Resampling-based methods in single and multiple testing for equality of covariance/correlation matrices.

PubMed

Yang, Yang; DeGruttola, Victor

2012-06-22

Traditional resampling-based tests for homogeneity in covariance matrices across multiple groups resample residuals, that is, data centered by group means. These residuals do not share the same second moments when the null hypothesis is false, which makes them difficult to use in the setting of multiple testing. An alternative approach is to resample standardized residuals, data centered by group sample means and standardized by group sample covariance matrices. This approach, however, has been observed to inflate type I error when sample size is small or data are generated from heavy-tailed distributions. We propose to improve this approach by using robust estimation for the first and second moments. We discuss two statistics: the Bartlett statistic and a statistic based on eigen-decomposition of sample covariance matrices. Both statistics can be expressed in terms of standardized errors under the null hypothesis. These methods are extended to test homogeneity in correlation matrices. Using simulation studies, we demonstrate that the robust resampling approach provides comparable or superior performance, relative to traditional approaches, for single testing and reasonable performance for multiple testing. The proposed methods are applied to data collected in an HIV vaccine trial to investigate possible determinants, including vaccine status, vaccine-induced immune response level and viral genotype, of unusual correlation pattern between HIV viral load and CD4 count in newly infected patients.

Robust Lee local statistic filter for removal of mixed multiplicative and impulse noise

NASA Astrophysics Data System (ADS)

Ponomarenko, Nikolay N.; Lukin, Vladimir V.; Egiazarian, Karen O.; Astola, Jaakko T.

2004-05-01

A robust version of Lee local statistic filter able to effectively suppress the mixed multiplicative and impulse noise in images is proposed. The performance of the proposed modification is studied for a set of test images, several values of multiplicative noise variance, Gaussian and Rayleigh probability density functions of speckle, and different characteris-tics of impulse noise. The advantages of the designed filter in comparison to the conventional Lee local statistic filter and some other filters able to cope with mixed multiplicative+impulse noise are demonstrated.

Design and analysis of multiple diseases genome-wide association studies without controls.

PubMed

Chen, Zhongxue; Huang, Hanwen; Ng, Hon Keung Tony

2012-11-15

In genome-wide association studies (GWAS), multiple diseases with shared controls is one of the case-control study designs. If data obtained from these studies are appropriately analyzed, this design can have several advantages such as improving statistical power in detecting associations and reducing the time and cost in the data collection process. In this paper, we propose a study design for GWAS which involves multiple diseases but without controls. We also propose corresponding statistical data analysis strategy for GWAS with multiple diseases but no controls. Through a simulation study, we show that the statistical association test with the proposed study design is more powerful than the test with single disease sharing common controls, and it has comparable power to the overall test based on the whole dataset including the controls. We also apply the proposed method to a real GWAS dataset to illustrate the methodologies and the advantages of the proposed design. Some possible limitations of this study design and testing method and their solutions are also discussed. Our findings indicate that the proposed study design and statistical analysis strategy could be more efficient than the usual case-control GWAS as well as those with shared controls. Copyright © 2012 Elsevier B.V. All rights reserved.

Statistical Tutorial | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data.  ST is designed as a follow up to Statistical Analysis of Research Data (SARD) held in April 2018.  The tutorial will apply the general principles of statistical analysis of research data including descriptive statistics, z- and t-tests of means and mean differences, simple and multiple linear regression, ANOVA tests, and Chi-Squared distribution.

Derivation and Applicability of Asymptotic Results for Multiple Subtests Person-Fit Statistics

PubMed Central

Albers, Casper J.; Meijer, Rob R.; Tendeiro, Jorge N.

2016-01-01

In high-stakes testing, it is important to check the validity of individual test scores. Although a test may, in general, result in valid test scores for most test takers, for some test takers, test scores may not provide a good description of a test taker’s proficiency level. Person-fit statistics have been proposed to check the validity of individual test scores. In this study, the theoretical asymptotic sampling distribution of two person-fit statistics that can be used for tests that consist of multiple subtests is first discussed. Second, simulation study was conducted to investigate the applicability of this asymptotic theory for tests of finite length, in which the correlation between subtests and number of items in the subtests was varied. The authors showed that these distributions provide reasonable approximations, even for tests consisting of subtests of only 10 items each. These results have practical value because researchers do not have to rely on extensive simulation studies to simulate sampling distributions. PMID:29881053

Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175

Does the IQ God Exist?

ERIC Educational Resources Information Center

Siegel, Linda S.

1995-01-01

Responds to "The Bell Curve" by arguing that IQ is merely a statistical fiction, an artificial construct not corresponding to any real entity. Discusses the "seductive statistical trap of factor analysis" as it relates to IQ tests, multiple intelligences, content and bias of IQ tests, lack of validity of IQ tests for individual…

Using the Coefficient of Determination "R"[superscript 2] to Test the Significance of Multiple Linear Regression

ERIC Educational Resources Information Center

Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.

2013-01-01

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics.

PubMed

Kwak, Il-Youp; Pan, Wei

2017-01-01

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods. The methods are implemented in R package aSPU, freely and publicly available at: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Advances in Testing the Statistical Significance of Mediation Effects

ERIC Educational Resources Information Center

Mallinckrodt, Brent; Abraham, W. Todd; Wei, Meifen; Russell, Daniel W.

2006-01-01

P. A. Frazier, A. P. Tix, and K. E. Barron (2004) highlighted a normal theory method popularized by R. M. Baron and D. A. Kenny (1986) for testing the statistical significance of indirect effects (i.e., mediator variables) in multiple regression contexts. However, simulation studies suggest that this method lacks statistical power relative to some…

Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution.

PubMed

Gangnon, Ronald E

2012-03-01

The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, whereas rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. © 2011, The International Biometric Society.

Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution

PubMed Central

Gangnon, Ronald E.

2011-01-01

Summary The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, while rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. PMID:21762118

A Spreadsheet Tool for Learning the Multiple Regression F-Test, T-Tests, and Multicollinearity

ERIC Educational Resources Information Center

Martin, David

2008-01-01

This note presents a spreadsheet tool that allows teachers the opportunity to guide students towards answering on their own questions related to the multiple regression F-test, the t-tests, and multicollinearity. The note demonstrates approaches for using the spreadsheet that might be appropriate for three different levels of statistics classes,…

Rapid and Accurate Multiple Testing Correction and Power Estimation for Millions of Correlated Markers

PubMed Central

Han, Buhm; Kang, Hyun Min; Eskin, Eleazar

2009-01-01

With the development of high-throughput sequencing and genotyping technologies, the number of markers collected in genetic association studies is growing rapidly, increasing the importance of methods for correcting for multiple hypothesis testing. The permutation test is widely considered the gold standard for accurate multiple testing correction, but it is often computationally impractical for these large datasets. Recently, several studies proposed efficient alternative approaches to the permutation test based on the multivariate normal distribution (MVN). However, they cannot accurately correct for multiple testing in genome-wide association studies for two reasons. First, these methods require partitioning of the genome into many disjoint blocks and ignore all correlations between markers from different blocks. Second, the true null distribution of the test statistic often fails to follow the asymptotic distribution at the tails of the distribution. We propose an accurate and efficient method for multiple testing correction in genome-wide association studies—SLIDE. Our method accounts for all correlation within a sliding window and corrects for the departure of the true null distribution of the statistic from the asymptotic distribution. In simulations using the Wellcome Trust Case Control Consortium data, the error rate of SLIDE's corrected p-values is more than 20 times smaller than the error rate of the previous MVN-based methods' corrected p-values, while SLIDE is orders of magnitude faster than the permutation test and other competing methods. We also extend the MVN framework to the problem of estimating the statistical power of an association study with correlated markers and propose an efficient and accurate power estimation method SLIP. SLIP and SLIDE are available at http://slide.cs.ucla.edu. PMID:19381255

Utilizing the Zero-One Linear Programming Constraints to Draw Multiple Sets of Matched Samples from a Non-Treatment Population as Control Groups for the Quasi-Experimental Design

ERIC Educational Resources Information Center

Li, Yuan H.; Yang, Yu N.; Tompkins, Leroy J.; Modarresi, Shahpar

2005-01-01

The statistical technique, "Zero-One Linear Programming," that has successfully been used to create multiple tests with similar characteristics (e.g., item difficulties, test information and test specifications) in the area of educational measurement, was deemed to be a suitable method for creating multiple sets of matched samples to be…

Improvements in cognition, quality of life, and physical performance with clinical Pilates in multiple sclerosis: a randomized controlled trial

PubMed Central

Küçük, Fadime; Kara, Bilge; Poyraz, Esra Çoşkuner; İdiman, Egemen

2016-01-01

[Purpose] The aim of this study was to determine the effects of clinical Pilates in multiple sclerosis patients. [Subjects and Methods] Twenty multiple sclerosis patients were enrolled in this study. The participants were divided into two groups as the clinical Pilates and control groups. Cognition (Multiple Sclerosis Functional Composite), balance (Berg Balance Scale), physical performance (timed performance tests, Timed up and go test), tiredness (Modified Fatigue Impact scale), depression (Beck Depression Inventory), and quality of life (Multiple Sclerosis International Quality of Life Questionnaire) were measured before and after treatment in all participants. [Results] There were statistically significant differences in balance, timed performance, tiredness and Multiple Sclerosis Functional Composite tests between before and after treatment in the clinical Pilates group. We also found significant differences in timed performance tests, the Timed up and go test and the Multiple Sclerosis Functional Composite between before and after treatment in the control group. According to the difference analyses, there were significant differences in Multiple Sclerosis Functional Composite and Multiple Sclerosis International Quality of Life Questionnaire scores between the two groups in favor of the clinical Pilates group. There were statistically significant clinical differences in favor of the clinical Pilates group in comparison of measurements between the groups. Clinical Pilates improved cognitive functions and quality of life compared with traditional exercise. [Conclusion] In Multiple Sclerosis treatment, clinical Pilates should be used as a holistic approach by physical therapists. PMID:27134355

Improvements in cognition, quality of life, and physical performance with clinical Pilates in multiple sclerosis: a randomized controlled trial.

PubMed

Küçük, Fadime; Kara, Bilge; Poyraz, Esra Çoşkuner; İdiman, Egemen

2016-03-01

[Purpose] The aim of this study was to determine the effects of clinical Pilates in multiple sclerosis patients. [Subjects and Methods] Twenty multiple sclerosis patients were enrolled in this study. The participants were divided into two groups as the clinical Pilates and control groups. Cognition (Multiple Sclerosis Functional Composite), balance (Berg Balance Scale), physical performance (timed performance tests, Timed up and go test), tiredness (Modified Fatigue Impact scale), depression (Beck Depression Inventory), and quality of life (Multiple Sclerosis International Quality of Life Questionnaire) were measured before and after treatment in all participants. [Results] There were statistically significant differences in balance, timed performance, tiredness and Multiple Sclerosis Functional Composite tests between before and after treatment in the clinical Pilates group. We also found significant differences in timed performance tests, the Timed up and go test and the Multiple Sclerosis Functional Composite between before and after treatment in the control group. According to the difference analyses, there were significant differences in Multiple Sclerosis Functional Composite and Multiple Sclerosis International Quality of Life Questionnaire scores between the two groups in favor of the clinical Pilates group. There were statistically significant clinical differences in favor of the clinical Pilates group in comparison of measurements between the groups. Clinical Pilates improved cognitive functions and quality of life compared with traditional exercise. [Conclusion] In Multiple Sclerosis treatment, clinical Pilates should be used as a holistic approach by physical therapists.

A simple test of association for contingency tables with multiple column responses.

PubMed

Decady, Y J; Thomas, D R

2000-09-01

Loughin and Scherer (1998, Biometrics 54, 630-637) investigated tests of association in two-way tables when one of the categorical variables allows for multiple-category responses from individual respondents. Standard chi-squared tests are invalid in this case, and they developed a bootstrap test procedure that provides good control of test levels under the null hypothesis. This procedure and some others that have been proposed are computationally involved and are based on techniques that are relatively unfamiliar to many practitioners. In this paper, the methods introduced by Rao and Scott (1981, Journal of the American Statistical Association 76, 221-230) for analyzing complex survey data are used to develop a simple test based on a corrected chi-squared statistic.

Post-Graduate Student Performance in "Supervised In-Class" vs. "Unsupervised Online" Multiple Choice Tests: Implications for Cheating and Test Security

ERIC Educational Resources Information Center

Ladyshewsky, Richard K.

