy of equine assisted activities and therapies (EAAT) on gross motor outcomes representing the ICF component of body functions and activity in children with cerebral palsy (CP). We conducted a systematic review and meta-analysis of randomized controlled trials and observational studies of hippotherapy (HPOT) and therapeutic horseback riding (TR) for children with spastic CP. Gross motor outcomes, assessed via muscle activity and muscle tone, gait, posture and Gross Motor Function Measures (GMFM) were evaluated. Five TR studies and nine HPOT studies were included. Our meta-analysis indicated that short-term HPOT (total riding time 8-10 min) significantly reduced asymmetrical activity of the hip adductor muscles. HPOT could improve postural control in children with spastic CP, GMFCS level < 5. However, the evidence did not show a statistically significant effect on GMFM after long-term HPOT or TR (total riding time, 8-22 h) in children with spastic CP. This systematic review found insufficient evidence to support the claim that long-term TR or HPOT provide a significant benefit to children with spastic CP. We found no statistically significant evidence of either therapeutic effect or maintenance effects on the gross motor activity status in CP children.

  15. Statistical analysis of angular correlation measurements

    International Nuclear Information System (INIS)

    Oliveira, R.A.A.M. de.

    1986-01-01

    Obtaining the multipole mixing ratio, δ, of γ transitions in angular correlation measurements is a statistical problem characterized by the small number of angles in which the observation is made and by the limited statistic of counting, α. The inexistence of a sufficient statistics for the estimator of δ, is shown. Three different estimators for δ were constructed and their properties of consistency, bias and efficiency were tested. Tests were also performed in experimental results obtained in γ-γ directional correlation measurements. (Author) [pt

  16. GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran)

    Science.gov (United States)

    Haghizadeh, Ali; Moghaddam, Davoud Davoudi; Pourghasemi, Hamid Reza

    2017-12-01

    Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster-Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts.

  17. Comparison of the effect of endodontic-periodontal combined lesion on the outcome of endodontic microsurgery with that of isolated endodontic lesion: survival analysis using propensity score analysis.

    Science.gov (United States)

    Song, Minju; Kang, Minji; Kang, Dae Ryong; Jung, Hoi In; Kim, Euiseong

    2018-05-01

    The purpose of this retrospective clinical study was to evaluate the effect of lesion types related to endodontic microsurgery on the clinical outcome. Patients who underwent endodontic microsurgery between March 2001 and March 2014 with a postoperative follow-up period of at least 1 year were included in the study. Survival analyses were conducted to compare the clinical outcomes between isolated endodontic lesion group (endo group) and endodontic-periodontal combined lesion group (endo-perio group) and to evaluate other clinical variables. To reduce the effect of selection bias in this study, the estimated propensity scores were used to match the cases of the endo group with those of the endo-perio group. Among the 414 eligible cases, the 83 cases in the endo-perio group were matched to 166 out of the 331 cases in the endo group based on propensity score matching (PSM). The cumulated success rates of the endo and endo-perio groups were 87.3 and 72.3%, respectively. The median success period of the endo-perio group was 12 years (95% CI: 5.507, 18.498). Lesion type was found to be significant according to both Log-rank test (P = 0.002) and Cox proportional hazard regression analysis (P = 0.001). Among the other clinical variables, sex (female or male), age, and tooth type (anterior, premolar, or molar) were determined to be significant in Cox regression analysis (P lesions had a negative effect on the clinical outcome based on an analysis that utilized PSM, a useful statistical matching method for observational studies. Lesion type is a significant predictor of the outcome of endodontic microsurgery.

  18. Statistical mechanical analysis of the linear vector channel in digital communication

    International Nuclear Information System (INIS)

    Takeda, Koujin; Hatabu, Atsushi; Kabashima, Yoshiyuki

    2007-01-01

    A statistical mechanical framework to analyze linear vector channel models in digital wireless communication is proposed for a large system. The framework is a generalization of that proposed for code-division multiple-access systems in Takeda et al (2006 Europhys. Lett. 76 1193) and enables the analysis of the system in which the elements of the channel transfer matrix are statistically correlated with each other. The significance of the proposed scheme is demonstrated by assessing the performance of an existing model of multi-input multi-output communication systems

  19. Monte Carlo based statistical power analysis for mediation models: methods and software.

    Science.gov (United States)

    Zhang, Zhiyong

    2014-12-01

    The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.

  20. Assessment of statistical methods used in library-based approaches to microbial source tracking.

    Science.gov (United States)

    Ritter, Kerry J; Carruthers, Ethan; Carson, C Andrew; Ellender, R D; Harwood, Valerie J; Kingsley, Kyle; Nakatsu, Cindy; Sadowsky, Michael; Shear, Brian; West, Brian; Whitlock, John E; Wiggins, Bruce A; Wilbur, Jayson D

    2003-12-01

    Several commonly used statistical methods for fingerprint identification in microbial source tracking (MST) were examined to assess the effectiveness of pattern-matching algorithms to correctly identify sources. Although numerous statistical methods have been employed for source identification, no widespread consensus exists as to which is most appropriate. A large-scale comparison of several MST methods, using identical fecal sources, presented a unique opportunity to assess the utility of several popular statistical methods. These included discriminant analysis, nearest neighbour analysis, maximum similarity and average similarity, along with several measures of distance or similarity. Threshold criteria for excluding uncertain or poorly matched isolates from final analysis were also examined for their ability to reduce false positives and increase prediction success. Six independent libraries used in the study were constructed from indicator bacteria isolated from fecal materials of humans, seagulls, cows and dogs. Three of these libraries were constructed using the rep-PCR technique and three relied on antibiotic resistance analysis (ARA). Five of the libraries were constructed using Escherichia coli and one using Enterococcus spp. (ARA). Overall, the outcome of this study suggests a high degree of variability across statistical methods. Despite large differences in correct classification rates among the statistical methods, no single statistical approach emerged as superior. Thresholds failed to consistently increase rates of correct classification and improvement was often associated with substantial effective sample size reduction. Recommendations are provided to aid in selecting appropriate analyses for these types of data.

  1. A statistical analysis of the impact of advertising signs on road safety.

    Science.gov (United States)

    Yannis, George; Papadimitriou, Eleonora; Papantoniou, Panagiotis; Voulgari, Chrisoula

    2013-01-01

    This research aims to investigate the impact of advertising signs on road safety. An exhaustive review of international literature was carried out on the effect of advertising signs on driver behaviour and safety. Moreover, a before-and-after statistical analysis with control groups was applied on several road sites with different characteristics in the Athens metropolitan area, in Greece, in order to investigate the correlation between the placement or removal of advertising signs and the related occurrence of road accidents. Road accident data for the 'before' and 'after' periods on the test sites and the control sites were extracted from the database of the Hellenic Statistical Authority, and the selected 'before' and 'after' periods vary from 2.5 to 6 years. The statistical analysis shows no statistical correlation between road accidents and advertising signs in none of the nine sites examined, as the confidence intervals of the estimated safety effects are non-significant at 95% confidence level. This can be explained by the fact that, in the examined road sites, drivers are overloaded with information (traffic signs, directions signs, labels of shops, pedestrians and other vehicles, etc.) so that the additional information load from advertising signs may not further distract them.

  2. Building the Community Online Resource for Statistical Seismicity Analysis (CORSSA)

    Science.gov (United States)

    Michael, A. J.; Wiemer, S.; Zechar, J. D.; Hardebeck, J. L.; Naylor, M.; Zhuang, J.; Steacy, S.; Corssa Executive Committee

    2010-12-01

    Statistical seismology is critical to the understanding of seismicity, the testing of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology - especially to those aspects with great impact on public policy - statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA). CORSSA is a web-based educational platform that is authoritative, up-to-date, prominent, and user-friendly. We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each containing between four and eight articles. The CORSSA web page, www.corssa.org, officially unveiled on September 6, 2010, debuts with an initial set of approximately 10 to 15 articles available online for viewing and commenting with additional articles to be added over the coming months. Each article will be peer-reviewed and will present a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles will include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. A special article will compare and review

  3. Multivariate analysis on unilateral cleft lip and palate treatment outcome by EUROCRAN index: A retrospective study.

    Science.gov (United States)

    Yew, Ching Ching; Alam, Mohammad Khursheed; Rahman, Shaifulizan Abdul

    2016-10-01

    This study is to evaluate the dental arch relationship and palatal morphology of unilateral cleft lip and palate patients by using EUROCRAN index, and to assess the factors that affect them using multivariate statistical analysis. A total of one hundred and seven patients from age five to twelve years old with non-syndromic unilateral cleft lip and palate were included in the study. These patients have received cheiloplasty and one stage palatoplasty surgery but yet to receive alveolar bone grafting procedure. Five assessors trained in the use of the EUROCRAN index underwent calibration exercise and ranked the dental arch relationships and palatal morphology of the patients' study models. For intra-rater agreement, the examiners scored the models twice, with two weeks interval in between sessions. Variable factors of the patients were collected and they included gender, site, type and, family history of unilateral cleft lip and palate; absence of lateral incisor on cleft side, cheiloplasty and palatoplasty technique used. Associations between various factors and dental arch relationships were assessed using logistic regression analysis. Dental arch relationship among unilateral cleft lip and palate in local population had relatively worse scoring than other parts of the world. Crude logistics regression analysis did not demonstrate any significant associations among the various socio-demographic factors, cheiloplasty and palatoplasty techniques used with the dental arch relationship outcome. This study has limitations that might have affected the results, example: having multiple operators performing the surgeries and the inability to access the influence of underlying genetic predisposed cranio-facial variability. These may have substantial influence on the treatment outcome. The factors that can affect unilateral cleft lip and palate treatment outcome is multifactorial in nature and remained controversial in general. Copyright © 2016 Elsevier Ireland Ltd. All

  4. A multicenter study of the outcomes of the surgical treatment of adolescent idiopathic scoliosis using the Scoliosis Research Society (SRS) outcome instrument.