2015-01-01

This research explores differences in multiple choice test (MCT) scores in a cohort of post-graduate students enrolled in a management and leadership course. A total of 250 students completed the MCT in either a supervised in-class paper and pencil test or an unsupervised online test. The only statistically significant difference between the nine…

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables.

PubMed

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C; Downing, James R; Lamba, Jatinder

2009-08-15

In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org.

Characterizing the Joint Effect of Diverse Test-Statistic Correlation Structures and Effect Size on False Discovery Rates in a Multiple-Comparison Study of Many Outcome Measures

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Ploutz-Snyder, Robert; Fiedler, James

2011-01-01

In their 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report the results of a simulation assessing the robustness of their adaptive step-down procedure (GBS) for controlling the false discovery rate (FDR) when normally distributed test statistics are serially correlated. In this study we extend the investigation to the case of multiple comparisons involving correlated non-central t-statistics, in particular when several treatments or time periods are being compared to a control in a repeated-measures design with many dependent outcome measures. In addition, we consider several dependence structures other than serial correlation and illustrate how the FDR depends on the interaction between effect size and the type of correlation structure as indexed by Foerstner s distance metric from an identity. The relationship between the correlation matrix R of the original dependent variables and R, the correlation matrix of associated t-statistics is also studied. In general R depends not only on R, but also on sample size and the signed effect sizes for the multiple comparisons.

Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers

ERIC Educational Resources Information Center

Chen, Chi-hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

2017-01-01

Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories…

An Investigation of Dental Luting Cement Solubility as a Function of the Marginal Gap.

DTIC Science & Technology

1988-05-01

way ANOVA for the Phase 1 Diffusion Study revealed that there were statistically significant differences between the test groups. A Duncan’s Multiple...cement. The 25, 50, and 75 micron groups demonstrated no statistically significant differences in the amount of remaining luting cement. ( p< 0.05) A...one-way ANOVA was also performed on Phase 2 Dynamic Study. This test revealed that there were statistically significant differences among the test

Multiple-Choice versus Constructed-Response Tests in the Assessment of Mathematics Computation Skills.

ERIC Educational Resources Information Center

Gadalla, Tahany M.

The equivalence of multiple-choice (MC) and constructed response (discrete) (CR-D) response formats as applied to mathematics computation at grade levels two to six was tested. The difference between total scores from the two response formats was tested for statistical significance, and the factor structure of items in both response formats was…

Constructing a Criterion Reference Test to Measure the Research and Statistical Competencies of Graduate Students at the Jordanian Governmental Universities

ERIC Educational Resources Information Center

Al-Habashneh, Maher Hussein; Najjar, Nabil Juma

2017-01-01

This study aimed at constructing a criterion-reference test to measure the research and statistical competencies of graduate students at the Jordanian governmental universities, the test has to be in its first form of (50) multiple choice items, then the test was introduced to (5) arbitrators with competence in measurement and evaluation to…

Robust Detection of Examinees with Aberrant Answer Changes

ERIC Educational Resources Information Center

Belov, Dmitry I.

2015-01-01

The statistical analysis of answer changes (ACs) has uncovered multiple testing irregularities on large-scale assessments and is now routinely performed at testing organizations. However, AC data has an uncertainty caused by technological or human factors. Therefore, existing statistics (e.g., number of wrong-to-right ACs) used to detect examinees…

Monte Carlo based statistical power analysis for mediation models: methods and software.

PubMed

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.

Statistical inference for Hardy-Weinberg proportions in the presence of missing genotype information.

PubMed

Graffelman, Jan; Sánchez, Milagros; Cook, Samantha; Moreno, Victor

2013-01-01

In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables

PubMed Central

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R.; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C.; Downing, James R.; Lamba, Jatinder

2009-01-01

Motivation: In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Results: Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Availability: Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org. Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19528086

Inhibition of Orthopaedic Implant Infections by Immunomodulatory Effects of Host Defense Peptides

DTIC Science & Technology

2014-12-01

significance was determined by t- tests or by one-way analysis of variance (ANOVA) followed by Bonferroni post hoc tests in experiments with multiple...groups. Non- parametric Mann-Whitney tests , Kruskal-Wallis ANOVA followed by Newman-Kuels post hoc tests , or van Elteren’s two-way tests were applied to...in D, and black symbols in A), statistical analysis was by one-way ANOVA followed by Bonferroni versus control, post hoc tests . Otherwise, statistical

Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.

PubMed

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei

2016-02-01

Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.

Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions

PubMed Central

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei

2015-01-01

Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979

Models for Scoring Missing Responses to Multiple-Choice Items. Program Statistics Research Technical Report No. 94-1.

ERIC Educational Resources Information Center

Longford, Nicholas T.

This study is a critical evaluation of the roles for coding and scoring of missing responses to multiple-choice items in educational tests. The focus is on tests in which the test-takers have little or no motivation; in such tests omitting and not reaching (as classified by the currently adopted operational rules) is quite frequent. Data from the…

Best (but oft-forgotten) practices: the multiple problems of multiplicity-whether and how to correct for many statistical tests.

PubMed

Streiner, David L

2015-10-01

Testing many null hypotheses in a single study results in an increased probability of detecting a significant finding just by chance (the problem of multiplicity). Debates have raged over many years with regard to whether to correct for multiplicity and, if so, how it should be done. This article first discusses how multiple tests lead to an inflation of the α level, then explores the following different contexts in which multiplicity arises: testing for baseline differences in various types of studies, having >1 outcome variable, conducting statistical tests that produce >1 P value, taking multiple "peeks" at the data, and unplanned, post hoc analyses (i.e., "data dredging," "fishing expeditions," or "P-hacking"). It then discusses some of the methods that have been proposed for correcting for multiplicity, including single-step procedures (e.g., Bonferroni); multistep procedures, such as those of Holm, Hochberg, and Šidák; false discovery rate control; and resampling approaches. Note that these various approaches describe different aspects and are not necessarily mutually exclusive. For example, resampling methods could be used to control the false discovery rate or the family-wise error rate (as defined later in this article). However, the use of one of these approaches presupposes that we should correct for multiplicity, which is not universally accepted, and the article presents the arguments for and against such "correction." The final section brings together these threads and presents suggestions with regard to when it makes sense to apply the corrections and how to do so. © 2015 American Society for Nutrition.

The optimal power puzzle: scrutiny of the monotone likelihood ratio assumption in multiple testing.

PubMed

Cao, Hongyuan; Sun, Wenguang; Kosorok, Michael R

2013-01-01

In single hypothesis testing, power is a non-decreasing function of type I error rate; hence it is desirable to test at the nominal level exactly to achieve optimal power. The puzzle lies in the fact that for multiple testing, under the false discovery rate paradigm, such a monotonic relationship may not hold. In particular, exact false discovery rate control may lead to a less powerful testing procedure if a test statistic fails to fulfil the monotone likelihood ratio condition. In this article, we identify different scenarios wherein the condition fails and give caveats for conducting multiple testing in practical settings.

An Illustration to Assist in Comparing and Remembering Several Multiplicity Adjustment Methods

ERIC Educational Resources Information Center

Hasler, Mario

2017-01-01

There are many well-known or new methods to adjust statistical tests for multiplicity. This article provides an illustration helping lecturers or consultants to remember the differences of three important multiplicity adjustment methods and to explain them to non-statisticians.

Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

ERIC Educational Resources Information Center

Li, Spencer D.

2011-01-01

Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

A Multidimensional Scaling Approach to Dimensionality Assessment for Measurement Instruments Modeled by Multidimensional Item Response Theory

ERIC Educational Resources Information Center

Toro, Maritsa

2011-01-01

The statistical assessment of dimensionality provides evidence of the underlying constructs measured by a survey or test instrument. This study focuses on educational measurement, specifically tests comprised of items described as multidimensional. That is, items that require examinee proficiency in multiple content areas and/or multiple cognitive…

Congruence analysis of geodetic networks - hypothesis tests versus model selection by information criteria

NASA Astrophysics Data System (ADS)

Lehmann, Rüdiger; Lösler, Michael

2017-12-01

Geodetic deformation analysis can be interpreted as a model selection problem. The null model indicates that no deformation has occurred. It is opposed to a number of alternative models, which stipulate different deformation patterns. A common way to select the right model is the usage of a statistical hypothesis test. However, since we have to test a series of deformation patterns, this must be a multiple test. As an alternative solution for the test problem, we propose the p-value approach. Another approach arises from information theory. Here, the Akaike information criterion (AIC) or some alternative is used to select an appropriate model for a given set of observations. Both approaches are discussed and applied to two test scenarios: A synthetic levelling network and the Delft test data set. It is demonstrated that they work but behave differently, sometimes even producing different results. Hypothesis tests are well-established in geodesy, but may suffer from an unfavourable choice of the decision error rates. The multiple test also suffers from statistical dependencies between the test statistics, which are neglected. Both problems are overcome by applying information criterions like AIC.

Single-variant and multi-variant trend tests for genetic association with next-generation sequencing that are robust to sequencing error.

PubMed

Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Alejandro Q; Musolf, Anthony; Matise, Tara C; Finch, Stephen J; Gordon, Derek

2012-01-01

As with any new technology, next-generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to those data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single-variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p value, no matter how many loci. Copyright © 2013 S. Karger AG, Basel.

Single variant and multi-variant trend tests for genetic association with next generation sequencing that are robust to sequencing error

PubMed Central

Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Andrew; Musolf, Anthony; Matise, Tara C.; Finch, Stephen J.; Gordon, Derek

2013-01-01

As with any new technology, next generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model, based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to that data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p-value, no matter how many loci. PMID:23594495

An Algorithm to Improve Test Answer Copying Detection Using the Omega Statistic

ERIC Educational Resources Information Center

Maeda, Hotaka; Zhang, Bo

2017-01-01

The omega (?) statistic is reputed to be one of the best indices for detecting answer copying on multiple choice tests, but its performance relies on the accurate estimation of copier ability, which is challenging because responses from the copiers may have been contaminated. We propose an algorithm that aims to identify and delete the suspected…

Statistical significance of combinatorial regulations

PubMed Central

Terada, Aika; Okada-Hatakeyama, Mariko; Tsuda, Koji; Sese, Jun

2013-01-01

More than three transcription factors often work together to enable cells to respond to various signals. The detection of combinatorial regulation by multiple transcription factors, however, is not only computationally nontrivial but also extremely unlikely because of multiple testing correction. The exponential growth in the number of tests forces us to set a strict limit on the maximum arity. Here, we propose an efficient branch-and-bound algorithm called the “limitless arity multiple-testing procedure” (LAMP) to count the exact number of testable combinations and calibrate the Bonferroni factor to the smallest possible value. LAMP lists significant combinations without any limit, whereas the family-wise error rate is rigorously controlled under the threshold. In the human breast cancer transcriptome, LAMP discovered statistically significant combinations of as many as eight binding motifs. This method may contribute to uncover pathways regulated in a coordinated fashion and find hidden associations in heterogeneous data. PMID:23882073

Introductory Statistics in the Garden

ERIC Educational Resources Information Center

Wagaman, John C.

2017-01-01

This article describes four semesters of introductory statistics courses that incorporate service learning and gardening into the curriculum with applications of the binomial distribution, least squares regression and hypothesis testing. The activities span multiple semesters and are iterative in nature.

Exact goodness-of-fit tests for Markov chains.

PubMed

Besag, J; Mondal, D

2013-06-01

Goodness-of-fit tests are useful in assessing whether a statistical model is consistent with available data. However, the usual χ² asymptotics often fail, either because of the paucity of the data or because a nonstandard test statistic is of interest. In this article, we describe exact goodness-of-fit tests for first- and higher order Markov chains, with particular attention given to time-reversible ones. The tests are obtained by conditioning on the sufficient statistics for the transition probabilities and are implemented by simple Monte Carlo sampling or by Markov chain Monte Carlo. They apply both to single and to multiple sequences and allow a free choice of test statistic. Three examples are given. The first concerns multiple sequences of dry and wet January days for the years 1948-1983 at Snoqualmie Falls, Washington State, and suggests that standard analysis may be misleading. The second one is for a four-state DNA sequence and lends support to the original conclusion that a second-order Markov chain provides an adequate fit to the data. The last one is six-state atomistic data arising in molecular conformational dynamics simulation of solvated alanine dipeptide and points to strong evidence against a first-order reversible Markov chain at 6 picosecond time steps. © 2013, The International Biometric Society.