    Science.gov (United States)

    Merola, Andrew A; Haher, Thomas R; Brkaric, Mario; Panagopoulos, Georgia; Mathur, Samir; Kohani, Omid; Lowe, Thomas G; Lenke, Larry G; Wenger, Dennis R; Newton, Peter O; Clements, David H; Betz, Randal R

    2002-09-15

    A multicenter study of the outcomes of the surgical treatment of adolescent idiopathic scoliosis using the Scoliosis Research Society Questionnaire (SRS 24). To evaluate the patient based outcome of the surgical treatment of adolescent idiopathic scoliosis. A paucity of information exists with respect to patient measures of outcome regarding the surgical treatment of adolescent idiopathic scoliosis. To our knowledge, no prospective outcome study on this topic thus far exists. Using the SRS 24 questionnaire, seven scoliosis centers agreed to prospectively assess outcome for surgically treated patients with adolescent idiopathic scoliosis. Data were collected before surgery and at 24 months after surgery. Data were analyzed using paired and independent samples t test for all seven SRS 24 questionnaire domains (Pain, General Self-Image, Postoperative Self-Image, Postoperative Function, Function From Back Condition, General Level of Activity, and Satisfaction) using Statistical Package for Social Science. The domains were analyzed with respect to the total cohort, gender, curve magnitude, and type of surgery using independent-samples t tests. A total of 242 patients were included in our analysis. A baseline preoperative pain level of 3.68 of 5 was found. This improved to 4.63 after surgery, representing an improvement of 0.95 points. Surgical intervention was associated with improving outcome when compared with preoperative status. Pain, General Self-Image, Function From Back Condition, and Level of Activity all demonstrated statistically significant improvement as compared with preoperative status (P adolescent scoliosis population. Pain scores were improved in our study population at the 2-year postsurgical follow-up. Statistically significant improvements were likewise seen in the General Self-Image, Function From Back Condition, and Level of Activity domains. The present study demonstrates the ability of surgery to improve the outcome of patients afflicted with

  5. Meta- and statistical analysis of single-case intervention research data: quantitative gifts and a wish list.

    Science.gov (United States)

    Kratochwill, Thomas R; Levin, Joel R

    2014-04-01

    In this commentary, we add to the spirit of the articles appearing in the special series devoted to meta- and statistical analysis of single-case intervention-design data. Following a brief discussion of historical factors leading to our initial involvement in statistical analysis of such data, we discuss: (a) the value added by including statistical-analysis recommendations in the What Works Clearinghouse Standards for single-case intervention designs; (b) the importance of visual analysis in single-case intervention research, along with the distinctive role that could be played by single-case effect-size measures; and (c) the elevated internal validity and statistical-conclusion validity afforded by the incorporation of various forms of randomization into basic single-case design structures. For the future, we envision more widespread application of quantitative analyses, as critical adjuncts to visual analysis, in both primary single-case intervention research studies and literature reviews in the behavioral, educational, and health sciences. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  6. Statistical analysis of the spatial distribution of galaxies and clusters

    International Nuclear Information System (INIS)

    Cappi, Alberto

    1993-01-01

    This thesis deals with the analysis of the distribution of galaxies and clusters, describing some observational problems and statistical results. First chapter gives a theoretical introduction, aiming to describe the framework of the formation of structures, tracing the history of the Universe from the Planck time, t_p = 10"-"4"3 sec and temperature corresponding to 10"1"9 GeV, to the present epoch. The most usual statistical tools and models of the galaxy distribution, with their advantages and limitations, are described in chapter two. A study of the main observed properties of galaxy clustering, together with a detailed statistical analysis of the effects of selecting galaxies according to apparent magnitude or diameter, is reported in chapter three. Chapter four delineates some properties of groups of galaxies, explaining the reasons of discrepant results on group distributions. Chapter five is a study of the distribution of galaxy clusters, with different statistical tools, like correlations, percolation, void probability function and counts in cells; it is found the same scaling-invariant behaviour of galaxies. Chapter six describes our finding that rich galaxy clusters too belong to the fundamental plane of elliptical galaxies, and gives a discussion of its possible implications. Finally chapter seven reviews the possibilities offered by multi-slit and multi-fibre spectrographs, and I present some observational work on nearby and distant galaxy clusters. In particular, I show the opportunities offered by ongoing surveys of galaxies coupled with multi-object fibre spectrographs, focusing on the ESO Key Programme A galaxy redshift survey in the south galactic pole region to which I collaborate and on MEFOS, a multi-fibre instrument with automatic positioning. Published papers related to the work described in this thesis are reported in the last appendix. (author) [fr

  7. Operational statistical analysis of the results of computer-based testing of students

    Directory of Open Access Journals (Sweden)

    Виктор Иванович Нардюжев

    2018-12-01

    Full Text Available The article is devoted to the issues of statistical analysis of results of computer-based testing for evaluation of educational achievements of students. The issues are relevant due to the fact that computerbased testing in Russian universities has become an important method for evaluation of educational achievements of students and quality of modern educational process. Usage of modern methods and programs for statistical analysis of results of computer-based testing and assessment of quality of developed tests is an actual problem for every university teacher. The article shows how the authors solve this problem using their own program “StatInfo”. For several years the program has been successfully applied in a credit system of education at such technological stages as loading computerbased testing protocols into a database, formation of queries, generation of reports, lists, and matrices of answers for statistical analysis of quality of test items. Methodology, experience and some results of its usage by university teachers are described in the article. Related topics of a test development, models, algorithms, technologies, and software for large scale computer-based testing has been discussed by the authors in their previous publications which are presented in the reference list.

  8. Statistical analysis of seismicity and hazard estimation for Italy (mixed approach). Statistical parameters of main shocks and aftershocks in the Italian region

    International Nuclear Information System (INIS)

    Molchan, G.M.; Kronrod, T.L.; Dmitrieva, O.E.

    1995-03-01

    The catalog of earthquakes of Italy (1900-1993) is analyzed in the present work. The following problems have been considered: 1) a choice of the operating magnitude, 2) an analysis of data completeness, and 3) a grouping (in time and in space). The catalog has been separated into main shocks and aftershocks. Statistical estimations of seismicity parameters (a,b) are performed for the seismogenetic zones defined by GNDT. The non-standard elements of the analysis performed are: (a) statistical estimation and comparison of seismicity parameters under the condition of arbitrary data grouping in magnitude, time and space; (b) use of a not conventional statistical method for the aftershock identification; the method is based on the idea of optimizing two kinds of errors in the aftershock identification process; (c) use of the aftershock zones to reveal seismically- interrelated seismogenic zones. This procedure contributes to the stability of the estimation of the ''b-value'' Refs, 25 figs, tabs

  9. Analysis and classification of ECG-waves and rhythms using circular statistics and vector strength

    Directory of Open Access Journals (Sweden)

    Janßen Jan-Dirk

    2017-09-01

    Full Text Available The most common way to analyse heart rhythm is to calculate the RR-interval and the heart rate variability. For further evaluation, descriptive statistics are often used. Here we introduce a new and more natural heart rhythm analysis tool that is based on circular statistics and vector strength. Vector strength is a tool to measure the periodicity or lack of periodicity of a signal. We divide the signal into non-overlapping window segments and project the detected R-waves around the unit circle using the complex exponential function and the median RR-interval. In addition, we calculate the vector strength and apply circular statistics as wells as an angular histogram on the R-wave vectors. This approach enables an intuitive visualization and analysis of rhythmicity. Our results show that ECG-waves and rhythms can be easily visualized, analysed and classified by circular statistics and vector strength.

  10. Outcomes analysis in 100 liver transplantation patients.

    Science.gov (United States)

    Geevarghese, S K; Bradley, A E; Wright, J K; Chapman, W C; Feurer, I; Payne, J L; Hunter, E B; Pinson, C W

    1998-05-01

    There is an increasing demand for outcomes analysis, including quality of life and financial analysis, following medical interventions and surgical procedures. We analyzed outcomes for 100 consecutive patients undergoing liver transplantation during a period of case management revision. Patient survival was calculated by Kaplan-Meier actuarial methods. The Karnofsky performance status was objectively assessed for surviving patients up to 6 years after transplantation and was evaluated by repeated measures analysis of variance and covariance. Subjective evaluation of quality of life over time was obtained using the Psychosocial Adjustment to Illness Scale. The correlations between time and scale were calculated. Financial data were accumulated from billing records. Six-month, 1-year, 2-year, and 3- through 5-year survival was 86%, 84%, 83%, and 78%, respectively. Karnofsky performance status confirmed poor functional status preoperatively with a mean of 53 +/- 2, but significantly improving to 72 +/- 2 at 3 months, 80 +/- 2 at 6 months, 90 +/- 1 at 1 year, 92 +/- 1 at 2 years, 94 +/- 1 at 3 years, 96 +/- 1 at 4 years, and 97 +/- 1 at 5 years (P <0.001). Psychosocial Adjustment to Illness Scale scores demonstrated significant improvement following transplantation overall (r = -0.33), improving most in sexual relationships (r = -0.41), and domestic environment (r = -0.35; P <0.001). Median length of stay for the first half of the patients was 19 days declining to 11 days for the second half. Median hospital charges declined from $105,000 to $90,000. Quality of life parameters assessed both by care givers (Karnofsky) and by patients (Psychosocial Adjustment to Illness Scale) improved dramatically following transplantation and over time, demonstrating that liver transplantation effectively restores a good quality of life. Outcomes can be improved while reducing length of stay and charges through modifications in case management.

  11. Consolidity analysis for fully fuzzy functions, matrices, probability and statistics

    Directory of Open Access Journals (Sweden)

    Walaa Ibrahim Gabr

    2015-03-01

    Full Text Available The paper presents a comprehensive review of the know-how for developing the systems consolidity theory for modeling, analysis, optimization and design in fully fuzzy environment. The solving of systems consolidity theory included its development for handling new functions of different dimensionalities, fuzzy analytic geometry, fuzzy vector analysis, functions of fuzzy complex variables, ordinary differentiation of fuzzy functions and partial fraction of fuzzy polynomials. On the other hand, the handling of fuzzy matrices covered determinants of fuzzy matrices, the eigenvalues of fuzzy matrices, and solving least-squares fuzzy linear equations. The approach demonstrated to be also applicable in a systematic way in handling new fuzzy probabilistic and statistical problems. This included extending the conventional probabilistic and statistical analysis for handling fuzzy random data. Application also covered the consolidity of fuzzy optimization problems. Various numerical examples solved have demonstrated that the new consolidity concept is highly effective in solving in a compact form the propagation of fuzziness in linear, nonlinear, multivariable and dynamic problems with different types of complexities. Finally, it is demonstrated that the implementation of the suggested fuzzy mathematics can be easily embedded within normal mathematics through building special fuzzy functions library inside the computational Matlab Toolbox or using other similar software languages.

  12. A novel complete-case analysis to determine statistical significance between treatments in an intention-to-treat population of randomized clinical trials involving missing data.

    Science.gov (United States)

    Liu, Wei; Ding, Jinhui

    2018-04-01

    The application of the principle of the intention-to-treat (ITT) to the analysis of clinical trials is challenged in the presence of missing outcome data. The consequences of stopping an assigned treatment in a withdrawn subject are unknown. It is difficult to make a single assumption about missing mechanisms for all clinical trials because there are complicated reactions in the human body to drugs due to the presence of complex biological networks, leading to data missing randomly or non-randomly. Currently there is no statistical method that can tell whether a difference between two treatments in the ITT population of a randomized clinical trial with missing data is significant at a pre-specified level. Making no assumptions about the missing mechanisms, we propose a generalized complete-case (GCC) analysis based on the data of completers. An evaluation of the impact of missing data on the ITT analysis reveals that a statistically significant GCC result implies a significant treatment effect in the ITT population at a pre-specified significance level unless, relative to the comparator, the test drug is poisonous to the non-completers as documented in their medical records. Applications of the GCC analysis are illustrated using literature data, and its properties and limits are discussed.