Use of the Global Test Statistic as a Performance Measurement in a Reananlysis of Environmental Health Data

PubMed Central

Dymova, Natalya; Hanumara, R. Choudary; Gagnon, Ronald N.

2009-01-01

Performance measurement is increasingly viewed as an essential component of environmental and public health protection programs. In characterizing program performance over time, investigators often observe multiple changes resulting from a single intervention across a range of categories. Although a variety of statistical tools allow evaluation of data one variable at a time, the global test statistic is uniquely suited for analyses of categories or groups of interrelated variables. Here we demonstrate how the global test statistic can be applied to environmental and occupational health data for the purpose of making overall statements on the success of targeted intervention strategies. PMID:19696393

Use of the global test statistic as a performance measurement in a reanalysis of environmental health data.

PubMed

Dymova, Natalya; Hanumara, R Choudary; Enander, Richard T; Gagnon, Ronald N

2009-10-01

Performance measurement is increasingly viewed as an essential component of environmental and public health protection programs. In characterizing program performance over time, investigators often observe multiple changes resulting from a single intervention across a range of categories. Although a variety of statistical tools allow evaluation of data one variable at a time, the global test statistic is uniquely suited for analyses of categories or groups of interrelated variables. Here we demonstrate how the global test statistic can be applied to environmental and occupational health data for the purpose of making overall statements on the success of targeted intervention strategies.

Multidimensional Rasch Analysis of a Psychological Test with Multiple Subtests: A Statistical Solution for the Bandwidth-Fidelity Dilemma

ERIC Educational Resources Information Center

Cheng, Ying-Yao; Wang, Wen-Chung; Ho, Yi-Hui

2009-01-01

Educational and psychological tests are often composed of multiple short subtests, each measuring a distinct latent trait. Unfortunately, short subtests suffer from low measurement precision, which makes the bandwidth-fidelity dilemma inevitable. In this study, the authors demonstrate how a multidimensional Rasch analysis can be employed to take…

Robustness of statistical tests for multiplicative terms in the additive main effects and multiplicative interaction model for cultivar trials.

PubMed

Piepho, H P

1995-03-01

The additive main effects multiplicative interaction model is frequently used in the analysis of multilocation trials. In the analysis of such data it is of interest to decide how many of the multiplicative interaction terms are significant. Several tests for this task are available, all of which assume that errors are normally distributed with a common variance. This paper investigates the robustness of several tests (Gollob, F GH1, FGH2, FR)to departures from these assumptions. It is concluded that, because of its better robustness, the F Rtest is preferable. If the other tests are to be used, preliminary tests for the validity of assumptions should be performed.

"TNOs are Cool": A survey of the trans-Neptunian region. XIII. Statistical analysis of multiple trans-Neptunian objects observed with Herschel Space Observatory

NASA Astrophysics Data System (ADS)

Kovalenko, I. D.; Doressoundiram, A.; Lellouch, E.; Vilenius, E.; Müller, T.; Stansberry, J.

2017-11-01

Context. Gravitationally bound multiple systems provide an opportunity to estimate the mean bulk density of the objects, whereas this characteristic is not available for single objects. Being a primitive population of the outer solar system, binary and multiple trans-Neptunian objects (TNOs) provide unique information about bulk density and internal structure, improving our understanding of their formation and evolution. Aims: The goal of this work is to analyse parameters of multiple trans-Neptunian systems, observed with Herschel and Spitzer space telescopes. Particularly, statistical analysis is done for radiometric size and geometric albedo, obtained from photometric observations, and for estimated bulk density. Methods: We use Monte Carlo simulation to estimate the real size distribution of TNOs. For this purpose, we expand the dataset of diameters by adopting the Minor Planet Center database list with available values of the absolute magnitude therein, and the albedo distribution derived from Herschel radiometric measurements. We use the 2-sample Anderson-Darling non-parametric statistical method for testing whether two samples of diameters, for binary and single TNOs, come from the same distribution. Additionally, we use the Spearman's coefficient as a measure of rank correlations between parameters. Uncertainties of estimated parameters together with lack of data are taken into account. Conclusions about correlations between parameters are based on statistical hypothesis testing. Results: We have found that the difference in size distributions of multiple and single TNOs is biased by small objects. The test on correlations between parameters shows that the effective diameter of binary TNOs strongly correlates with heliocentric orbital inclination and with magnitude difference between components of binary system. The correlation between diameter and magnitude difference implies that small and large binaries are formed by different mechanisms. Furthermore, the statistical test indicates, although not significant with the sample size, that a moderately strong correlation exists between diameter and bulk density. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

Common Scientific and Statistical Errors in Obesity Research

PubMed Central

George, Brandon J.; Beasley, T. Mark; Brown, Andrew W.; Dawson, John; Dimova, Rositsa; Divers, Jasmin; Goldsby, TaShauna U.; Heo, Moonseong; Kaiser, Kathryn A.; Keith, Scott; Kim, Mimi Y.; Li, Peng; Mehta, Tapan; Oakes, J. Michael; Skinner, Asheley; Stuart, Elizabeth; Allison, David B.

2015-01-01

We identify 10 common errors and problems in the statistical analysis, design, interpretation, and reporting of obesity research and discuss how they can be avoided. The 10 topics are: 1) misinterpretation of statistical significance, 2) inappropriate testing against baseline values, 3) excessive and undisclosed multiple testing and “p-value hacking,” 4) mishandling of clustering in cluster randomized trials, 5) misconceptions about nonparametric tests, 6) mishandling of missing data, 7) miscalculation of effect sizes, 8) ignoring regression to the mean, 9) ignoring confirmation bias, and 10) insufficient statistical reporting. We hope that discussion of these errors can improve the quality of obesity research by helping researchers to implement proper statistical practice and to know when to seek the help of a statistician. PMID:27028280

Robustness of Multiple Objective Decision Analysis Preference Functions

DTIC Science & Technology

2002-06-01

p p′ : The probability of some event. ,i ip q : The probability of event . i Π : An aggregation of proportional data used in calculating a test ...statistical tests of the significance of the term and also is conducted in a multivariate framework rather than the ROSA univariate approach. A...residual error is ˆ−e = y y (45) The coefficient provides a ready indicator of the contribution for the associated variable and statistical tests

Multiple hypotheses testing based on ordered p values--a historical survey with applications to medical research.

PubMed

Hommel, Gerhard; Bretz, Frank; Maurer, Willi

2011-07-01

Global tests and multiple test procedures are often based on ordered p values. Such procedures are available for arbitrary dependence structures as well as for specific dependence assumptions of the test statistics. Most of these procedures have been considered as global tests. Multiple test procedures can be obtained by applying the closure principle in order to control the familywise error rate, or by using the false discovery rate as a criterion for type I error rate control. We provide an overview and present examples showing the importance of these procedures in medical research. Finally, we discuss modifications when different weights for the hypotheses of interest are chosen.

Criterion-Referenced Test Items for Welding.

ERIC Educational Resources Information Center

Davis, Diane, Ed.

This test item bank on welding contains test questions based upon competencies found in the Missouri Welding Competency Profile. Some test items are keyed for multiple competencies. These criterion-referenced test items are designed to work with the Vocational Instructional Management System. Questions have been statistically sampled and validated…

BrightStat.com: free statistics online.

PubMed

Stricker, Daniel

2008-10-01

Powerful software for statistical analysis is expensive. Here I present BrightStat, a statistical software running on the Internet which is free of charge. BrightStat's goals, its main capabilities and functionalities are outlined. Three different sample runs, a Friedman test, a chi-square test, and a step-wise multiple regression are presented. The results obtained by BrightStat are compared with results computed by SPSS, one of the global leader in providing statistical software, and VassarStats, a collection of scripts for data analysis running on the Internet. Elementary statistics is an inherent part of academic education and BrightStat is an alternative to commercial products.

Identification of differentially expressed genes and false discovery rate in microarray studies.

PubMed

Gusnanto, Arief; Calza, Stefano; Pawitan, Yudi

2007-04-01

To highlight the development in microarray data analysis for the identification of differentially expressed genes, particularly via control of false discovery rate. The emergence of high-throughput technology such as microarrays raises two fundamental statistical issues: multiplicity and sensitivity. We focus on the biological problem of identifying differentially expressed genes. First, multiplicity arises due to testing tens of thousands of hypotheses, rendering the standard P value meaningless. Second, known optimal single-test procedures such as the t-test perform poorly in the context of highly multiple tests. The standard approach of dealing with multiplicity is too conservative in the microarray context. The false discovery rate concept is fast becoming the key statistical assessment tool replacing the P value. We review the false discovery rate approach and argue that it is more sensible for microarray data. We also discuss some methods to take into account additional information from the microarrays to improve the false discovery rate. There is growing consensus on how to analyse microarray data using the false discovery rate framework in place of the classical P value. Further research is needed on the preprocessing of the raw data, such as the normalization step and filtering, and on finding the most sensitive test procedure.

gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels.

PubMed

Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J

2017-05-01

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong

2017-01-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

PubMed

Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong

2017-02-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.

Identifying Variations in Hydraulic Conductivity on the East River at Crested Butte, CO

NASA Astrophysics Data System (ADS)

Ulmer, K. N.; Malenda, H. F.; Singha, K.

2016-12-01

Slug tests are a widely used method to measure saturated hydraulic conductivity, or how easily water flows through an aquifer, by perturbing the piezometric surface and measuring the time the local groundwater table takes to re-equilibrate. Saturated hydraulic conductivity is crucial to calculating the speed and direction of groundwater movement. Therefore, it is important to document data variance from in situ slug tests. This study addresses two potential sources of data variability: different users and different types of slug used. To test for user variability, two individuals slugged the same six wells with water multiple times at a stream meander on the East River near Crested Butte, CO. To test for variations in type of slug test, multiple water and metal slug tests were performed at a single well in the same meander. The distributions of hydraulic conductivities of each test were then tested for variance using both the Kruskal-Wallis test and the Brown-Forsythe test. When comparing the hydraulic conductivity distributions gathered by the two individuals, we found that they were statistically similar. However, we found that the two types of slug tests produced hydraulic conductivity distributions for the same well that are statistically dissimilar. In conclusion, multiple people should be able to conduct slug tests without creating any considerable variations in the resulting hydraulic conductivity values, but only a single type of slug should be used for those tests.

Statistical significance test for transition matrices of atmospheric Markov chains

NASA Technical Reports Server (NTRS)

Vautard, Robert; Mo, Kingtse C.; Ghil, Michael

1990-01-01

Low-frequency variability of large-scale atmospheric dynamics can be represented schematically by a Markov chain of multiple flow regimes. This Markov chain contains useful information for the long-range forecaster, provided that the statistical significance of the associated transition matrix can be reliably tested. Monte Carlo simulation yields a very reliable significance test for the elements of this matrix. The results of this test agree with previously used empirical formulae when each cluster of maps identified as a distinct flow regime is sufficiently large and when they all contain a comparable number of maps. Monte Carlo simulation provides a more reliable way to test the statistical significance of transitions to and from small clusters. It can determine the most likely transitions, as well as the most unlikely ones, with a prescribed level of statistical significance.

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

An omnibus test for family-based association studies with multiple SNPs and multiple phenotypes.

PubMed

Lasky-Su, Jessica; Murphy, Amy; McQueen, Matthew B; Weiss, Scott; Lange, Christoph

2010-06-01

We propose an omnibus family-based association test (MFBAT) that can be applied to multiple markers and multiple phenotypes and that has only one degree of freedom. The proposed test statistic extends current FBAT methodology to incorporate multiple markers as well as multiple phenotypes. Using simulation studies, power estimates for the proposed methodology are compared with the standard methodologies. On the basis of these simulations, we find that MFBAT substantially outperforms other methods, including haplotypic approaches and doing multiple tests with single single-nucleotide polymorphisms (SNPs) and single phenotypes. The practical relevance of the approach is illustrated by an application to asthma in which SNP/phenotype combinations are identified and reach overall significance that would not have been identified using other approaches. This methodology is directly applicable to cases in which there are multiple SNPs, such as candidate gene studies, cases in which there are multiple phenotypes, such as expression data, and cases in which there are multiple phenotypes and genotypes, such as genome-wide association studies that incorporate expression profiles as phenotypes. This program is available in the PBAT analysis package.

Detection of Undocumented Changepoints Using Multiple Test Statistics and Composite Reference Series.

NASA Astrophysics Data System (ADS)

Menne, Matthew J.; Williams, Claude N., Jr.

2005-10-01

An evaluation of three hypothesis test statistics that are commonly used in the detection of undocumented changepoints is described. The goal of the evaluation was to determine whether the use of multiple tests could improve undocumented, artificial changepoint detection skill in climate series. The use of successive hypothesis testing is compared to optimal approaches, both of which are designed for situations in which multiple undocumented changepoints may be present. In addition, the importance of the form of the composite climate reference series is evaluated, particularly with regard to the impact of undocumented changepoints in the various component series that are used to calculate the composite.In a comparison of single test changepoint detection skill, the composite reference series formulation is shown to be less important than the choice of the hypothesis test statistic, provided that the composite is calculated from the serially complete and homogeneous component series. However, each of the evaluated composite series is not equally susceptible to the presence of changepoints in its components, which may be erroneously attributed to the target series. Moreover, a reference formulation that is based on the averaging of the first-difference component series is susceptible to random walks when the composition of the component series changes through time (e.g., values are missing), and its use is, therefore, not recommended. When more than one test is required to reject the null hypothesis of no changepoint, the number of detected changepoints is reduced proportionately less than the number of false alarms in a wide variety of Monte Carlo simulations. Consequently, a consensus of hypothesis tests appears to improve undocumented changepoint detection skill, especially when reference series homogeneity is violated. A consensus of successive hypothesis tests using a semihierarchic splitting algorithm also compares favorably to optimal solutions, even when changepoints are not hierarchic.

Visualization and statistical comparisons of microbial communities using R packages on Phylochip data.

PubMed

Holmes, Susan; Alekseyenko, Alexander; Timme, Alden; Nelson, Tyrrell; Pasricha, Pankaj Jay; Spormann, Alfred

2011-01-01

This article explains the statistical and computational methodology used to analyze species abundances collected using the LNBL Phylochip in a study of Irritable Bowel Syndrome (IBS) in rats. Some tools already available for the analysis of ordinary microarray data are useful in this type of statistical analysis. For instance in correcting for multiple testing we use Family Wise Error rate control and step-down tests (available in the multtest package). Once the most significant species are chosen we use the hypergeometric tests familiar for testing GO categories to test specific phyla and families. We provide examples of normalization, multivariate projections, batch effect detection and integration of phylogenetic covariation, as well as tree equalization and robustification methods.

Expected p-values in light of an ROC curve analysis applied to optimal multiple testing procedures.

PubMed

Vexler, Albert; Yu, Jihnhee; Zhao, Yang; Hutson, Alan D; Gurevich, Gregory

2017-01-01

Many statistical studies report p-values for inferential purposes. In several scenarios, the stochastic aspect of p-values is neglected, which may contribute to drawing wrong conclusions in real data experiments. The stochastic nature of p-values makes their use to examine the performance of given testing procedures or associations between investigated factors to be difficult. We turn our focus on the modern statistical literature to address the expected p-value (EPV) as a measure of the performance of decision-making rules. During the course of our study, we prove that the EPV can be considered in the context of receiver operating characteristic (ROC) curve analysis, a well-established biostatistical methodology. The ROC-based framework provides a new and efficient methodology for investigating and constructing statistical decision-making procedures, including: (1) evaluation and visualization of properties of the testing mechanisms, considering, e.g. partial EPVs; (2) developing optimal tests via the minimization of EPVs; (3) creation of novel methods for optimally combining multiple test statistics. We demonstrate that the proposed EPV-based approach allows us to maximize the integrated power of testing algorithms with respect to various significance levels. In an application, we use the proposed method to construct the optimal test and analyze a myocardial infarction disease dataset. We outline the usefulness of the "EPV/ROC" technique for evaluating different decision-making procedures, their constructions and properties with an eye towards practical applications.

Evaluating Neurotoxicity of a Mixture of Five OP Pesticides Using a Composite Score

EPA Science Inventory

The evaluation of the cumulative effects of neurotoxic pesticides often involves the analysis of both neurochemical and behavioral endpoints. Multiple statistical tests on many endpoints can greatly inflate Type I error rates. Multiple comparison adjustments are often overly con...

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

PubMed Central

Broadaway, K. Alaine; Cutler, David J.; Duncan, Richard; Moore, Jacob L.; Ware, Erin B.; Jhun, Min A.; Bielak, Lawrence F.; Zhao, Wei; Smith, Jennifer A.; Peyser, Patricia A.; Kardia, Sharon L.R.; Ghosh, Debashis; Epstein, Michael P.

2016-01-01

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy. PMID:26942286

A Binomial Test of Group Differences with Correlated Outcome Measures

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Levin, Joel R.; Ferron, John M.

2011-01-01

Building on previous arguments for why educational researchers should not provide effect-size estimates in the face of statistically nonsignificant outcomes (Robinson & Levin, 1997), Onwuegbuzie and Levin (2005) proposed a 3-step statistical approach for assessing group differences when multiple outcome measures are individually analyzed…

Using Multilevel Modeling in Language Assessment Research: A Conceptual Introduction

ERIC Educational Resources Information Center

Barkaoui, Khaled

2013-01-01

This article critiques traditional single-level statistical approaches (e.g., multiple regression analysis) to examining relationships between language test scores and variables in the assessment setting. It highlights the conceptual, methodological, and statistical problems associated with these techniques in dealing with multilevel or nested…

A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series

USGS Publications Warehouse

Cohn, T.A.; England, J.F.; Berenbrock, C.E.; Mason, R.R.; Stedinger, J.R.; Lamontagne, J.R.

2013-01-01

he Grubbs-Beck test is recommended by the federal guidelines for detection of low outliers in flood flow frequency computation in the United States. This paper presents a generalization of the Grubbs-Beck test for normal data (similar to the Rosner (1983) test; see also Spencer and McCuen (1996)) that can provide a consistent standard for identifying multiple potentially influential low flows. In cases where low outliers have been identified, they can be represented as “less-than” values, and a frequency distribution can be developed using censored-data statistical techniques, such as the Expected Moments Algorithm. This approach can improve the fit of the right-hand tail of a frequency distribution and provide protection from lack-of-fit due to unimportant but potentially influential low flows (PILFs) in a flood series, thus making the flood frequency analysis procedure more robust.

A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series

NASA Astrophysics Data System (ADS)

Cohn, T. A.; England, J. F.; Berenbrock, C. E.; Mason, R. R.; Stedinger, J. R.; Lamontagne, J. R.

2013-08-01

The Grubbs-Beck test is recommended by the federal guidelines for detection of low outliers in flood flow frequency computation in the United States. This paper presents a generalization of the Grubbs-Beck test for normal data (similar to the Rosner (1983) test; see also Spencer and McCuen (1996)) that can provide a consistent standard for identifying multiple potentially influential low flows. In cases where low outliers have been identified, they can be represented as "less-than" values, and a frequency distribution can be developed using censored-data statistical techniques, such as the Expected Moments Algorithm. This approach can improve the fit of the right-hand tail of a frequency distribution and provide protection from lack-of-fit due to unimportant but potentially influential low flows (PILFs) in a flood series, thus making the flood frequency analysis procedure more robust.

Multiple Hypothesis Testing for Experimental Gingivitis Based on Wilcoxon Signed Rank Statistics

PubMed Central

Preisser, John S.; Sen, Pranab K.; Offenbacher, Steven

2011-01-01

Dental research often involves repeated multivariate outcomes on a small number of subjects for which there is interest in identifying outcomes that exhibit change in their levels over time as well as to characterize the nature of that change. In particular, periodontal research often involves the analysis of molecular mediators of inflammation for which multivariate parametric methods are highly sensitive to outliers and deviations from Gaussian assumptions. In such settings, nonparametric methods may be favored over parametric ones. Additionally, there is a need for statistical methods that control an overall error rate for multiple hypothesis testing. We review univariate and multivariate nonparametric hypothesis tests and apply them to longitudinal data to assess changes over time in 31 biomarkers measured from the gingival crevicular fluid in 22 subjects whereby gingivitis was induced by temporarily withholding tooth brushing. To identify biomarkers that can be induced to change, multivariate Wilcoxon signed rank tests for a set of four summary measures based upon area under the curve are applied for each biomarker and compared to their univariate counterparts. Multiple hypothesis testing methods with choice of control of the false discovery rate or strong control of the family-wise error rate are examined. PMID:21984957

Multiple-Line Inference of Selection on Quantitative Traits

PubMed Central

Riedel, Nico; Khatri, Bhavin S.; Lässig, Michael; Berg, Johannes

2015-01-01

Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population genetics test for selection acting on a quantitative trait that is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inferences. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test can distinguish between different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signature of lineage-specific selection not seen in two-line tests. PMID:26139839

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

PubMed

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.

Statistical testing and power analysis for brain-wide association study.

PubMed

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.

Multivariate two-part statistics for analysis of correlated mass spectrometry data from multiple biological specimens.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Weiss, Robert H; Kelly, Karen; Kim, Kyoungmi

2017-01-01

High through-put mass spectrometry (MS) is now being used to profile small molecular compounds across multiple biological sample types from the same subjects with the goal of leveraging information across biospecimens. Multivariate statistical methods that combine information from all biospecimens could be more powerful than the usual univariate analyses. However, missing values are common in MS data and imputation can impact between-biospecimen correlation and multivariate analysis results. We propose two multivariate two-part statistics that accommodate missing values and combine data from all biospecimens to identify differentially regulated compounds. Statistical significance is determined using a multivariate permutation null distribution. Relative to univariate tests, the multivariate procedures detected more significant compounds in three biological datasets. In a simulation study, we showed that multi-biospecimen testing procedures were more powerful than single-biospecimen methods when compounds are differentially regulated in multiple biospecimens but univariate methods can be more powerful if compounds are differentially regulated in only one biospecimen. We provide R functions to implement and illustrate our method as supplementary information CONTACT: sltaylor@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Multivariate objective response detectors (MORD): statistical tools for multichannel EEG analysis during rhythmic stimulation.

PubMed

Felix, Leonardo Bonato; Miranda de Sá, Antonio Mauricio Ferreira Leite; Infantosi, Antonio Fernando Catelli; Yehia, Hani Camille

2007-03-01

The presence of cerebral evoked responses can be tested by using objective response detectors. They are statistical tests that provide a threshold above which responses can be assumed to have occurred. The detection power depends on the signal-to-noise ratio (SNR) of the response and the amount of data available. However, the correlation within the background noise could also affect the power of such detectors. For a fixed SNR, the detection can only be improved at the expense of using a longer stretch of signal. This can constitute a limitation, for instance, in monitored surgeries. Alternatively, multivariate objective response detection (MORD) could be used. This work applies two MORD techniques (multiple coherence and multiple component synchrony measure) to EEG data collected during intermittent photic stimulation. They were evaluated throughout Monte Carlo simulations, which also allowed verifying that correlation in the background reduces the detection rate. Considering the N EEG derivations as close as possible to the primary visual cortex, if N = 4, 6 or 8, multiple coherence leads to a statistically significant higher detection rate in comparison with multiple component synchrony measure. With the former, the best performance was obtained with six signals (O1, O2, T5, T6, P3 and P4).

Adaptive graph-based multiple testing procedures

PubMed Central

Klinglmueller, Florian; Posch, Martin; Koenig, Franz

2016-01-01

Multiple testing procedures defined by directed, weighted graphs have recently been proposed as an intuitive visual tool for constructing multiple testing strategies that reflect the often complex contextual relations between hypotheses in clinical trials. Many well-known sequentially rejective tests, such as (parallel) gatekeeping tests or hierarchical testing procedures are special cases of the graph based tests. We generalize these graph-based multiple testing procedures to adaptive trial designs with an interim analysis. These designs permit mid-trial design modifications based on unblinded interim data as well as external information, while providing strong family wise error rate control. To maintain the familywise error rate, it is not required to prespecify the adaption rule in detail. Because the adaptive test does not require knowledge of the multivariate distribution of test statistics, it is applicable in a wide range of scenarios including trials with multiple treatment comparisons, endpoints or subgroups, or combinations thereof. Examples of adaptations are dropping of treatment arms, selection of subpopulations, and sample size reassessment. If, in the interim analysis, it is decided to continue the trial as planned, the adaptive test reduces to the originally planned multiple testing procedure. Only if adaptations are actually implemented, an adjusted test needs to be applied. The procedure is illustrated with a case study and its operating characteristics are investigated by simulations. PMID:25319733

The chi-square test of independence.