  13. A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data

    Directory of Open Access Journals (Sweden)

    Maria Vinaixa

    2012-10-01

    Full Text Available Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features significantly altered between samples. By comparing the retention time and MS/MS data of a model compound to that from the altered feature of interest in the research sample, metabolites can be then unequivocally identified. This paper reports on a comprehensive overview of a workflow for statistical analysis to rank relevant metabolite features that will be selected for further MS/MS experiments. We focus on univariate data analysis applied in parallel on all detected features. Characteristics and challenges of this analysis are discussed and illustrated using four different real LC/MS untargeted metabolomic datasets. We demonstrate the influence of considering or violating mathematical assumptions on which univariate statistical test rely, using high-dimensional LC/MS datasets. Issues in data analysis such as determination of sample size, analytical variation, assumption of normality and homocedasticity, or correction for multiple testing are discussed and illustrated in the context of our four untargeted LC/MS working examples.

  14. Analysis and Comprehensive Analytical Modeling of Statistical Variations in Subthreshold MOSFET's High Frequency Characteristics

    Directory of Open Access Journals (Sweden)

    Rawid Banchuin

    2014-01-01

    Full Text Available In this research, the analysis of statistical variations in subthreshold MOSFET's high frequency characteristics defined in terms of gate capacitance and transition frequency, have been shown and the resulting comprehensive analytical models of such variations in terms of their variances have been proposed. Major imperfection in the physical level properties including random dopant fluctuation and effects of variations in MOSFET's manufacturing process, have been taken into account in the proposed analysis and modeling. The up to dated comprehensive analytical model of statistical variation in MOSFET's parameter has been used as the basis of analysis and modeling. The resulting models have been found to be both analytic and comprehensive as they are the precise mathematical expressions in terms of physical level variables of MOSFET. Furthermore, they have been verified at the nanometer level by using 65~nm level BSIM4 based benchmarks and have been found to be very accurate with smaller than 5 % average percentages of errors. Hence, the performed analysis gives the resulting models which have been found to be the potential mathematical tool for the statistical and variability aware analysis and design of subthreshold MOSFET based VHF circuits, systems and applications.

  15. Spatial Analysis Along Networks Statistical and Computational Methods

    CERN Document Server

    Okabe, Atsuyuki

    2012-01-01

    In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Process

  16. STATISTICAL ANALYSIS OF SPORT MOVEMENT OBSERVATIONS: THE CASE OF ORIENTEERING

    Directory of Open Access Journals (Sweden)

    K. Amouzandeh

    2017-09-01

    Full Text Available Study of movement observations is becoming more popular in several applications. Particularly, analyzing sport movement time series has been considered as a demanding area. However, most of the attempts made on analyzing movement sport data have focused on spatial aspects of movement to extract some movement characteristics, such as spatial patterns and similarities. This paper proposes statistical analysis of sport movement observations, which refers to analyzing changes in the spatial movement attributes (e.g. distance, altitude and slope and non-spatial movement attributes (e.g. speed and heart rate of athletes. As the case study, an example dataset of movement observations acquired during the “orienteering” sport is presented and statistically analyzed.

  17. Statistical Analysis Of Failure Strength Of Material Using Weibull Distribution

    International Nuclear Information System (INIS)

    Entin Hartini; Mike Susmikanti; Antonius Sitompul

    2008-01-01

    In evaluation of ceramic and glass materials strength a statistical approach is necessary Strength of ceramic and glass depend on its measure and size distribution of flaws in these material. The distribution of strength for ductile material is narrow and close to a Gaussian distribution while strength of brittle materials as ceramic and glass following Weibull distribution. The Weibull distribution is an indicator of the failure of material strength resulting from a distribution of flaw size. In this paper, cumulative probability of material strength to failure probability, cumulative probability of failure versus fracture stress and cumulative probability of reliability of material were calculated. Statistical criteria calculation supporting strength analysis of Silicon Nitride material were done utilizing MATLAB. (author)

  18. On two methods of statistical image analysis

    NARCIS (Netherlands)

    Missimer, J; Knorr, U; Maguire, RP; Herzog, H; Seitz, RJ; Tellman, L; Leenders, K.L.

    1999-01-01

    The computerized brain atlas (CBA) and statistical parametric mapping (SPM) are two procedures for voxel-based statistical evaluation of PET activation studies. Each includes spatial standardization of image volumes, computation of a statistic, and evaluation of its significance. In addition,

  19. PROSA: A computer program for statistical analysis of near-real-time-accountancy (NRTA) data

    International Nuclear Information System (INIS)

    Beedgen, R.; Bicking, U.

    1987-04-01

    The computer program PROSA (Program for Statistical Analysis of NRTA Data) is a tool to decide on the basis of statistical considerations if, in a given sequence of materials balance periods, a loss of material might have occurred or not. The evaluation of the material balance data is based on statistical test procedures. In PROSA three truncated sequential tests are applied to a sequence of material balances. The manual describes the statistical background of PROSA and how to use the computer program on an IBM-PC with DOS 3.1. (orig.) [de

  20. Statistical testing and power analysis for brain-wide association study.

    Science.gov (United States)

    Gong, Weikang; Wan, Lin; Lu, Wenlian; Ma, Liang; Cheng, Fan; Cheng, Wei; Grünewald, Stefan; Feng, Jianfeng

    2018-04-05

    The identification of connexel-wise associations, which involves examining functional connectivities between pairwise voxels across the whole brain, is both statistically and computationally challenging. Although such a connexel-wise methodology has recently been adopted by brain-wide association studies (BWAS) to identify connectivity changes in several mental disorders, such as schizophrenia, autism and depression, the multiple correction and power analysis methods designed specifically for connexel-wise analysis are still lacking. Therefore, we herein report the development of a rigorous statistical framework for connexel-wise significance testing based on the Gaussian random field theory. It includes controlling the family-wise error rate (FWER) of multiple hypothesis testings using topological inference methods, and calculating power and sample size for a connexel-wise study. Our theoretical framework can control the false-positive rate accurately, as validated empirically using two resting-state fMRI datasets. Compared with Bonferroni correction and false discovery rate (FDR), it can reduce false-positive rate and increase statistical power by appropriately utilizing the spatial information of fMRI data. Importantly, our method bypasses the need of non-parametric permutation to correct for multiple comparison, thus, it can efficiently tackle large datasets with high resolution fMRI images. The utility of our method is shown in a case-control study. Our approach can identify altered functional connectivities in a major depression disorder dataset, whereas existing methods fail. A software package is available at https://github.com/weikanggong/BWAS. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Statistical analysis of magnetically soft particles in magnetorheological elastomers

    Science.gov (United States)

    Gundermann, T.; Cremer, P.; Löwen, H.; Menzel, A. M.; Odenbach, S.

    2017-04-01

    The physical properties of magnetorheological elastomers (MRE) are a complex issue and can be influenced and controlled in many ways, e.g. by applying a magnetic field, by external mechanical stimuli, or by an electric potential. In general, the response of MRE materials to these stimuli is crucially dependent on the distribution of the magnetic particles inside the elastomer. Specific knowledge of the interactions between particles or particle clusters is of high relevance for understanding the macroscopic rheological properties and provides an important input for theoretical calculations. In order to gain a better insight into the correlation between the macroscopic effects and microstructure and to generate a database for theoretical analysis, x-ray micro-computed tomography (X-μCT) investigations as a base for a statistical analysis of the particle configurations were carried out. Different MREs with quantities of 2-15 wt% (0.27-2.3 vol%) of iron powder and different allocations of the particles inside the matrix were prepared. The X-μCT results were edited by an image processing software regarding the geometrical properties of the particles with and without the influence of an external magnetic field. Pair correlation functions for the positions of the particles inside the elastomer were calculated to statistically characterize the distributions of the particles in the samples.

  2. Pattern recognition in menstrual bleeding diaries by statistical cluster analysis

    Directory of Open Access Journals (Sweden)

    Wessel Jens

    2009-07-01

    Full Text Available Abstract Background The aim of this paper is to empirically identify a treatment-independent statistical method to describe clinically relevant bleeding patterns by using bleeding diaries of clinical studies on various sex hormone containing drugs. Methods We used the four cluster analysis methods single, average and complete linkage as well as the method of Ward for the pattern recognition in menstrual bleeding diaries. The optimal number of clusters was determined using the semi-partial R2, the cubic cluster criterion, the pseudo-F- and the pseudo-t2-statistic. Finally, the interpretability of the results from a gynecological point of view was assessed. Results The method of Ward yielded distinct clusters of the bleeding diaries. The other methods successively chained the observations into one cluster. The optimal number of distinctive bleeding patterns was six. We found two desirable and four undesirable bleeding patterns. Cyclic and non cyclic bleeding patterns were well separated. Conclusion Using this cluster analysis with the method of Ward medications and devices having an impact on bleeding can be easily compared and categorized.

  3. Potential errors and misuse of statistics in studies on leakage in endodontics.

    Science.gov (United States)

    Lucena, C; Lopez, J M; Pulgar, R; Abalos, C; Valderrama, M J

    2013-04-01

    To assess the quality of the statistical methodology used in studies of leakage in Endodontics, and to compare the results found using appropriate versus inappropriate inferential statistical methods. The search strategy used the descriptors 'root filling' 'microleakage', 'dye penetration', 'dye leakage', 'polymicrobial leakage' and 'fluid filtration' for the time interval 2001-2010 in journals within the categories 'Dentistry, Oral Surgery and Medicine' and 'Materials Science, Biomaterials' of the Journal Citation Report. All retrieved articles were reviewed to find potential pitfalls in statistical methodology that may be encountered during study design, data management or data analysis. The database included 209 papers. In all the studies reviewed, the statistical methods used were appropriate for the category attributed to the outcome variable, but in 41% of the cases, the chi-square test or parametric methods were inappropriately selected subsequently. In 2% of the papers, no statistical test was used. In 99% of cases, a statistically 'significant' or 'not significant' effect was reported as a main finding, whilst only 1% also presented an estimation of the magnitude of the effect. When the appropriate statistical methods were applied in the studies with originally inappropriate data analysis, the conclusions changed in 19% of the cases. Statistical deficiencies in leakage studies may affect their results and interpretation and might be one of the reasons for the poor agreement amongst the reported findings. Therefore, more effort should be made to standardize statistical methodology. © 2012 International Endodontic Journal.

  4. Statistical Analysis and validation

    NARCIS (Netherlands)

    Hoefsloot, H.C.J.; Horvatovich, P.; Bischoff, R.

    2013-01-01

    In this chapter guidelines are given for the selection of a few biomarker candidates from a large number of compounds with a relative low number of samples. The main concepts concerning the statistical validation of the search for biomarkers are discussed. These complicated methods and concepts are

  5. Variability analysis of AGN: a review of results using new statistical criteria

    Science.gov (United States)

    Zibecchi, L.; Andruchow, I.; Cellone, S. A.; Romero, G. E.; Combi, J. A.