PubMed

McHugh, Mary L

2013-01-01

The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not require equality of variances among the study groups or homoscedasticity in the data. It permits evaluation of both dichotomous independent variables, and of multiple group studies. Unlike many other non-parametric and some parametric statistics, the calculations needed to compute the Chi-square provide considerable information about how each of the groups performed in the study. This richness of detail allows the researcher to understand the results and thus to derive more detailed information from this statistic than from many others. The Chi-square is a significance statistic, and should be followed with a strength statistic. The Cramer's V is the most common strength test used to test the data when a significant Chi-square result has been obtained. Advantages of the Chi-square include its robustness with respect to distribution of the data, its ease of computation, the detailed information that can be derived from the test, its use in studies for which parametric assumptions cannot be met, and its flexibility in handling data from both two group and multiple group studies. Limitations include its sample size requirements, difficulty of interpretation when there are large numbers of categories (20 or more) in the independent or dependent variables, and tendency of the Cramer's V to produce relative low correlation measures, even for highly significant results.

MAFsnp: A Multi-Sample Accurate and Flexible SNP Caller Using Next-Generation Sequencing Data

PubMed Central

Hu, Jiyuan; Li, Tengfei; Xiu, Zidi; Zhang, Hong

2015-01-01

Most existing statistical methods developed for calling single nucleotide polymorphisms (SNPs) using next-generation sequencing (NGS) data are based on Bayesian frameworks, and there does not exist any SNP caller that produces p-values for calling SNPs in a frequentist framework. To fill in this gap, we develop a new method MAFsnp, a Multiple-sample based Accurate and Flexible algorithm for calling SNPs with NGS data. MAFsnp is based on an estimated likelihood ratio test (eLRT) statistic. In practical situation, the involved parameter is very close to the boundary of the parametric space, so the standard large sample property is not suitable to evaluate the finite-sample distribution of the eLRT statistic. Observing that the distribution of the test statistic is a mixture of zero and a continuous part, we propose to model the test statistic with a novel two-parameter mixture distribution. Once the parameters in the mixture distribution are estimated, p-values can be easily calculated for detecting SNPs, and the multiple-testing corrected p-values can be used to control false discovery rate (FDR) at any pre-specified level. With simulated data, MAFsnp is shown to have much better control of FDR than the existing SNP callers. Through the application to two real datasets, MAFsnp is also shown to outperform the existing SNP callers in terms of calling accuracy. An R package “MAFsnp” implementing the new SNP caller is freely available at http://homepage.fudan.edu.cn/zhangh/softwares/. PMID:26309201

Evaluating Equating Results in the Non-Equivalent Groups with Anchor Test Design Using Equipercentile and Equity Criteria

ERIC Educational Resources Information Center

Duong, Minh Quang

2011-01-01

Testing programs often use multiple test forms of the same test to control item exposure and to ensure test security. Although test forms are constructed to be as similar as possible, they often differ. Test equating techniques are those statistical methods used to adjust scores obtained on different test forms of the same test so that they are…

A SAS macro for testing differences among three or more independent groups using Kruskal-Wallis and Nemenyi tests.

PubMed

Liu, Yuewei; Chen, Weihong

2012-02-01

As a nonparametric method, the Kruskal-Wallis test is widely used to compare three or more independent groups when an ordinal or interval level of data is available, especially when the assumptions of analysis of variance (ANOVA) are not met. If the Kruskal-Wallis statistic is statistically significant, Nemenyi test is an alternative method for further pairwise multiple comparisons to locate the source of significance. Unfortunately, most popular statistical packages do not integrate the Nemenyi test, which is not easy to be calculated by hand. We described the theory and applications of the Kruskal-Wallis and Nemenyi tests, and presented a flexible SAS macro to implement the two tests. The SAS macro was demonstrated by two examples from our cohort study in occupational epidemiology. It provides a useful tool for SAS users to test the differences among three or more independent groups using a nonparametric method.

Testing jumps via false discovery rate control.

PubMed

Yen, Yu-Min

2013-01-01

Many recently developed nonparametric jump tests can be viewed as multiple hypothesis testing problems. For such multiple hypothesis tests, it is well known that controlling type I error often makes a large proportion of erroneous rejections, and such situation becomes even worse when the jump occurrence is a rare event. To obtain more reliable results, we aim to control the false discovery rate (FDR), an efficient compound error measure for erroneous rejections in multiple testing problems. We perform the test via the Barndorff-Nielsen and Shephard (BNS) test statistic, and control the FDR with the Benjamini and Hochberg (BH) procedure. We provide asymptotic results for the FDR control. From simulations, we examine relevant theoretical results and demonstrate the advantages of controlling the FDR. The hybrid approach is then applied to empirical analysis on two benchmark stock indices with high frequency data.

Black Male Labor Force Participation.

ERIC Educational Resources Information Center

Baer, Roger K.

This study attempts to test (via multiple regression analysis) hypothesized relationships between designated independent variables and age specific incidences of labor force participation for black male subpopulations in 54 Standard Metropolitan Statistical Areas. Leading independent variables tested include net migration, earnings, unemployment,…

Unscaled Bayes factors for multiple hypothesis testing in microarray experiments.

PubMed

Bertolino, Francesco; Cabras, Stefano; Castellanos, Maria Eugenia; Racugno, Walter

2015-12-01

Multiple hypothesis testing collects a series of techniques usually based on p-values as a summary of the available evidence from many statistical tests. In hypothesis testing, under a Bayesian perspective, the evidence for a specified hypothesis against an alternative, conditionally on data, is given by the Bayes factor. In this study, we approach multiple hypothesis testing based on both Bayes factors and p-values, regarding multiple hypothesis testing as a multiple model selection problem. To obtain the Bayes factors we assume default priors that are typically improper. In this case, the Bayes factor is usually undetermined due to the ratio of prior pseudo-constants. We show that ignoring prior pseudo-constants leads to unscaled Bayes factor which do not invalidate the inferential procedure in multiple hypothesis testing, because they are used within a comparative scheme. In fact, using partial information from the p-values, we are able to approximate the sampling null distribution of the unscaled Bayes factor and use it within Efron's multiple testing procedure. The simulation study suggests that under normal sampling model and even with small sample sizes, our approach provides false positive and false negative proportions that are less than other common multiple hypothesis testing approaches based only on p-values. The proposed procedure is illustrated in two simulation studies, and the advantages of its use are showed in the analysis of two microarray experiments. © The Author(s) 2011.

Addressing astronomy misconceptions and achieving national science standards utilizing aspects of multiple intelligences theory in the classroom and the planetarium

NASA Astrophysics Data System (ADS)

Sarrazine, Angela Renee

The purpose of this study was to incorporate multiple intelligences techniques in both a classroom and planetarium setting to create a significant increase in student learning about the moon and lunar phases. Utilizing a free-response questionnaire and a 25 item multiple choice pre-test/post-test design, this study identified middle school students' misconceptions and measured increases in student learning about the moon and lunar phases. The study spanned two semesters and contained six treatment groups which consisted of both single and multiple interventions. One group only attended the planetarium program. Two groups attended one of two classes a week prior to the planetarium program, and two groups attended one of two classes a week after the planetarium program. The most rigorous treatment group attended a class both a week before and after the planetarium program. Utilizing Rasch analysis techniques and parametric statistical tests, all six groups exhibited statistically significant gains in knowledge at the 0.05 level. There were no significant differences between students who attended only a planetarium program versus a single classroom program. Also, subjects who attended either a pre-planetarium class or a post- planetarium class did not show a statistically significant gain over the planetarium only situation. Equivalent effects on student learning were exhibited by the pre-planetarium class groups and post-planetarium class groups. Therefore, it was determined that the placement of the second intervention does not have a significant impact on student learning. However, a decrease in learning was observed with the addition of a third intervention. Further instruction and testing appeared to hinder student learning. This is perhaps an effect of subject fatigue.

An Investigation of the Impact of Guessing on Coefficient α and Reliability

PubMed Central

2014-01-01

Guessing is known to influence the test reliability of multiple-choice tests. Although there are many studies that have examined the impact of guessing, they used rather restrictive assumptions (e.g., parallel test assumptions, homogeneous inter-item correlations, homogeneous item difficulty, and homogeneous guessing levels across items) to evaluate the relation between guessing and test reliability. Based on the item response theory (IRT) framework, this study investigated the extent of the impact of guessing on reliability under more realistic conditions where item difficulty, item discrimination, and guessing levels actually vary across items with three different test lengths (TL). By accommodating multiple item characteristics simultaneously, this study also focused on examining interaction effects between guessing and other variables entered in the simulation to be more realistic. The simulation of the more realistic conditions and calculations of reliability and classical test theory (CTT) item statistics were facilitated by expressing CTT item statistics, coefficient α, and reliability in terms of IRT model parameters. In addition to the general negative impact of guessing on reliability, results showed interaction effects between TL and guessing and between guessing and test difficulty.

Primer of statistics in dental research: part I.

PubMed

Shintani, Ayumi

2014-01-01

Statistics play essential roles in evidence-based dentistry (EBD) practice and research. It ranges widely from formulating scientific questions, designing studies, collecting and analyzing data to interpreting, reporting, and presenting study findings. Mastering statistical concepts appears to be an unreachable goal among many dental researchers in part due to statistical authorities' limitations of explaining statistical principles to health researchers without elaborating complex mathematical concepts. This series of 2 articles aim to introduce dental researchers to 9 essential topics in statistics to conduct EBD with intuitive examples. The part I of the series includes the first 5 topics (1) statistical graph, (2) how to deal with outliers, (3) p-value and confidence interval, (4) testing equivalence, and (5) multiplicity adjustment. Part II will follow to cover the remaining topics including (6) selecting the proper statistical tests, (7) repeated measures analysis, (8) epidemiological consideration for causal association, and (9) analysis of agreement. Copyright © 2014. Published by Elsevier Ltd.

Detecting anomalies in CMB maps: a new method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neelakanta, Jayanth T., E-mail: jayanthtn@gmail.com

2015-10-01

Ever since WMAP announced its first results, different analyses have shown that there is weak evidence for several large-scale anomalies in the CMB data. While the evidence for each anomaly appears to be weak, the fact that there are multiple seemingly unrelated anomalies makes it difficult to account for them via a single statistical fluke. So, one is led to considering a combination of these anomalies. But, if we ''hand-pick'' the anomalies (test statistics) to consider, we are making an a posteriori choice. In this article, we propose two statistics that do not suffer from this problem. The statistics aremore » linear and quadratic combinations of the a{sub ℓ m}'s with random co-efficients, and they test the null hypothesis that the a{sub ℓ m}'s are independent, normally-distributed, zero-mean random variables with an m-independent variance. The motivation for considering multiple modes is this: because most physical models that lead to large-scale anomalies result in coupling multiple ℓ and m modes, the ''coherence'' of this coupling should get enhanced if a combination of different modes is considered. In this sense, the statistics are thus much more generic than those that have been hitherto considered in literature. Using fiducial data, we demonstrate that the method works and discuss how it can be used with actual CMB data to make quite general statements about the incompatibility of the data with the null hypothesis.« less

Content and Method in the Teaching of Marketing Research Revisited

ERIC Educational Resources Information Center

Wilson, Holt; Neeley, Concha; Niedzwiecki, Kelly

2009-01-01

This paper presents the findings from a survey of marketing research faculty. The study finds SPSS is the most used statistical software, that cross tabulation, single, independent, and dependent t-tests, and ANOVA are among the most important statistical tools according to respondents. Bivariate and multiple regression are also considered…

The Development and Demonstration of Multiple Regression Models for Operant Conditioning Questions.

ERIC Educational Resources Information Center

Fanning, Fred; Newman, Isadore

Based on the assumption that inferential statistics can make the operant conditioner more sensitive to possible significant relationships, regressions models were developed to test the statistical significance between slopes and Y intercepts of the experimental and control group subjects. These results were then compared to the traditional operant…

Multiple choice answers: what to do when you have too many questions.

PubMed

Jupiter, Daniel C

2015-01-01

Carrying out too many statistical tests in a single study throws results into doubt, for reasons statistical and ethical. I discuss why this is the case and briefly mention ways to handle the problem. Copyright © 2015 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Roles of frequency, attitudes, and multiple intelligence modality surrounding Electricity Content-Based Reader's Theatre

NASA Astrophysics Data System (ADS)

Hosier, Julie Winchester

Integration of subjects is something elementary teachers must do to insure required objectives are covered. Science-based Reader's Theatre is one way to weave reading into science. This study examined the roles of frequency, attitudes, and Multiple Intelligence modalities surrounding Electricity Content-Based Reader's Theatre. This study used quasi-experimental, repeated measures ANOVA with time as a factor design. A convenience sample of two fifth-grade classrooms participated in the study for eighteen weeks. Five Electricity Achievement Tests were given throughout the study to assess students' growth. A Student Reader's Theatre Attitudinal Survey revealed students' attitudes before and after Electricity Content-Based Reader's Theatre treatment. The Multiple Intelligence Inventory for Kids (Faris, 2007) examined whether Multiple Intelligence modality played a role in achievement on Electricity Test 4, the post-treatment test. Analysis using repeated measures ANOVA and an independent t-test found that students in the experimental group, which practiced its student-created Electricity Content-Based Reader's Theatre skits ten times versus two times for the for control group, did significantly better on Electricity Achievement Test 4, t(76) = 3.018, p = 0.003. Dependent t-tests did not find statistically significant differences between students' attitudes about Electricity Content-Based Reader's Theatre before and after treatment. A Kruskal-Wallis test found no statistically significant difference between the various Multiple Intelligence modalities score mean ranks (x2 = 5.57, df = 2, alpha = .062). Qualitative data do, however, indicate students had strong positive feelings about Electricity Content-Based Reader's Theatre after treatment. Students indicated it to be motivating, confidence-building, and a fun way to learn about science; however, they disliked writing their own scripts. Examining the frequency, attitudes, and Multiple Intelligence modalities lead to the conclusion that the role of frequency had the greatest impact on the success of Electricity Content-Based Reader's Theatre. The participating teachers, students, and research found integrating science and reading through Electricity Content-Based Reader's Theatre beneficial.

DEIVA: a web application for interactive visual analysis of differential gene expression profiles.

PubMed

Harshbarger, Jayson; Kratz, Anton; Carninci, Piero

2017-01-07

Differential gene expression (DGE) analysis is a technique to identify statistically significant differences in RNA abundance for genes or arbitrary features between different biological states. The result of a DGE test is typically further analyzed using statistical software, spreadsheets or custom ad hoc algorithms. We identified a need for a web-based system to share DGE statistical test results, and locate and identify genes in DGE statistical test results with a very low barrier of entry. We have developed DEIVA, a free and open source, browser-based single page application (SPA) with a strong emphasis on being user friendly that enables locating and identifying single or multiple genes in an immediate, interactive, and intuitive manner. By design, DEIVA scales with very large numbers of users and datasets. Compared to existing software, DEIVA offers a unique combination of design decisions that enable inspection and analysis of DGE statistical test results with an emphasis on ease of use.

Asymptotic Distribution of the Likelihood Ratio Test Statistic for Sphericity of Complex Multivariate Normal Distribution.

DTIC Science & Technology

1981-08-01

RATIO TEST STATISTIC FOR SPHERICITY OF COMPLEX MULTIVARIATE NORMAL DISTRIBUTION* C. Fang P. R. Krishnaiah B. N. Nagarsenker** August 1981 Technical...and their applications in time sEries, the reader is referred to Krishnaiah (1976). Motivated by the applications in the area of inference on multiple...for practical purposes. Here, we note that Krishnaiah , Lee and Chang (1976) approxi- mated the null distribution of certain power of the likeli

A note on generalized Genome Scan Meta-Analysis statistics

PubMed Central

Koziol, James A; Feng, Anne C

2005-01-01

Background Wise et al. introduced a rank-based statistical technique for meta-analysis of genome scans, the Genome Scan Meta-Analysis (GSMA) method. Levinson et al. recently described two generalizations of the GSMA statistic: (i) a weighted version of the GSMA statistic, so that different studies could be ascribed different weights for analysis; and (ii) an order statistic approach, reflecting the fact that a GSMA statistic can be computed for each chromosomal region or bin width across the various genome scan studies. Results We provide an Edgeworth approximation to the null distribution of the weighted GSMA statistic, and, we examine the limiting distribution of the GSMA statistics under the order statistic formulation, and quantify the relevance of the pairwise correlations of the GSMA statistics across different bins on this limiting distribution. We also remark on aggregate criteria and multiple testing for determining significance of GSMA results. Conclusion Theoretical considerations detailed herein can lead to clarification and simplification of testing criteria for generalizations of the GSMA statistic. PMID:15717930

A spreadsheet template compatible with Microsoft Excel and iWork Numbers that returns the simultaneous confidence intervals for all pairwise differences between multiple sample means.

PubMed

Brown, Angus M

2010-04-01

The objective of the method described in this paper is to develop a spreadsheet template for the purpose of comparing multiple sample means. An initial analysis of variance (ANOVA) test on the data returns F--the test statistic. If F is larger than the critical F value drawn from the F distribution at the appropriate degrees of freedom, convention dictates rejection of the null hypothesis and allows subsequent multiple comparison testing to determine where the inequalities between the sample means lie. A variety of multiple comparison methods are described that return the 95% confidence intervals for differences between means using an inclusive pairwise comparison of the sample means. 2009 Elsevier Ireland Ltd. All rights reserved.

Study Designs and Statistical Analyses for Biomarker Research

PubMed Central

Gosho, Masahiko; Nagashima, Kengo; Sato, Yasunori

2012-01-01

Biomarkers are becoming increasingly important for streamlining drug discovery and development. In addition, biomarkers are widely expected to be used as a tool for disease diagnosis, personalized medication, and surrogate endpoints in clinical research. In this paper, we highlight several important aspects related to study design and statistical analysis for clinical research incorporating biomarkers. We describe the typical and current study designs for exploring, detecting, and utilizing biomarkers. Furthermore, we introduce statistical issues such as confounding and multiplicity for statistical tests in biomarker research. PMID:23012528

Informal Statistics Help Desk

NASA Technical Reports Server (NTRS)

Young, M.; Koslovsky, M.; Schaefer, Caroline M.; Feiveson, A. H.

2017-01-01

Back by popular demand, the JSC Biostatistics Laboratory and LSAH statisticians are offering an opportunity to discuss your statistical challenges and needs. Take the opportunity to meet the individuals offering expert statistical support to the JSC community. Join us for an informal conversation about any questions you may have encountered with issues of experimental design, analysis, or data visualization. Get answers to common questions about sample size, repeated measures, statistical assumptions, missing data, multiple testing, time-to-event data, and when to trust the results of your analyses.

FDR doesn't Tell the Whole Story: Joint Influence of Effect Size and Covariance Structure on the Distribution of the False Discovery Proportions

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Ploutz-Snyder, Robert; Fiedler, James

2011-01-01

As part of a 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report results of simulations that estimated the false discovery rate (FDR) for equally correlated test statistics using a well-known multiple-test procedure. In our study we estimate the distribution of the false discovery proportion (FDP) for the same procedure under a variety of correlation structures among multiple dependent variables in a MANOVA context. Specifically, we study the mean (the FDR), skewness, kurtosis, and percentiles of the FDP distribution in the case of multiple comparisons that give rise to correlated non-central t-statistics when results at several time periods are being compared to baseline. Even if the FDR achieves its nominal value, other aspects of the distribution of the FDP depend on the interaction between signed effect sizes and correlations among variables, proportion of true nulls, and number of dependent variables. We show examples where the mean FDP (the FDR) is 10% as designed, yet there is a surprising probability of having 30% or more false discoveries. Thus, in a real experiment, the proportion of false discoveries could be quite different from the stipulated FDR.

Mass univariate analysis of event-related brain potentials/fields I: a critical tutorial review.

PubMed

Groppe, David M; Urbach, Thomas P; Kutas, Marta

2011-12-01

Event-related potentials (ERPs) and magnetic fields (ERFs) are typically analyzed via ANOVAs on mean activity in a priori windows. Advances in computing power and statistics have produced an alternative, mass univariate analyses consisting of thousands of statistical tests and powerful corrections for multiple comparisons. Such analyses are most useful when one has little a priori knowledge of effect locations or latencies, and for delineating effect boundaries. Mass univariate analyses complement and, at times, obviate traditional analyses. Here we review this approach as applied to ERP/ERF data and four methods for multiple comparison correction: strong control of the familywise error rate (FWER) via permutation tests, weak control of FWER via cluster-based permutation tests, false discovery rate control, and control of the generalized FWER. We end with recommendations for their use and introduce free MATLAB software for their implementation. Copyright © 2011 Society for Psychophysiological Research.

A new method to address verification bias in studies of clinical screening tests: cervical cancer screening assays as an example.

PubMed

Xue, Xiaonan; Kim, Mimi Y; Castle, Philip E; Strickler, Howard D

2014-03-01

Studies to evaluate clinical screening tests often face the problem that the "gold standard" diagnostic approach is costly and/or invasive. It is therefore common to verify only a subset of negative screening tests using the gold standard method. However, undersampling the screen negatives can lead to substantial overestimation of the sensitivity and underestimation of the specificity of the diagnostic test. Our objective was to develop a simple and accurate statistical method to address this "verification bias." We developed a weighted generalized estimating equation approach to estimate, in a single model, the accuracy (eg, sensitivity/specificity) of multiple assays and simultaneously compare results between assays while addressing verification bias. This approach can be implemented using standard statistical software. Simulations were conducted to assess the proposed method. An example is provided using a cervical cancer screening trial that compared the accuracy of human papillomavirus and Pap tests, with histologic data as the gold standard. The proposed approach performed well in estimating and comparing the accuracy of multiple assays in the presence of verification bias. The proposed approach is an easy to apply and accurate method for addressing verification bias in studies of multiple screening methods. Copyright © 2014 Elsevier Inc. All rights reserved.

Which level of evidence does the US National Toxicology Program provide? Statistical considerations using the Technical Report 578 on Ginkgo biloba as an example.

PubMed

Gaus, Wilhelm

2014-09-02

The US National Toxicology Program (NTP) is assessed by a statistician. In the NTP-program groups of rodents are fed for a certain period of time with different doses of the substance that is being investigated. Then the animals are sacrificed and all organs are examined pathologically. Such an investigation facilitates many statistical tests. Technical Report TR 578 on Ginkgo biloba is used as an example. More than 4800 statistical tests are possible with the investigations performed. Due to a thought experiment we expect >240 false significant tests. In actuality, 209 significant pathological findings were reported. The readers of Toxicology Letters should carefully distinguish between confirmative and explorative statistics. A confirmative interpretation of a significant test rejects the null-hypothesis and delivers "statistical proof". It is only allowed if (i) a precise hypothesis was established independently from the data used for the test and (ii) the computed p-values are adjusted for multiple testing if more than one test was performed. Otherwise an explorative interpretation generates a hypothesis. We conclude that NTP-reports - including TR 578 on Ginkgo biloba - deliver explorative statistics, i.e. they generate hypotheses, but do not prove them. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Correcting for multiple-testing in multi-arm trials: is it necessary and is it done?

PubMed

Wason, James M S; Stecher, Lynne; Mander, Adrian P

2014-09-17

Multi-arm trials enable the evaluation of multiple treatments within a single trial. They provide a way of substantially increasing the efficiency of the clinical development process. However, since multi-arm trials test multiple hypotheses, some regulators require that a statistical correction be made to control the chance of making a type-1 error (false-positive). Several conflicting viewpoints are expressed in the literature regarding the circumstances in which a multiple-testing correction should be used. In this article we discuss these conflicting viewpoints and review the frequency with which correction methods are currently used in practice. We identified all multi-arm clinical trials published in 2012 by four major medical journals. Summary data on several aspects of the trial design were extracted, including whether the trial was exploratory or confirmatory, whether a multiple-testing correction was applied and, if one was used, what type it was. We found that almost half (49%) of published multi-arm trials report using a multiple-testing correction. The percentage that corrected was higher for trials in which the experimental arms included multiple doses or regimens of the same treatments (67%). The percentage that corrected was higher in exploratory than confirmatory trials, although this is explained by a greater proportion of exploratory trials testing multiple doses and regimens of the same treatment. A sizeable proportion of published multi-arm trials do not correct for multiple-testing. Clearer guidance about whether multiple-testing correction is needed for multi-arm trials that test separate treatments against a common control group is required.