    We present here a re-analysis of the variability results of a sample of active galactic nuclei (AGN), which have been observed on several sessions with the 2.15 m "Jorge Sahade" telescope (CASLEO), San Juan, Argentina, and whose results are published (Romero et al. 1999, 2000, 2002; Cellone et al. 2000). The motivation for this new analysis is the implementation, dur- ing the last years, of improvements in the statistical criteria applied, taking quantitatively into account the incidence of the photometric errors (Cellone et al. 2007). This work is framed as a first step in an integral study on the statistical estimators of AGN variability. This study is motivated by the great diversity of statistical tests that have been proposed to analyze the variability of these objects. Since we note that, in some cases, the results of the object variability depend on the test used, we attempt to make a com- parative study of the various tests and analyze, under the given conditions, which of them is the most efficient and reliable.

  6. A Statistical Primer: Understanding Descriptive and Inferential Statistics

    OpenAIRE

    Gillian Byrne

    2007-01-01

    As libraries and librarians move more towards evidence‐based decision making, the data being generated in libraries is growing. Understanding the basics of statistical analysis is crucial for evidence‐based practice (EBP), in order to correctly design and analyze researchas well as to evaluate the research of others. This article covers the fundamentals of descriptive and inferential statistics, from hypothesis construction to sampling to common statistical techniques including chi‐square, co...

  7. Statistical Compilation of the ICT Sector and Policy Analysis | Page 5 ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    The project is designed to expand the scope of conventional investigation beyond the telecommunications industry to include other vertically integrated components of the ICT sector such as manufacturing and services. ... Statistical Compilation of the ICT Sector and Policy Analysis project : country experiences; Malaysia.

  8. Statistical Analysis of CFD Solutions From the Fifth AIAA Drag Prediction Workshop

    Science.gov (United States)

    Morrison, Joseph H.

    2013-01-01

    A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from North America, Europe, Asia, and South America using a common grid sequence and multiple turbulence models for the June 2012 fifth Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was the Common Research Model subsonic transport wing-body previously used for the 4th Drag Prediction Workshop. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with previous workshops.

  9. Neutron activation and statistical analysis of pottery from Thera, Greece

    International Nuclear Information System (INIS)

    Kilikoglou, V.; Grimanis, A.P.; Karayannis, M.I.

    1990-01-01

    Neutron activation analysis, in combination with multivariate analysis of the generated data, was used for the chemical characterization of prehistoric pottery from the Greek islands of Thera, Melos (islands with similar geology) and Crete. The statistical procedure which proved that Theran pottery could be distinguished from Melian is described. This discrimination, attained for the first time, was mainly based on the concentrations of the trace elements Sm, Yb, Lu and Cr. Also, Cretan imports to both Thera and Melos were clearly separable from local products. (author) 22 refs.; 1 fig.; 4 tabs

  10. The rank-heat plot is a novel way to present the results from a network meta-analysis including multiple outcomes.

    Science.gov (United States)

    Veroniki, Areti Angeliki; Straus, Sharon E; Fyraridis, Alexandros; Tricco, Andrea C

    2016-08-01

    To present a novel and simple graphical approach to improve the presentation of the treatment ranking in a network meta-analysis (NMA) including multiple outcomes. NMA simultaneously compares many relevant interventions for a clinical condition from a network of trials, and allows ranking of the effectiveness and/or safety of each intervention. There are numerous ways to present the NMA results, which can challenge their interpretation by research users. The rank-heat plot is a novel graph that can be used to quickly recognize which interventions are most likely the best or worst interventions with respect to their effectiveness and/or safety for a single or multiple outcome(s) and may increase interpretability. Using empirical NMAs, we show that the need for a concise and informative presentation of results is imperative, particularly as the number of competing treatments and outcomes in an NMA increases. The rank-heat plot is an efficient way to present the results of ranking statistics, particularly when a large amount of data is available, and it is targeted to users from various backgrounds. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Educational Statistics and School Improvement. Statistics and the Federal Role in Education.

    Science.gov (United States)

    Hawley, Willis D.

    This paper focuses on how educational statistics might better serve the quest for educational improvement in elementary and secondary schools. A model for conceptualizing the sources and processes of school productivity is presented. The Learning Productivity Model suggests that school outcomes are the consequence of the interaction of five…

  12. The statistical analysis of the mobility and the labor force use

    Directory of Open Access Journals (Sweden)

    Daniela-Emanuela Dãnãcicã

    2006-05-01

    Full Text Available The paper approaches some of the classical methods used in statistics for theanalysis of labor force and proposes new ways of current analysis required foradopting optimal economic patterns and strategies. The proposed methods, thelinear mean deviation used in the analysis of the external mobility of the laborforce, the coefficient of variation used in the analysis of the external mobility of thelabor force and two-dimensional table used the coefficient of internal mobilitycalculation, are illustrated by the premises, the calculus methodology, practicalapplications and guidance for their use in adopting and applying optimal economicpolicy.

  13. Statistical analysis of the hydrodynamic pressure in the near field of compressible jets

    International Nuclear Information System (INIS)

    Camussi, R.; Di Marco, A.; Castelain, T.

    2017-01-01

    Highlights: • Statistical properties of pressure fluctuations retrieved through wavelet analysis • Time delay PDFs approximated by a log-normal distribution • Amplitude PDFs approximated by a Gamma distribution • Random variable PDFs weakly dependent upon position and Mach number. • A general stochastic model achieved for the distance dependency - Abstract: This paper is devoted to the statistical characterization of the pressure fluctuations measured in the near field of a compressible jet at two subsonic Mach numbers, 0.6 and 0.9. The analysis is focused on the hydrodynamic pressure measured at different distances from the jet exit and analyzed at the typical frequency associated to the Kelvin–Helmholtz instability. Statistical properties are retrieved by the application of the wavelet transform to the experimental data and the computation of the wavelet scalogram around that frequency. This procedure highlights traces of events that appear intermittently in time and have variable strength. A wavelet-based event tracking procedure has been applied providing a statistical characterization of the time delay between successive events and of their energy level. On this basis, two stochastic models are proposed and validated against the experimental data in the different flow conditions

  14. Categorical data processing for real estate objects valuation using statistical analysis

    Science.gov (United States)

    Parygin, D. S.; Malikov, V. P.; Golubev, A. V.; Sadovnikova, N. P.; Petrova, T. M.; Finogeev, A. G.

    2018-05-01

    Theoretical and practical approaches to the use of statistical methods for studying various properties of infrastructure objects are analyzed in the paper. Methods of forecasting the value of objects are considered. A method for coding categorical variables describing properties of real estate objects is proposed. The analysis of the results of modeling the price of real estate objects using regression analysis and an algorithm based on a comparative approach is carried out.

  15. Statistical assessment on a combined analysis of GRYN-ROMN-UCBN upland vegetation vital signs

    Science.gov (United States)

    Irvine, Kathryn M.; Rodhouse, Thomas J.

    2014-01-01

    As of 2013, Rocky Mountain and Upper Columbia Basin Inventory and Monitoring Networks have multiple years of vegetation data and Greater Yellowstone Network has three years of vegetation data and monitoring is ongoing in all three networks. Our primary objective is to assess whether a combined analysis of these data aimed at exploring correlations with climate and weather data is feasible. We summarize the core survey design elements across protocols and point out the major statistical challenges for a combined analysis at present. The dissimilarity in response designs between ROMN and UCBN-GRYN network protocols presents a statistical challenge that has not been resolved yet. However, the UCBN and GRYN data are compatible as they implement a similar response design; therefore, a combined analysis is feasible and will be pursued in future. When data collected by different networks are combined, the survey design describing the merged dataset is (likely) a complex survey design. A complex survey design is the result of combining datasets from different sampling designs. A complex survey design is characterized by unequal probability sampling, varying stratification, and clustering (see Lohr 2010 Chapter 7 for general overview). Statistical analysis of complex survey data requires modifications to standard methods, one of which is to include survey design weights within a statistical model. We focus on this issue for a combined analysis of upland vegetation from these networks, leaving other topics for future research. We conduct a simulation study on the possible effects of equal versus unequal probability selection of points on parameter estimates of temporal trend using available packages within the R statistical computing package. We find that, as written, using lmer or lm for trend detection in a continuous response and clm and clmm for visually estimated cover classes with “raw” GRTS design weights specified for the weight argument leads to substantially

  16. Lectures on probability and statistics

    International Nuclear Information System (INIS)

    Yost, G.P.

    1984-09-01

    These notes are based on a set of statistics lectures delivered at Imperial College to the first-year postgraduate students in High Energy Physics. They are designed for the professional experimental scientist. We begin with the fundamentals of probability theory, in which one makes statements about the set of possible outcomes of an experiment, based upon a complete a priori understanding of the experiment. For example, in a roll of a set of (fair) dice, one understands a priori that any given side of each die is equally likely to turn up. From that, we can calculate the probability of any specified outcome. We finish with the inverse problem, statistics. Here, one begins with a set of actual data (e.g., the outcomes of a number of rolls of the dice), and attempts to make inferences about the state of nature which gave those data (e.g., the likelihood of seeing any given side of any given die turn up). This is a much more difficult problem, of course, and one's solutions often turn out to be unsatisfactory in one respect or another

  17. NEW PARADIGM OF ANALYSIS OF STATISTICAL AND EXPERT DATA IN PROBLEMS OF ECONOMICS AND MANAGEMENT

    OpenAIRE

    Orlov A. I.

    2014-01-01

    The article is devoted to the methods of analysis of statistical and expert data in problems of economics and management that are discussed in the framework of scientific specialization "Mathematical methods of economy", including organizational-economic and economic-mathematical modeling, econometrics and statistics, as well as economic aspects of decision theory, systems analysis, cybernetics, operations research. The main provisions of the new paradigm of this scientific and practical fiel...

  18. Integrating Expert Knowledge with Statistical Analysis for Landslide Susceptibility Assessment at Regional Scale

    Directory of Open Access Journals (Sweden)

    Christos Chalkias

    2016-03-01

    Full Text Available In this paper, an integration landslide susceptibility model by combining expert-based and bivariate statistical analysis (Landslide Susceptibility Index—LSI approaches is presented. Factors related with the occurrence of landslides—such as elevation, slope angle, slope aspect, lithology, land cover, Mean Annual Precipitation (MAP and Peak Ground Acceleration (PGA—were analyzed within a GIS environment. This integrated model produced a landslide susceptibility map which categorized the study area according to the probability level of landslide occurrence. The accuracy of the final map was evaluated by Receiver Operating Characteristics (ROC analysis depending on an independent (validation dataset of landslide events. The prediction ability was found to be 76% revealing that the integration of statistical analysis with human expertise can provide an acceptable landslide susceptibility assessment at regional scale.

  19. Evaluation of trauma care using TRISS method: the role of adjusted misclassification rate and adjusted w-statistic

    Directory of Open Access Journals (Sweden)

    Bytyçi Cen I

    2009-01-01

    Full Text Available Abstract Background Major trauma is a leading cause of death worldwide. Evaluation of trauma care using Trauma Injury and Injury Severity Score (TRISS method is focused in trauma outcome (deaths and survivors. For testing TRISS method TRISS misclassification rate is used. Calculating w-statistic, as a difference between observed and TRISS expected survivors, we compare our trauma care results with the TRISS standard. Aim The aim of this study is to analyze interaction between misclassification rate and w-statistic and to adjust these parameters to be closer to the truth. Materials and methods Analysis of components of TRISS misclassification rate and w-statistic and actual trauma outcome. Results The component of false negative (FN (by TRISS method unexpected deaths has two parts: preventable (Pd and non-preventable (nonPd trauma deaths. Pd represents inappropriate trauma care of an institution; otherwise nonpreventable trauma deaths represents errors in TRISS method. Removing patients with preventable trauma deaths we get an Adjusted misclassification rate: (FP + FN - Pd/N or (b+c-Pd/N. Substracting nonPd from FN value in w-statistic formula we get an Adjusted w-statistic: [FP-(FN - nonPd]/N, respectively (FP-Pd/N, or (b-Pd/N. Conclusion Because adjusted formulas clean method from inappropriate trauma care, and clean trauma care from the methods error, TRISS adjusted misclassification rate and adjusted w-statistic gives more realistic results and may be used in researches of trauma outcome.

  20. Wavelet Statistical Analysis of Low-Latitude Geomagnetic Measurements

    Science.gov (United States)

    Papa, A. R.; Akel, A. F.

    2009-05-01

    Following previous works by our group (Papa et al., JASTP, 2006), where we analyzed a series of records acquired at the Vassouras National Geomagnetic Observatory in Brazil for the month of October 2000, we introduced a wavelet analysis for the same type of data and for other periods. It is well known that wavelets allow a more detailed study in several senses: the time window for analysis can be drastically reduced if compared to other traditional methods (Fourier, for example) and at the same time allow an almost continuous accompaniment of both amplitude and frequency of signals as time goes by. This advantage brings some possibilities for potentially useful forecasting methods of the type also advanced by our group in previous works (see for example, Papa and Sosman, JASTP, 2008). However, the simultaneous statistical analysis of both time series (in our case amplitude and frequency) is a challenging matter and is in this sense that we have found what we consider our main goal. Some possible trends for future works are advanced.

  1. PVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool

    KAUST Repository

    AlTurki, Musab; Meseguer, José

    2011-01-01

    Statistical model checking is an attractive formal analysis method for probabilistic systems such as, for example, cyber-physical systems which are often probabilistic in nature. This paper is about drastically increasing the scalability

  2. Secondhand smoke and adverse fetal outcomes in nonsmoking pregnant women: a meta-analysis.

    Science.gov (United States)

    Leonardi-Bee, Jo; Britton, John; Venn, Andrea

    2011-04-01

    To determine the risk of adverse fetal outcomes of secondhand smoke exposure in nonsmoking pregnant women. This was a systematic review and meta-analysis in accordance with Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. We searched Medline and Embase (to March 2009) and reference lists for eligible studies; no language restrictions were imposed. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were estimated by using random-effect models. Our search was for epidemiologic studies of maternal exposure to secondhand smoke during pregnancy in nonsmoking pregnant women. The main outcome measures were spontaneous abortion, perinatal and neonatal death, stillbirth, and congenital malformations. We identified 19 studies that assessed the effects of secondhand smoke exposure in nonsmoking pregnant women. We found no evidence of a statistically significant effect of secondhand smoke exposure on the risk of spontaneous abortion (OR: 1.17 [95% CI: 0.88-1.54]; 6 studies). However, secondhand smoke exposure significantly increased the risk of stillbirth (OR: 1.23 [95% CI: 1.09-1.38]; 4 studies) and congenital malformation (OR: 1.13 [95% CI: 1.01-1.26]; 7 studies), although none of the associations with specific congenital abnormalities were individually significant. Secondhand smoke exposure had no significant effect on perinatal or neonatal death. Pregnant women who are exposed to secondhand smoke are estimated to be 23% more likely to experience stillbirth and 13% more likely give birth to a child with a congenital malformation. Because the timing and mechanism of this effect is not clear, it is important to prevent secondhand smoke exposure in women before and during pregnancy.

  3. Statistical analysis of the W Cyg light curve

    International Nuclear Information System (INIS)

    Klyus, I.A.

    1983-01-01

    A statistical analysis of the light curve of W Cygni has been carried out. The process of brightness variations brightness of the star is shown to be a stationary stochastic one. The hypothesis of stationarity of the process was checked at the significance level of α=0.05. Oscillations of the brightness with average durations of 131 and 250 days have been found. It is proved that oscillations are narrow-band noise, i.e. cycles. Peaks on the power spectrum corresponding to these cycles exceed 99% confidence interval. It has been stated that the oscillations are independent

  4. Statistical Analysis of a Method to Predict Drug-Polymer Miscibility

    DEFF Research Database (Denmark)

    Knopp, Matthias Manne; Olesen, Niels Erik; Huang, Yanbin

    2016-01-01

    In this study, a method proposed to predict drug-polymer miscibility from differential scanning calorimetry measurements was subjected to statistical analysis. The method is relatively fast and inexpensive and has gained popularity as a result of the increasing interest in the formulation of drug...... as provided in this study. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci....

  5. Accounting for center in the Early External Cephalic Version trials: an empirical comparison of statistical methods to adjust for center in a multicenter trial with binary outcomes.

    Science.gov (United States)

    Reitsma, Angela; Chu, Rong; Thorpe, Julia; McDonald, Sarah; Thabane, Lehana; Hutton, Eileen

    2014-09-26

    Clustering of outcomes at centers involved in multicenter trials is a type of center effect. The Consolidated Standards of Reporting Trials Statement recommends that multicenter randomized controlled trials (RCTs) should account for center effects in their analysis, however most do not. The Early External Cephalic Version (EECV) trials published in 2003 and 2011 stratified by center at randomization, but did not account for center in the analyses, and due to the nature of the intervention and number of centers, may have been prone to center effects. Using data from the EECV trials, we undertook an empirical study to compare various statistical approaches to account for center effect while estimating the impact of external cephalic version timing (early or delayed) on the outcomes of cesarean section, preterm birth, and non-cephalic presentation at the time of birth. The data from the EECV pilot trial and the EECV2 trial were merged into one dataset. Fisher's exact method was used to test the overall effect of external cephalic version timing unadjusted for center effects. Seven statistical models that accounted for center effects were applied to the data. The models included: i) the Mantel-Haenszel test, ii) logistic regression with fixed center effect and fixed treatment effect, iii) center-size weighted and iv) un-weighted logistic regression with fixed center effect and fixed treatment-by-center interaction, iv) logistic regression with random center effect and fixed treatment effect, v) logistic regression with random center effect and random treatment-by-center interaction, and vi) generalized estimating equations. For each of the three outcomes of interest approaches to account for center effect did not alter the overall findings of the trial. The results were similar for the majority of the methods used to adjust for center, illustrating the robustness of the findings. Despite literature that suggests center effect can change the estimate of effect in

  6. A Bifactor Approach to Model Multifaceted Constructs in Statistical Mediation Analysis

    Science.gov (United States)

    Gonzalez, Oscar; MacKinnon, David P.

    2018-01-01

    Statistical mediation analysis allows researchers to identify the most important mediating constructs in the causal process studied. Identifying specific mediators is especially relevant when the hypothesized mediating construct consists of multiple related facets. The general definition of the construct and its facets might relate differently to…

  7. Statistical Compilation of the ICT Sector and Policy Analysis | Page 4 ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Statistical Compilation of the ICT Sector and Policy Analysis. As the presence and influence of information and communication technologies (ICTs) continues to widen and deepen, so too does its impact on economic development. However, much work needs to be done before the linkages between economic development ...

  8. Statistical Compilation of the ICT Sector and Policy Analysis | Page 3 ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Statistical Compilation of the ICT Sector and Policy Analysis. As the presence and influence of information and communication technologies (ICTs) continues to widen and deepen, so too does its impact on economic development. However, much work needs to be done before the linkages between economic development ...

  9. COgnitive behavioural therapy versus standardised medical care for adults with Dissociative non-Epileptic Seizures (CODES): statistical and economic analysis plan for a randomised controlled trial.

    Science.gov (United States)

    Robinson, Emily J; Goldstein, Laura H; McCrone, Paul; Perdue, Iain; Chalder, Trudie; Mellers, John D C; Richardson, Mark P; Murray, Joanna; Reuber, Markus; Medford, Nick; Stone, Jon; Carson, Alan; Landau, Sabine

    2017-06-06

    Dissociative seizures (DSs), also called psychogenic non-epileptic seizures, are a distressing and disabling problem for many patients in neurological settings with high and often unnecessary economic costs. The COgnitive behavioural therapy versus standardised medical care for adults with Dissociative non-Epileptic Seizures (CODES) trial is an evaluation of a specifically tailored psychological intervention with the aims of reducing seizure frequency and severity and improving psychological well-being in adults with DS. The aim of this paper is to report in detail the quantitative and economic analysis plan for the CODES trial, as agreed by the trial steering committee. The CODES trial is a multicentre, pragmatic, parallel group, randomised controlled trial performed to evaluate the clinical effectiveness and cost-effectiveness of 13 sessions of cognitive behavioural therapy (CBT) plus standardised medical care (SMC) compared with SMC alone for adult outpatients with DS. The objectives and design of the trial are summarised, and the aims and procedures of the planned analyses are illustrated. The proposed analysis plan addresses statistical considerations such as maintaining blinding, monitoring adherence with the protocol, describing aspects of treatment and dealing with missing data. The formal analysis approach for the primary and secondary outcomes is described, as are the descriptive statistics that will be reported. This paper provides transparency to the planned inferential analyses for the CODES trial prior to the extraction of outcome data. It also provides an update to the previously published trial protocol and guidance to those conducting similar trials. ISRCTN registry ISRCTN05681227 (registered on 5 March 2014); ClinicalTrials.gov NCT02325544 (registered on 15 December 2014).

  10. ROOT — A C++ framework for petabyte data storage, statistical analysis and visualization

    CERN Document Server

    Antcheva, I; Bellenot, B; Biskup,1, M; Brun, R; Buncic, N; Canal, Ph; Casadei, D; Couet, O; Fine, V; Franco,1, L; Ganis, G; Gheata, A; Gonzalez Maline, D; Goto, M; Iwaszkiewicz, J; Kreshuk, A; Marcos Segura, D; Maunder, R; Moneta, L; Naumann, A; Offermann, E; Onuchin, V; Panacek, S; Rademakers, F; Russo, P; Tadel, M

    2009-01-01

    ROOT is an object-oriented C++ framework conceived in the high-energy physics (HEP) community, designed for storing and analyzing petabytes of data in an efficient way. Any instance of a C++ class can be stored into a ROOT file in a machine-independent compressed binary format. In ROOT the TTree object container is optimized for statistical data analysis over very large data sets by using vertical data storage techniques. These containers can span a large number of files on local disks, the web, or a number of different shared file systems. In order to analyze this data, the user can chose out of a wide set of mathematical and statistical functions, including linear algebra classes, numerical algorithms such as integration and minimization, and various methods for performing regression analysis (fitting). In particular, the RooFit package allows the user to perform complex data modeling and fitting while the RooStats library provides abstractions and implementations for advanced statistical tools. Multivariat...