Evaluation of Cepstrum Algorithm with Impact Seeded Fault Data of Helicopter Oil Cooler Fan Bearings and Machine Fault Simulator Data

DTIC Science & Technology

2013-02-01

of a bearing must be put into practice. There are many potential methods, the most traditional being the use of statistical time-domain features...accelerate degradation to test multiples bearings to gain statistical relevance and extrapolate results to scale for field conditions. Temperature...as time statistics , frequency estimation to improve the fault frequency detection. For future investigations, one can further explore the

Constructing objective tests

NASA Astrophysics Data System (ADS)

Aubrecht, Gordon J.; Aubrecht, Judith D.

1983-07-01

True-false or multiple-choice tests can be useful instruments for evaluating student progress. We examine strategies for planning objective tests which serve to test the material covered in science (physics) courses. We also examine strategies for writing questions for tests within a test blueprint. The statistical basis for judging the quality of test items are discussed. Reliability, difficulty, and discrimination indices are defined and examples presented. Our recommendation are rather easily put into practice.

The potential for increased power from combining P-values testing the same hypothesis.

PubMed

Ganju, Jitendra; Julie Ma, Guoguang

2017-02-01

The conventional approach to hypothesis testing for formal inference is to prespecify a single test statistic thought to be optimal. However, we usually have more than one test statistic in mind for testing the null hypothesis of no treatment effect but we do not know which one is the most powerful. Rather than relying on a single p-value, combining p-values from prespecified multiple test statistics can be used for inference. Combining functions include Fisher's combination test and the minimum p-value. Using randomization-based tests, the increase in power can be remarkable when compared with a single test and Simes's method. The versatility of the method is that it also applies when the number of covariates exceeds the number of observations. The increase in power is large enough to prefer combined p-values over a single p-value. The limitation is that the method does not provide an unbiased estimator of the treatment effect and does not apply to situations when the model includes treatment by covariate interaction.

Bayesian estimation of the transmissivity spatial structure from pumping test data

NASA Astrophysics Data System (ADS)

Demir, Mehmet Taner; Copty, Nadim K.; Trinchero, Paolo; Sanchez-Vila, Xavier

2017-06-01

Estimating the statistical parameters (mean, variance, and integral scale) that define the spatial structure of the transmissivity or hydraulic conductivity fields is a fundamental step for the accurate prediction of subsurface flow and contaminant transport. In practice, the determination of the spatial structure is a challenge because of spatial heterogeneity and data scarcity. In this paper, we describe a novel approach that uses time drawdown data from multiple pumping tests to determine the transmissivity statistical spatial structure. The method builds on the pumping test interpretation procedure of Copty et al. (2011) (Continuous Derivation method, CD), which uses the time-drawdown data and its time derivative to estimate apparent transmissivity values as a function of radial distance from the pumping well. A Bayesian approach is then used to infer the statistical parameters of the transmissivity field by combining prior information about the parameters and the likelihood function expressed in terms of radially-dependent apparent transmissivities determined from pumping tests. A major advantage of the proposed Bayesian approach is that the likelihood function is readily determined from randomly generated multiple realizations of the transmissivity field, without the need to solve the groundwater flow equation. Applying the method to synthetically-generated pumping test data, we demonstrate that, through a relatively simple procedure, information on the spatial structure of the transmissivity may be inferred from pumping tests data. It is also shown that the prior parameter distribution has a significant influence on the estimation procedure, given the non-uniqueness of the estimation procedure. Results also indicate that the reliability of the estimated transmissivity statistical parameters increases with the number of available pumping tests.

Spatial scan statistics for detection of multiple clusters with arbitrary shapes.

PubMed

Lin, Pei-Sheng; Kung, Yi-Hung; Clayton, Murray

2016-12-01

In applying scan statistics for public health research, it would be valuable to develop a detection method for multiple clusters that accommodates spatial correlation and covariate effects in an integrated model. In this article, we connect the concepts of the likelihood ratio (LR) scan statistic and the quasi-likelihood (QL) scan statistic to provide a series of detection procedures sufficiently flexible to apply to clusters of arbitrary shape. First, we use an independent scan model for detection of clusters and then a variogram tool to examine the existence of spatial correlation and regional variation based on residuals of the independent scan model. When the estimate of regional variation is significantly different from zero, a mixed QL estimating equation is developed to estimate coefficients of geographic clusters and covariates. We use the Benjamini-Hochberg procedure (1995) to find a threshold for p-values to address the multiple testing problem. A quasi-deviance criterion is used to regroup the estimated clusters to find geographic clusters with arbitrary shapes. We conduct simulations to compare the performance of the proposed method with other scan statistics. For illustration, the method is applied to enterovirus data from Taiwan. © 2016, The International Biometric Society.

Relationship between contrast sensitivity test and disease severity in multiple sclerosis patients.

PubMed

Soler García, A; González Gómez, A; Figueroa-Ortiz, L C; García-Ben, A; García-Campos, J

2014-09-01

To assess the importance of the Pelli-Robson contrast sensitivity test in multiple sclerosis patients according to the Expanded Disability Status Scale (EDSS). A total of 62 patients with multiple sclerosis were included in a retrospective study. Patients were enrolled from the Neurology Department to Neuroophthalmology at Virgen de la Victoria Hospital. Patients were classified into 3 groups according to EDSS: group A) lower than 1.5, group B) between 1.5 and 3.5 and group C) greater than 3.5. Visual acuity and monocular and binocular contrast sensitivity were performed with Snellen and Pelli-Robson tests respectively. Twelve disease-free control participants were also recruited. Correlations between parameter changes were analyzed. The mean duration of the disease was 81.54±35.32 months. Monocular and binocular Pelli-Robson mean values in the control group were 1.82±0.10 and 1.93±0.43 respectively, and 1.61±0.29 and 1.83±0.19 in multiple sclerosis patients. There were statistically significant differences in the monocular analysis for a level of significance P<.05. Mean monocular and binocular Pelli-Robson values in relation to gravity level were, in group A: 1.66±0.24 and 1.90±0.98, group B: 1.64±0.21 and 1.82±0.16, and group C: 1.47±0.45 and 1.73±0.32 respectively. Group differences were statistically significant in both tests: P=.05 and P=.027. Monocular and binocular contrast discrimination analyzed using the Pelli-Robson test was found to be significantly lower when the severity level, according EDSS, increases in multiple sclerosis patients. Copyright © 2013 Sociedad Española de Oftalmología. Published by Elsevier Espana. All rights reserved.

Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

NASA Technical Reports Server (NTRS)

Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

1984-01-01

An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.

Multiple Choice Questions Can Be Designed or Revised to Challenge Learners' Critical Thinking

ERIC Educational Resources Information Center

Tractenberg, Rochelle E.; Gushta, Matthew M.; Mulroney, Susan E.; Weissinger, Peggy A.

2013-01-01

Multiple choice (MC) questions from a graduate physiology course were evaluated by cognitive-psychology (but not physiology) experts, and analyzed statistically, in order to test the independence of content expertise and cognitive complexity ratings of MC items. Integration of higher order thinking into MC exams is important, but widely known to…

The Effect of Images on Item Statistics in Multiple Choice Anatomy Examinations

ERIC Educational Resources Information Center

Notebaert, Andrew J.

2017-01-01

Although multiple choice examinations are often used to test anatomical knowledge, these often forgo the use of images in favor of text-based questions and answers. Because anatomy is reliant on visual resources, examinations using images should be used when appropriate. This study was a retrospective analysis of examination items that were text…

High time for a change: psychometric analysis of multiple-choice questions in nursing.

PubMed

Redmond, Sandra P; Hartigan-Rogers, Jackie A; Cobbett, Shelley

2012-11-26

Nurse educators teach students to develop an informed nursing practice but can educators claim the same grounding in the available evidence when formulating multiple-choice assessment tools to evaluate student learning? Multiple-choice questions are a popular assessment format within nursing education. While widely accepted as a credible format to assess student knowledge across disciplines, debate exists among educators regarding the number of options necessary to adequately test cognitive reasoning and optimal discrimination between student abilities. The purpose of this quasi-experimental between groups study was to examine the psychometric properties of three option multiple-choice questions when compared to the more traditional four option questions. Data analysis revealed that there were no statistically significant differences in the item discrimination, difficulty or the mean examination scores when multiple-choice test questions were administered with three versus four option answer choices. This study provides additional guidance for nurse educators to assist in improving multiple-choice question writing and test design.

Application of modified profile analysis to function testing of the motion/no-motion issue in an aircraft ground-handling simulation. [statistical analysis procedure for man machine systems flight simulation

NASA Technical Reports Server (NTRS)

Parrish, R. V.; Mckissick, B. T.; Steinmetz, G. G.

1979-01-01

A recent modification of the methodology of profile analysis, which allows the testing for differences between two functions as a whole with a single test, rather than point by point with multiple tests is discussed. The modification is applied to the examination of the issue of motion/no motion conditions as shown by the lateral deviation curve as a function of engine cut speed of a piloted 737-100 simulator. The results of this application are presented along with those of more conventional statistical test procedures on the same simulator data.

Factors related to student performance in statistics courses in Lebanon

NASA Astrophysics Data System (ADS)

Naccache, Hiba Salim

The purpose of the present study was to identify factors that may contribute to business students in Lebanese universities having difficulty in introductory and advanced statistics courses. Two statistics courses are required for business majors at Lebanese universities. Students are not obliged to be enrolled in any math courses prior to taking statistics courses. Drawing on recent educational research, this dissertation attempted to identify the relationship between (1) students’ scores on Lebanese university math admissions tests; (2) students’ scores on a test of very basic mathematical concepts; (3) students’ scores on the survey of attitude toward statistics (SATS); (4) course performance as measured by students’ final scores in the course; and (5) their scores on the final exam. Data were collected from 561 students enrolled in multiple sections of two courses: 307 students in the introductory statistics course and 260 in the advanced statistics course in seven campuses across Lebanon over one semester. The multiple regressions results revealed four significant relationships at the introductory level: between students’ scores on the math quiz with their (1) final exam scores; (2) their final averages; (3) the Cognitive subscale of the SATS with their final exam scores; and (4) their final averages. These four significant relationships were also found at the advanced level. In addition, two more significant relationships were found between students’ final average and the two subscales of Effort (5) and Affect (6). No relationship was found between students’ scores on the admission math tests and both their final exam scores and their final averages in both the introductory and advanced level courses. On the other hand, there was no relationship between students’ scores on Lebanese admissions tests and their final achievement. Although these results were consistent across course formats and instructors, they may encourage Lebanese universities to assess the effectiveness of prerequisite math courses. Moreover, these findings may lead the Lebanese Ministry of Education to make changes to the admissions exams, course prerequisites, and course content. Finally, to enhance the attitude of students, new learning techniques, such as group work during class meetings can be helpful, and future research should aim to test the effectiveness of these pedagogical techniques on students’ attitudes toward statistics.

Comparability of Computer- and Paper-Administered Multiple-Choice Tests for K-12 Populations: A Synthesis

ERIC Educational Resources Information Center

Kingston, Neal M.

2009-01-01

There have been many studies of the comparability of computer-administered and paper-administered tests. Not surprisingly (given the variety of measurement and statistical sampling issues that can affect any one study) the results of such studies have not always been consistent. Moreover, the quality of computer-based test administration systems…

p-hacking by post hoc selection with multiple opportunities: Detectability by skewness test?: Comment on Simonsohn, Nelson, and Simmons (2014).

PubMed

Ulrich, Rolf; Miller, Jeff

2015-12-01

Simonsohn, Nelson, and Simmons (2014) have suggested a novel test to detect p-hacking in research, that is, when researchers report excessive rates of "significant effects" that are truly false positives. Although this test is very useful for identifying true effects in some cases, it fails to identify false positives in several situations when researchers conduct multiple statistical tests (e.g., reporting the most significant result). In these cases, p-curves are right-skewed, thereby mimicking the existence of real effects even if no effect is actually present. (c) 2015 APA, all rights reserved).

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits

PubMed Central

Zeng, Ping; Mukherjee, Sayan; Zhou, Xiang

2017-01-01

Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects—the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the “MArginal ePIstasis Test”, or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium. PMID:28746338

The Relative Importance of Low Significance Level and High Power in Multiple Tests of Significance.