  11. Quantile regression for the statistical analysis of immunological data with many non-detects.

    Science.gov (United States)

    Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

    2012-07-07

    Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

  12. mapDIA: Preprocessing and statistical analysis of quantitative proteomics data from data independent acquisition mass spectrometry.

    Science.gov (United States)

    Teo, Guoshou; Kim, Sinae; Tsou, Chih-Chiang; Collins, Ben; Gingras, Anne-Claude; Nesvizhskii, Alexey I; Choi, Hyungwon

    2015-11-03

    Data independent acquisition (DIA) mass spectrometry is an emerging technique that offers more complete detection and quantification of peptides and proteins across multiple samples. DIA allows fragment-level quantification, which can be considered as repeated measurements of the abundance of the corresponding peptides and proteins in the downstream statistical analysis. However, few statistical approaches are available for aggregating these complex fragment-level data into peptide- or protein-level statistical summaries. In this work, we describe a software package, mapDIA, for statistical analysis of differential protein expression using DIA fragment-level intensities. The workflow consists of three major steps: intensity normalization, peptide/fragment selection, and statistical analysis. First, mapDIA offers normalization of fragment-level intensities by total intensity sums as well as a novel alternative normalization by local intensity sums in retention time space. Second, mapDIA removes outlier observations and selects peptides/fragments that preserve the major quantitative patterns across all samples for each protein. Last, using the selected fragments and peptides, mapDIA performs model-based statistical significance analysis of protein-level differential expression between specified groups of samples. Using a comprehensive set of simulation datasets, we show that mapDIA detects differentially expressed proteins with accurate control of the false discovery rates. We also describe the analysis procedure in detail using two recently published DIA datasets generated for 14-3-3β dynamic interaction network and prostate cancer glycoproteome. The software was written in C++ language and the source code is available for free through SourceForge website http://sourceforge.net/projects/mapdia/.This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy

    Science.gov (United States)

    Mancini, F.; Ceppi, C.; Ritrovato, G.

    2010-09-01

    This study focuses on landslide susceptibility mapping in the Daunia area (Apulian Apennines, Italy) and achieves this by using a multivariate statistical method and data processing in a Geographical Information System (GIS). The Logistic Regression (hereafter LR) method was chosen to produce a susceptibility map over an area of 130 000 ha where small settlements are historically threatened by landslide phenomena. By means of LR analysis, the tendency to landslide occurrences was, therefore, assessed by relating a landslide inventory (dependent variable) to a series of causal factors (independent variables) which were managed in the GIS, while the statistical analyses were performed by means of the SPSS (Statistical Package for the Social Sciences) software. The LR analysis produced a reliable susceptibility map of the investigated area and the probability level of landslide occurrence was ranked in four classes. The overall performance achieved by the LR analysis was assessed by local comparison between the expected susceptibility and an independent dataset extrapolated from the landslide inventory. Of the samples classified as susceptible to landslide occurrences, 85% correspond to areas where landslide phenomena have actually occurred. In addition, the consideration of the regression coefficients provided by the analysis demonstrated that a major role is played by the "land cover" and "lithology" causal factors in determining the occurrence and distribution of landslide phenomena in the Apulian Apennines.

  14. Clinical medical education in rural and underserved areas and eventual practice outcomes: A systematic review and meta-analysis.

    Science.gov (United States)

    Raymond Guilbault, Ryan William; Vinson, Joseph Alexander

    2017-01-01

    Undergraduate medical students are enrolled in clinical education programs in rural and underserved urban areas to increase the likelihood that they will eventually practice in those areas and train in a primary care specialty to best serve those patient populations. MEDLINE and Cochrane Library online databases were searched to identify articles that provide a detailed description of the exposure and outcome of interest. A qualitative review of articles reporting outcome data without comparison or control groups was completed using the Medical Education Research Study Quality Instrument (MERSQI). A meta-analysis of articles reporting outcome data with comparison or control groups was completed with statistical and graphical summary estimates. Seven hundred and nine articles were retrieved from the initial search and reviewed based on inclusion and exclusion criteria. Of those, ten articles were identified for qualitative analysis and five articles included control groups and thus were included in the quantitative analysis. Results indicated that medical students with clinical training in underserved areas are almost three times as likely to practice in underserved areas than students who do not train in those areas (relative risk [RR] = 2.94; 95% confidence interval [CI]: 2.17, 4.00). Furthermore, medical students training in underserved areas are about four times as likely to practice primary care in underserved areas than students who do not train in those locations (RR = 4.35; 95% CI: 1.56, 12.10). These estimates may help guide medical school administrators and policymakers to expand underserved clinical training programs to help relieve some of the problems associated with access to medical care among underserved populations.

  15. Statistical Analysis of Spectral Properties and Prosodic Parameters of Emotional Speech

    Science.gov (United States)

    Přibil, J.; Přibilová, A.

    2009-01-01

    The paper addresses reflection of microintonation and spectral properties in male and female acted emotional speech. Microintonation component of speech melody is analyzed regarding its spectral and statistical parameters. According to psychological research of emotional speech, different emotions are accompanied by different spectral noise. We control its amount by spectral flatness according to which the high frequency noise is mixed in voiced frames during cepstral speech synthesis. Our experiments are aimed at statistical analysis of cepstral coefficient values and ranges of spectral flatness in three emotions (joy, sadness, anger), and a neutral state for comparison. Calculated histograms of spectral flatness distribution are visually compared and modelled by Gamma probability distribution. Histograms of cepstral coefficient distribution are evaluated and compared using skewness and kurtosis. Achieved statistical results show good correlation comparing male and female voices for all emotional states portrayed by several Czech and Slovak professional actors.

  16. Multivariate statistical analysis of wildfires in Portugal

    Science.gov (United States)

    Costa, Ricardo; Caramelo, Liliana; Pereira, Mário

    2013-04-01

    Several studies demonstrate that wildfires in Portugal present high temporal and spatial variability as well as cluster behavior (Pereira et al., 2005, 2011). This study aims to contribute to the characterization of the fire regime in Portugal with the multivariate statistical analysis of the time series of number of fires and area burned in Portugal during the 1980 - 2009 period. The data used in the analysis is an extended version of the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011), provided by the National Forest Authority (Autoridade Florestal Nacional, AFN), the Portuguese Forest Service, which includes information for more than 500,000 fire records. There are many multiple advanced techniques for examining the relationships among multiple time series at the same time (e.g., canonical correlation analysis, principal components analysis, factor analysis, path analysis, multiple analyses of variance, clustering systems). This study compares and discusses the results obtained with these different techniques. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005: "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).

  17. Cognition of and Demand for Education and Teaching in Medical Statistics in China: A Systematic Review and Meta-Analysis

    Science.gov (United States)

    Li, Gaoming; Yi, Dali; Wu, Xiaojiao; Liu, Xiaoyu; Zhang, Yanqi; Liu, Ling; Yi, Dong

    2015-01-01

    Background Although a substantial number of studies focus on the teaching and application of medical statistics in China, few studies comprehensively evaluate the recognition of and demand for medical statistics. In addition, the results of these various studies differ and are insufficiently comprehensive and systematic. Objectives This investigation aimed to evaluate the general cognition of and demand for medical statistics by undergraduates, graduates, and medical staff in China. Methods We performed a comprehensive database search related to the cognition of and demand for medical statistics from January 2007 to July 2014 and conducted a meta-analysis of non-controlled studies with sub-group analysis for undergraduates, graduates, and medical staff. Results There are substantial differences with respect to the cognition of theory in medical statistics among undergraduates (73.5%), graduates (60.7%), and medical staff (39.6%). The demand for theory in medical statistics is high among graduates (94.6%), undergraduates (86.1%), and medical staff (88.3%). Regarding specific statistical methods, the cognition of basic statistical methods is higher than of advanced statistical methods. The demand for certain advanced statistical methods, including (but not limited to) multiple analysis of variance (ANOVA), multiple linear regression, and logistic regression, is higher than that for basic statistical methods. The use rates of the Statistical Package for the Social Sciences (SPSS) software and statistical analysis software (SAS) are only 55% and 15%, respectively. Conclusion The overall statistical competence of undergraduates, graduates, and medical staff is insufficient, and their ability to practically apply their statistical knowledge is limited, which constitutes an unsatisfactory state of affairs for medical statistics education. Because the demand for skills in this area is increasing, the need to reform medical statistics education in China has become urgent

  18. [Methods of statistical analysis in differential diagnostics of the degree of brain glioma anaplasia during preoperative stage].

    Science.gov (United States)

    Glavatskiĭ, A Ia; Guzhovskaia, N V; Lysenko, S N; Kulik, A V

    2005-12-01

    The authors proposed a possible preoperative diagnostics of the degree of supratentorial brain gliom anaplasia using statistical analysis methods. It relies on a complex examination of 934 patients with I-IV degree anaplasias, which had been treated in the Institute of Neurosurgery from 1990 to 2004. The use of statistical analysis methods for differential diagnostics of the degree of brain gliom anaplasia may optimize a diagnostic algorithm, increase reliability of obtained data and in some cases avoid carrying out irrational operative intrusions. Clinically important signs for the use of statistical analysis methods directed to preoperative diagnostics of brain gliom anaplasia have been defined

  19. Statistics without Tears: Complex Statistics with Simple Arithmetic

    Science.gov (United States)

    Smith, Brian

    2011-01-01

    One of the often overlooked aspects of modern statistics is the analysis of time series data. Modern introductory statistics courses tend to rush to probabilistic applications involving risk and confidence. Rarely does the first level course linger on such useful and fascinating topics as time series decomposition, with its practical applications…

  20. 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

  1. [The research protocol VI: How to choose the appropriate statistical test. Inferential statistics].

    Science.gov (United States)

    Flores-Ruiz, Eric; Miranda-Novales, María Guadalupe; Villasís-Keever, Miguel Ángel

    2017-01-01

    The statistical analysis can be divided in two main components: descriptive analysis and inferential analysis. An inference is to elaborate conclusions from the tests performed with the data obtained from a sample of a population. Statistical tests are used in order to establish the probability that a conclusion obtained from a sample is applicable to the population from which it was obtained. However, choosing the appropriate statistical test in general poses a challenge for novice researchers. To choose the statistical test it is necessary to take into account three aspects: the research design, the number of measurements and the scale of measurement of the variables. Statistical tests are divided into two sets, parametric and nonparametric. Parametric tests can only be used if the data show a normal distribution. Choosing the right statistical test will make it easier for readers to understand and apply the results.

  2. The research protocol VI: How to choose the appropriate statistical test. Inferential statistics

    Directory of Open Access Journals (Sweden)

    Eric Flores-Ruiz

    2017-10-01

    Full Text Available The statistical analysis can be divided in two main components: descriptive analysis and inferential analysis. An inference is to elaborate conclusions from the tests performed with the data obtained from a sample of a population. Statistical tests are used in order to establish the probability that a conclusion obtained from a sample is applicable to the population from which it was obtained. However, choosing the appropriate statistical test in general poses a challenge for novice researchers. To choose the statistical test it is necessary to take into account three aspects: the research design, the number of measurements and the scale of measurement of the variables. Statistical tests are divided into two sets, parametric and nonparametric. Parametric tests can only be used if the data show a normal distribution. Choosing the right statistical test will make it easier for readers to understand and apply the results.

  3. Per Object statistical analysis

    DEFF Research Database (Denmark)

    2008-01-01

    of a specific class in turn, and uses as pair of PPO stages to derive the statistics and then assign them to the objects' Object Variables. It may be that this could all be done in some other, simply way, but several other ways that were tried did not succeed. The procedure ouptut has been tested against...

  4. Bias due to two-stage residual-outcome regression analysis in genetic association studies.

    Science.gov (United States)

    Demissie, Serkalem; Cupples, L Adrienne

    2011-11-01

    Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

  5. Did Medicare Part D Affect National Trends in Health Outcomes or Hospitalizations? A Time-Series Analysis.

    Science.gov (United States)

    Briesacher, Becky A; Madden, Jeanne M; Zhang, Fang; Fouayzi, Hassan; Ross-Degnan, Dennis; Gurwitz, Jerry H; Soumerai, Stephen B

    2015-06-16

    Medicare Part D increased economic access to medications, but its effect on population-level health outcomes and use of other medical services remains unclear. To examine changes in health outcomes and medical services in the Medicare population after implementation of Part D. Population-level longitudinal time-series analysis with generalized linear models. Community. Nationally representative sample of Medicare beneficiaries (n = 56,293 [unweighted and unique]) from 2000 to 2010. Changes in self-reported health status, limitations in activities of daily living (ADLs) (ADLs and instrumental ADLs), emergency department visits and hospital admissions (prevalence, counts, and spending), and mortality. Medicare claims data were used for confirmatory analyses. Five years after Part D implementation, no clinically or statistically significant reductions in the prevalence of fair or poor health status or limitations in ADLs or instrumental ADLs, relative to historical trends, were detected. Compared with trends before Part D, no changes in emergency department visits, hospital admissions or days, inpatient costs, or mortality after Part D were seen. Confirmatory analyses were consistent. Only total population-level outcomes were studied. Self-reported measures may lack sensitivity. Five years after implementation, and contrary to previous reports, no evidence was found of Part D's effect on a range of population-level health indicators among Medicare enrollees. Further, there was no clear evidence of gains in medical care efficiencies.

  6. Statistical analysis of installed wind capacity in the United States

    International Nuclear Information System (INIS)

    Staid, Andrea; Guikema, Seth D.

    2013-01-01

    There is a large disparity in the amount of wind power capacity installed in each of the states in the U.S. It is often thought that the different policies of individual state governments are the main reason for these differences, but this may not necessarily be the case. The aim of this paper is to use statistical methods to study the factors that have the most influence on the amount of installed wind capacity in each state. From this analysis, we were able to use these variables to accurately predict the installed wind capacity and to gain insight into the driving factors for wind power development and the reasons behind the differences among states. Using our best model, we find that the most important variables for explaining the amount of wind capacity have to do with the physical and geographic characteristics of the state as opposed to policies in place that favor renewable energy. - Highlights: • We conduct a statistical analysis of factors influencing wind capacity in the U.S. • We find that state policies do not strongly influence the differences among states. • Driving factors are wind resources, cropland area, and available percentage of land

  7. Statistical Learning in Specific Language Impairment and Autism Spectrum Disorder: A Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Rita Obeid

    2016-08-01

    Full Text Available Impairments in statistical learning might be a common deficit among individuals with Specific Language Impairment (SLI and Autism Spectrum Disorder (ASD. Using meta-analysis, we examined statistical learning in SLI (14 studies, 15 comparisons and ASD (13 studies, 20 comparisons to evaluate this hypothesis. Effect sizes were examined as a function of diagnosis across multiple statistical learning tasks (Serial Reaction Time, Contextual Cueing, Artificial Grammar Learning, Speech Stream, Observational Learning, Probabilistic Classification. Individuals with SLI showed deficits in statistical learning relative to age-matched controls g = .47, 95% CI [.28, .66], p < .001. In contrast, statistical learning was intact in individuals with ASD relative to controls, g = –.13, 95% CI [–.34, .08], p = .22. Effect sizes did not vary as a function of task modality or participant age. Our findings inform debates about overlapping social-communicative difficulties in children with SLI and ASD by suggesting distinct underlying mechanisms. In line with the procedural deficit hypothesis (Ullman & Pierpont, 2005, impaired statistical learning may account for phonological and syntactic difficulties associated with SLI. In contrast, impaired statistical learning fails to account for the social-pragmatic difficulties associated with ASD.

  8. Statistical analysis of non-homogeneous Poisson processes. Statistical processing of a particle multidetector

    International Nuclear Information System (INIS)

    Lacombe, J.P.

    1985-12-01

    Statistic study of Poisson non-homogeneous and spatial processes is the first part of this thesis. A Neyman-Pearson type test is defined concerning the intensity measurement of these processes. Conditions are given for which consistency of the test is assured, and others giving the asymptotic normality of the test statistics. Then some techniques of statistic processing of Poisson fields and their applications to a particle multidetector study are given. Quality tests of the device are proposed togetherwith signal extraction methods [fr

  9. Neurodevelopmental outcome of infantile spasms: A systematic review and meta-analysis.

    Science.gov (United States)

    Widjaja, Elysa; Go, Cristina; McCoy, Blathnaid; Snead, O Carter

    2015-01-01

    The aims of this systematic review and meta-analysis were to assess (i) estimates of good neurodevelopmental outcome in infantile spasms (IS), (ii) if neurodevelopmental outcome has changed since the publication of the first guideline on medical treatment of IS in 2004 and (iii) effect of lead time to treatment (LTTT). The Medline, Embase, Cochrane, PsycINFO, Web of Science and Scopus databases, and reference lists of retrieved articles were searched. Studies inclusion criteria were: (i) >5 patients with IS, (ii) mean/median follow-up of >6 months, (iii) neurodevelopmental outcome, and (iv) randomized and observational studies. The data extracted included proportion of good neurodevelopmental outcome, year of publication, cryptogenic or symptomatic IS and LTTT. Of the 1436 citations screened, 55 articles were included in final analysis, with a total of 2967 patients. The pooled estimate for good neurodevelopmental outcome was 0.236 (95% CI: 0.193-0.286). There was no difference between the proportions of good neurodevelopmental outcome for the 21 studies published after 2004 [0.264 (95% CI: 0.197-0.344)] compared to the 34 studies published before 2004 [0.220 (95% CI: 0.168-0.283)] (Q value=0.862, p=0.353). The pooled estimate of good neurodevelopmental outcome for cryptogenic IS [0.543 (95% CI: 0.458-0.625)] was higher than symptomatic IS [0.125 (95% CI: 0.09-0.171)] (Q value=69.724, p4weeks for good neurodevelopmental outcome of 8 studies was 1.519 (95% CI: 1.064-2.169). Neurodevelopmental outcome was overall poor in patients with IS and has not changed since the publication of first guideline on IS. Although cryptogenic IS has better prognosis than symptomatic IS, the outcome for cryptogenic IS remained poor. There was heterogeneity in neurodevelopmental outcome ascertainment methods, highlighting the need for a more standardized and comprehensive assessment of cognitive, behavioural, emotional and functional outcomes. Copyright © 2014 Elsevier B.V. All rights

  10. Statistically Derived Subtypes and Associations with Cerebrospinal Fluid and Genetic Biomarkers in Mild Cognitive Impairment: A Latent Profile Analysis.

    Science.gov (United States)

    Eppig, Joel S; Edmonds, Emily C; Campbell, Laura; Sanderson-Cimino, Mark; Delano-Wood, Lisa; Bondi, Mark W

    2017-08-01

    Research demonstrates heterogeneous neuropsychological profiles among individuals with mild cognitive impairment (MCI). However, few studies have included visuoconstructional ability or used latent mixture modeling to statistically identify MCI subtypes. Therefore, we examined whether unique neuropsychological MCI profiles could be ascertained using latent profile analysis (LPA), and subsequently investigated cerebrospinal fluid (CSF) biomarkers, genotype, and longitudinal clinical outcomes between the empirically derived classes. A total of 806 participants diagnosed by means of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI criteria received a comprehensive neuropsychological battery assessing visuoconstructional ability, language, attention/executive function, and episodic memory. Test scores were adjusted for demographic characteristics using standardized regression coefficients based on "robust" normal control performance (n=260). Calculated Z-scores were subsequently used in the LPA, and CSF-derived biomarkers, genotype, and longitudinal clinical outcome were evaluated between the LPA-derived MCI classes. Statistical fit indices suggested a 3-class model was the optimal LPA solution. The three-class LPA consisted of a mixed impairment MCI class (n=106), an amnestic MCI class (n=455), and an LPA-derived normal class (n=245). Additionally, the amnestic and mixed classes were more likely to be apolipoprotein e4+ and have worse Alzheimer's disease CSF biomarkers than LPA-derived normal subjects. Our study supports significant heterogeneity in MCI neuropsychological profiles using LPA and extends prior work (Edmonds et al., 2015) by demonstrating a lower rate of progression in the approximately one-third of ADNI MCI individuals who may represent "false-positive" diagnoses. Our results underscore the importance of using sensitive, actuarial methods for diagnosing MCI, as current diagnostic methods may be over-inclusive. (JINS, 2017, 23, 564-576).

  11. Meaningful mediation analysis : Plausible causal inference and informative communication

    NARCIS (Netherlands)

    Pieters, Rik

    2017-01-01

    Statistical mediation analysis has become the technique of choice in consumer research to make causal inferences about the influence of a treatment on an outcome via one or more mediators. This tutorial aims to strengthen two weak links that impede statistical mediation analysis from reaching its

  12. A cluster-randomised trial of a multifaceted quality improvement intervention in Brazilian intensive care units (Checklist-ICU trial): statistical analysis plan.

    Science.gov (United States)

    Damiani, Lucas P; Cavalcanti, Alexandre B; Moreira, Frederico R; Machado, Flavia; Bozza, Fernando A; Salluh, Jorge I F; Campagnucci, Valquiria P; Normilio-Silva, Karina; Chiattone, Viviane C; Angus, Derek C; Berwanger, Otavio; Chou H Chang, Chung-

    2015-06-01

    The Checklist During Multidisciplinary Visits for Reduction of Mortality in Intensive Care Units (Checklist- ICU) trial is a pragmatic, two-arm, cluster-randomised trial involving 118 intensive care units in Brazil, with the primary objective of determining if a multifaceted qualityimprovement intervention with a daily checklist, definition of daily care goals during multidisciplinary daily rounds and clinician prompts can reduce inhospital mortality. To describe our trial statistical analysis plan (SAP). This is an ongoing trial conducted in two phases. In the preparatory observational phase, we collect three sets of baseline data: ICU characteristics; patient characteristics, processes of care and outcomes; and completed safety attitudes questionnaires (SAQs). In the randomised phase, ICUs are assigned to the experimental or control arms and we collect patient data and repeat the SAQ. Our SAP includes the prespecified model for the primary and secondary outcome analyses, which account for the cluster-randomised design and availability of baseline data. We also detail the multiple mediation models that we will use to assess our secondary hypothesis (that the effect of the intervention on inhospital mortality is mediated not only through care processes targeted by the checklist, but also through changes in safety culture). We describe our approach to sensitivity and subgroup analyses and missing data. We report our SAP before closing our study database and starting analysis. We anticipate that this should prevent analysis bias and enhance the utility of results.

  13. Binomial outcomes in dataset with some clusters of size two: can the dependence of twins be accounted for? A simulation study comparing the reliability of statistical methods based on a dataset of preterm infants.

    Science.gov (United States)

    Sauzet, Odile; Peacock, Janet L

    2017-07-20

    The analysis of perinatal outcomes often involves datasets with some multiple births. These are datasets mostly formed of independent observations and a limited number of clusters of size two (twins) and maybe of size three or more. This non-independence needs to be accounted for in the statistical analysis. Using simulated data based on a dataset of preterm infants we have previously investigated the performance of several approaches to the analysis of continuous outcomes in the presence of some clusters of size two. Mixed models have been developed for binomial outcomes but very little is known about their reliability when only a limited number of small clusters are present. Using simulated data based on a dataset of preterm infants we investigated the performance of several approaches to the analysis of binomial outcomes in the presence of some clusters of size two. Logistic models, several methods of estimation for the logistic random intercept models and generalised estimating equations were compared. The presence of even a small percentage of twins means that a logistic regression model will underestimate all parameters but a logistic random intercept model fails to estimate the correlation between siblings if the percentage of twins is too small and will provide similar estimates to logistic regression. The method which seems to provide the best balance between estimation of the standard error and the parameter for any percentage of twins is the generalised estimating equations. This study has shown that the number of covariates or the level two variance do not necessarily affect the performance of the various methods used to analyse datasets containing twins but when the percentage of small clusters is too small, mixed models cannot capture the dependence between siblings.

  14. Binomial outcomes in dataset with some clusters of size two: can the dependence of twins be accounted for? A simulation study comparing the reliability of statistical methods based on a dataset of preterm infants

    Directory of Open Access Journals (Sweden)

    Odile Sauzet

    2017-07-01

    Full Text Available Abstract Background The analysis of perinatal outcomes often involves datasets with some multiple births. These are datasets mostly formed of independent observations and a limited number of clusters of size two (twins and maybe of size three or more. This non-independence needs to be accounted for in the statistical analysis. Using simulated data based on a dataset of preterm infants we have previously investigated the performance of several approaches to the analysis of continuous outcomes in the presence of some clusters of size two. Mixed models have been developed for binomial outcomes but very little is known about their reliability when only a limited number of small clusters are present. Methods Using simulated data based on a dataset of preterm infants we investigated the performance of several approaches to the analysis of binomial outcomes in the presence of some clusters of size two. Logistic models, several methods of estimation for the logistic random intercept models and generalised estimating equations were compared. Results The presence of even a small percentage of twins means that a logistic regression model will underestimate all parameters but a logistic random intercept model fails to estimate the correlation between siblings if the percentage of twins is too small and will provide similar estimates to logistic regression. The method which seems to provide the best balance between estimation of the standard error and the parameter for any percentage of twins is the generalised estimating equations. Conclusions This study has shown that the number of covariates or the level two variance do not necessarily affect the performance of the various methods used to analyse datasets containing twins but when the percentage of small clusters is too small, mixed models cannot capture the dependence between siblings.

  15. Integrated Data Collection Analysis (IDCA) Program - Statistical Analysis of RDX Standard Data Sets

    Energy Technology Data Exchange (ETDEWEB)

    Sandstrom, Mary M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Brown, Geoffrey W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Preston, Daniel N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Pollard, Colin J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Warner, Kirstin F. [Naval Surface Warfare Center (NSWC), Indian Head, MD (United States). Indian Head Division; Sorensen, Daniel N. [Naval Surface Warfare Center (NSWC), Indian Head, MD (United States). Indian Head Division; Remmers, Daniel L. [Naval Surface Warfare Center (NSWC), Indian Head, MD (United States). Indian Head Division; Phillips, Jason J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shelley, Timothy J. [Air Force Research Lab. (AFRL), Tyndall AFB, FL (United States); Reyes, Jose A. [Applied Research Associates, Tyndall AFB, FL (United States); Hsu, Peter C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Reynolds, John G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-10-30

    The Integrated Data Collection Analysis (IDCA) program is conducting a Proficiency Test for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are statistical analyses of the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of the RDX Type II Class 5 standard. The material was tested as a well-characterized standard several times during the proficiency study to assess differences among participants and the range of results that may arise for well-behaved explosive materials. The analyses show that there are detectable differences among the results from IDCA participants. While these differences are statistically significant, most of them can be disregarded for comparison purposes to assess potential variability when laboratories attempt to measure identical samples using methods assumed to be nominally the same. The results presented in this report include the average sensitivity results for the IDCA participants and the ranges of values obtained. The ranges represent variation about the mean values of the tests of between 26% and 42%. The magnitude of this variation is attributed to differences in operator, method, and environment as well as the use of different instruments that are also of varying age. The results appear to be a good representation of the broader safety testing community based on the range of methods, instruments, and environments included in the IDCA Proficiency Test.

  16. STATISTICS. The reusable holdout: Preserving validity in adaptive data analysis.

    Science.gov (United States)

    Dwork, Cynthia; Feldman, Vitaly; Hardt, Moritz; Pitassi, Toniann; Reingold, Omer; Roth, Aaron

    2015-08-07

    Misapplication of statistical data analysis is a common cause of spurious discoveries in scientific research. Existing approaches to ensuring the validity of inferences drawn from data assume a fixed procedure to be performed, selected before the data are examined. In common practice, however, data analysis is an intrinsically adaptive process, with new analyses generated on the basis of data exploration, as well as the results of previous analyses on the same data. We demonstrate a new approach for addressing the challenges of adaptivity based on insights from privacy-preserving data analysis. As an application, we show how to safely reuse a holdout data set many times to validate the results of adaptively chosen analyses. Copyright © 2015, American Association for the Advancement of Science.

  17. International Conference on Modern Problems of Stochastic Analysis and Statistics

    CERN Document Server

    2017-01-01

    This book brings together the latest findings in the area of stochastic analysis and statistics. The individual chapters cover a wide range of topics from limit theorems, Markov processes, nonparametric methods, acturial science, population dynamics, and many others. The volume is dedicated to Valentin Konakov, head of the International Laboratory of Stochastic Analysis and its Applications on the occasion of his 70th birthday. Contributions were prepared by the participants of the international conference of the international conference “Modern problems of stochastic analysis and statistics”, held at the Higher School of Economics in Moscow from May 29 - June 2, 2016. It offers a valuable reference resource for researchers and graduate students interested in modern stochastics.

  18. Factors influencing medical informatics examination grade--can biorhythm, astrological sign, seasonal aspect, or bad statistics predict outcome?

    Science.gov (United States)

    Petrovecki, Mladen; Rahelić, Dario; Bilić-Zulle, Lidija; Jelec, Vjekoslav

    2003-02-01

    To investigate whether and to what extent various parameters, such as individual characteristics, computer habits, situational factors, and pseudoscientific variables, influence Medical Informatics examination grade, and how inadequate statistical analysis can lead to wrong conclusions. The study included a total of 382 second-year undergraduate students at the Rijeka University School of Medicine in the period from 1996/97 to 2000/01 academic year. After passing the Medical Informatics exam, students filled out an anonymous questionnaire about their attitude toward learning medical informatics. They were asked to grade the course organization and curriculum content, and provide their date of birth; sex; study year; high school grades; Medical Informatics examination grade, type, and term; and describe their computer habits. From these data, we determined their zodiac signs and biorhythm. Data were compared by the use of t-test, one-way ANOVA with Tukey's honest significance difference test, and randomized complete block design ANOVA. Out of 21 variables analyzed, only 10 correlated with the average grade. Students taking Medical Informatics examination in the 1998/99 academic year earned lower average grade than any other generation. Significantly higher Medical Informatics exam grade was earned by students who finished a grammar high school; owned and regularly used a computer, Internet, and e-mail (pzodiac sign, zodiac sign quality, or biorhythm cycles, except when intentionally inadequate statistics was used for data analysis. Medical Informatics examination grades correlated with general learning capacity and computer habits of students, but showed no relation to other investigated parameters, such as examination term or pseudoscientific parameters. Inadequate statistical analysis can always confirm false conclusions.

  19. The outcome of the seminal fluid parameters collected via coitus interruptus versus masturbation.

    Science.gov (United States)

    Bahyah, M Kamarul; Murad, Z Ahmad; Ghazali, I; Roszaman, R; Noraziana, A W; Mokhtar, A; Omar, M H

    2010-03-01

    A one year study was carried out to determine the outcome of the seminal fluid parameters collected via masturbation and coitus interruptus in 151 patients who were undergoing intrauterine insemination (IUI) and patients who came for seminal analysis. There were no statistically significant differences in terms of volume, concentration, progressive motility and normal morphology from specimens collected via coitus interruptus compared to specimens collected via masturbation. Pregnancy outcomes were also comparable.

  20. Predictive Factors in OCT Analysis for Visual Outcome in Exudative AMD

    Directory of Open Access Journals (Sweden)

    Maria-Andreea Gamulescu

    2012-01-01

    Full Text Available Background. Reliable predictive factors for therapy outcome may enable treating physicians to counsel their patients more efficiently concerning probability of improvement or time point of discontinuation of a certain therapy. Methods. This is a retrospective analysis of 87 patients with exudative age-related macular degeneration who received three monthly intravitreal ranibizumab injections. Visual acuity before initiation of intravitreal therapy and 4–6 weeks after last intravitreal injection was compared and related to the preoperative visualisation of continuity of the outer retinal layers as assessed by OCT: external limiting membrane (ELM, inner photoreceptor segments (IPS, junction between inner and outer segments (IS/OS, and outer photoreceptor segments (OPS. Results. Visual acuity increased in 40 of 87 (46.0% patients, it remained stable in 25 (28.7%, and 22 (25.3% patients had decreased visual acuity four to six weeks after triple intravitreal ranibizumab injections. No statistically significant predictive value could be demonstrated for grade of continuity of outer retinal layers concerning visual acuity development. Conclusions. In our series of AMD patients, grade of continuity of outer retinal layers was not a significant predictive value for visual acuity development after triple ranibizumab injections.