ERIC Educational Resources Information Center

Westermann, Rainer; Hager, Willi

1983-01-01

Two psychological experiments--Anderson and Shanteau (1970), Berkowitz and LePage (1967)--are reanalyzed to present the problem of the relative importance of low Type 1 error probability and high power when answering a research question by testing several statistical hypotheses. (Author/PN)

[The problem of small "n" and big "P" in neuropsycho-pharmacology, or how to keep the rate of false discoveries under control].

PubMed

Petschner, Péter; Bagdy, György; Tóthfalusi, Laszló

2015-03-01

One of the characteristics of many methods used in neuropsychopharmacology is that a large number of parameters (P) are measured in relatively few subjects (n). Functional magnetic resonance imaging, electroencephalography (EEG) and genomic studies are typical examples. For example one microarray chip can contain thousands of probes. Therefore, in studies using microarray chips, P may be several thousand-fold larger than n. Statistical analysis of such studies is a challenging task and they are refereed to in the statistical literature such as the small "n" big "P" problem. The problem has many facets including the controversies associated with multiple hypothesis testing. A typical scenario in this context is, when two or more groups are compared by the individual attributes. If the increased classification error due to the multiple testing is neglected, then several highly significant differences will be discovered. But in reality, some of these significant differences are coincidental, not reproducible findings. Several methods were proposed to solve this problem. In this review we discuss two of the proposed solutions, algorithms to compare sets and statistical hypothesis tests controlling the false discovery rate.

Testing independence of bivariate interval-censored data using modified Kendall's tau statistic.

PubMed

Kim, Yuneung; Lim, Johan; Park, DoHwan

2015-11-01

In this paper, we study a nonparametric procedure to test independence of bivariate interval censored data; for both current status data (case 1 interval-censored data) and case 2 interval-censored data. To do it, we propose a score-based modification of the Kendall's tau statistic for bivariate interval-censored data. Our modification defines the Kendall's tau statistic with expected numbers of concordant and disconcordant pairs of data. The performance of the modified approach is illustrated by simulation studies and application to the AIDS study. We compare our method to alternative approaches such as the two-stage estimation method by Sun et al. (Scandinavian Journal of Statistics, 2006) and the multiple imputation method by Betensky and Finkelstein (Statistics in Medicine, 1999b). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Testing for clustering at many ranges inflates family-wise error rate (FWE).

PubMed

Loop, Matthew Shane; McClure, Leslie A

2015-01-15

Testing for clustering at multiple ranges within a single dataset is a common practice in spatial epidemiology. It is not documented whether this approach has an impact on the type 1 error rate. We estimated the family-wise error rate (FWE) for the difference in Ripley's K functions test, when testing at an increasing number of ranges at an alpha-level of 0.05. Case and control locations were generated from a Cox process on a square area the size of the continental US (≈3,000,000 mi2). Two thousand Monte Carlo replicates were used to estimate the FWE with 95% confidence intervals when testing for clustering at one range, as well as 10, 50, and 100 equidistant ranges. The estimated FWE and 95% confidence intervals when testing 10, 50, and 100 ranges were 0.22 (0.20 - 0.24), 0.34 (0.31 - 0.36), and 0.36 (0.34 - 0.38), respectively. Testing for clustering at multiple ranges within a single dataset inflated the FWE above the nominal level of 0.05. Investigators should construct simultaneous critical envelopes (available in spatstat package in R), or use a test statistic that integrates the test statistics from each range, as suggested by the creators of the difference in Ripley's K functions test.

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

A Novel Genome-Information Content-Based Statistic for Genome-Wide Association Analysis Designed for Next-Generation Sequencing Data

PubMed Central

Luo, Li; Zhu, Yun

2012-01-01

Abstract The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T2, collapsing method, multivariate and collapsing (CMC) method, individual χ2 test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets. PMID:22651812

A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data.

PubMed

Luo, Li; Zhu, Yun; Xiong, Momiao

2012-06-01

The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.

Statistical Estimation of Heterogeneities: A New Frontier in Well Testing

NASA Astrophysics Data System (ADS)

Neuman, S. P.; Guadagnini, A.; Illman, W. A.; Riva, M.; Vesselinov, V. V.

2001-12-01

Well-testing methods have traditionally relied on analytical solutions of groundwater flow equations in relatively simple domains, consisting of one or at most a few units having uniform hydraulic properties. Recently, attention has been shifting toward methods and solutions that would allow one to characterize subsurface heterogeneities in greater detail. On one hand, geostatistical inverse methods are being used to assess the spatial variability of parameters, such as permeability and porosity, on the basis of multiple cross-hole pressure interference tests. On the other hand, analytical solutions are being developed to describe the mean and variance (first and second statistical moments) of flow to a well in a randomly heterogeneous medium. Geostatistical inverse interpretation of cross-hole tests yields a smoothed but detailed "tomographic" image of how parameters actually vary in three-dimensional space, together with corresponding measures of estimation uncertainty. Moment solutions may soon allow one to interpret well tests in terms of statistical parameters such as the mean and variance of log permeability, its spatial autocorrelation and statistical anisotropy. The idea of geostatistical cross-hole tomography is illustrated through pneumatic injection tests conducted in unsaturated fractured tuff at the Apache Leap Research Site near Superior, Arizona. The idea of using moment equations to interpret well-tests statistically is illustrated through a recently developed three-dimensional solution for steady state flow to a well in a bounded, randomly heterogeneous, statistically anisotropic aquifer.

A Statistical Analysis of Brain Morphology Using Wild Bootstrapping

PubMed Central

Ibrahim, Joseph G.; Tang, Niansheng; Rowe, Daniel B.; Hao, Xuejun; Bansal, Ravi; Peterson, Bradley S.

2008-01-01

Methods for the analysis of brain morphology, including voxel-based morphology and surface-based morphometries, have been used to detect associations between brain structure and covariates of interest, such as diagnosis, severity of disease, age, IQ, and genotype. The statistical analysis of morphometric measures usually involves two statistical procedures: 1) invoking a statistical model at each voxel (or point) on the surface of the brain or brain subregion, followed by mapping test statistics (e.g., t test) or their associated p values at each of those voxels; 2) correction for the multiple statistical tests conducted across all voxels on the surface of the brain region under investigation. We propose the use of new statistical methods for each of these procedures. We first use a heteroscedastic linear model to test the associations between the morphological measures at each voxel on the surface of the specified subregion (e.g., cortical or subcortical surfaces) and the covariates of interest. Moreover, we develop a robust test procedure that is based on a resampling method, called wild bootstrapping. This procedure assesses the statistical significance of the associations between a measure of given brain structure and the covariates of interest. The value of this robust test procedure lies in its computationally simplicity and in its applicability to a wide range of imaging data, including data from both anatomical and functional magnetic resonance imaging (fMRI). Simulation studies demonstrate that this robust test procedure can accurately control the family-wise error rate. We demonstrate the application of this robust test procedure to the detection of statistically significant differences in the morphology of the hippocampus over time across gender groups in a large sample of healthy subjects. PMID:17649909

The Oxford Sleep Resistance test (OSLER) and the Multiple Unprepared Reaction Time Test (MURT) Detect Vigilance Modifications in Sleep Apnea Patients

PubMed Central

Alakuijala, Anniina; Maasilta, Paula; Bachour, Adel

2014-01-01

Study Objectives: The Oxford Sleep Resistance Test (OSLER) is a behavioral test that measures a subject's ability to maintain wakefulness and assesses daytime vigilance. The multiple unprepared reaction time (MURT) test measures a subject's reaction time in response to a series of visual or audible stimuli. Methods: We recruited 34 healthy controls in order to determine the normative data for MURT. Then we evaluated modifications in OSLER and MURT values in 192 patients who were referred for suspicion of sleep apnea. We performed OSLER (three 40-min sessions) and MURT (two 10-min sessions) tests at baseline. Of 173 treated OSA patients, 29 professional drivers were retested within six months of treatment. Results: MURT values above 250 ms can be considered abnormal. The OSLER error index (the number of all errors divided by the duration of the session in hours) correlated statistically significantly with sleep latency, MURT time, and ESS. Treatment improved OSLER sleep latency from 33 min 4 s to 36 min 48 s, OSLER error index from 66/h to 26/h, and MURT time from 278 ms to 224 ms; these differences were statistically significant. Conclusions: OSLER and MURT tests are practical and reliable tools for measuring improvement in vigilance due to sleep apnea therapy in professional drivers. Citation: Alakuijala A, Maasilta P, Bachour A. The Oxford Sleep Resistance Test (OSLER) and the multiple unprepared reaction time test (MURT) detect vigilance modifications in sleep apnea patients. J Clin Sleep Med 2014;10(10):1075-1082. PMID:25317088

OPATs: Omnibus P-value association tests.

PubMed

Chen, Chia-Wei; Yang, Hsin-Chou

2017-07-10

Combining statistical significances (P-values) from a set of single-locus association tests in genome-wide association studies is a proof-of-principle method for identifying disease-associated genomic segments, functional genes and biological pathways. We review P-value combinations for genome-wide association studies and introduce an integrated analysis tool, Omnibus P-value Association Tests (OPATs), which provides popular analysis methods of P-value combinations. The software OPATs programmed in R and R graphical user interface features a user-friendly interface. In addition to analysis modules for data quality control and single-locus association tests, OPATs provides three types of set-based association test: window-, gene- and biopathway-based association tests. P-value combinations with or without threshold and rank truncation are provided. The significance of a set-based association test is evaluated by using resampling procedures. Performance of the set-based association tests in OPATs has been evaluated by simulation studies and real data analyses. These set-based association tests help boost the statistical power, alleviate the multiple-testing problem, reduce the impact of genetic heterogeneity, increase the replication efficiency of association tests and facilitate the interpretation of association signals by streamlining the testing procedures and integrating the genetic effects of multiple variants in genomic regions of biological relevance. In summary, P-value combinations facilitate the identification of marker sets associated with disease susceptibility and uncover missing heritability in association studies, thereby establishing a foundation for the genetic dissection of complex diseases and traits. OPATs provides an easy-to-use and statistically powerful analysis tool for P-value combinations. OPATs, examples, and user guide can be downloaded from http://www.stat.sinica.edu.tw/hsinchou/genetics/association/OPATs.htm. © The Author 2017. Published by Oxford University Press.

Cross-situational statistical word learning in young children.

PubMed

Suanda, Sumarga H; Mugwanya, Nassali; Namy, Laura L

2014-10-01

Recent empirical work has highlighted the potential role of cross-situational statistical word learning in children's early vocabulary development. In the current study, we tested 5- to 7-year-old children's cross-situational learning by presenting children with a series of ambiguous naming events containing multiple words and multiple referents. Children rapidly learned word-to-object mappings by attending to the co-occurrence regularities across these ambiguous naming events. The current study begins to address the mechanisms underlying children's learning by demonstrating that the diversity of learning contexts affects performance. The implications of the current findings for the role of cross-situational word learning at different points in development are discussed along with the methodological implications of employing school-aged children to test hypotheses regarding the mechanisms supporting early word learning. Copyright © 2014 Elsevier Inc. All rights reserved.

A spatial scan statistic for compound Poisson data.

PubMed

Rosychuk, Rhonda J; Chang, Hsing-Ming

2013-12-20

The topic of spatial cluster detection gained attention in statistics during the late 1980s and early 1990s. Effort has been devoted to the development of methods for detecting spatial clustering of cases and events in the biological sciences, astronomy and epidemiology. More recently, research has examined detecting clusters of correlated count data associated with health conditions of individuals. Such a method allows researchers to examine spatial relationships of disease-related events rather than just incident or prevalent cases. We introduce a spatial scan test that identifies clusters of events in a study region. Because an individual case may have multiple (repeated) events, we base the test on a compound Poisson model. We illustrate our method for cluster detection on emergency department visits, where individuals may make multiple disease-related visits. Copyright © 2013 John Wiley & Sons, Ltd.

Identifying reprioritization response shift in a stroke caregiver population: a comparison of missing data methods.

PubMed

Sajobi, Tolulope T; Lix, Lisa M; Singh, Gurbakhshash; Lowerison, Mark; Engbers, Jordan; Mayo, Nancy E

2015-03-01

Response shift (RS) is an important phenomenon that influences the assessment of longitudinal changes in health-related quality of life (HRQOL) studies. Given that RS effects are often small, missing data due to attrition or item non-response can contribute to failure to detect RS effects. Since missing data are often encountered in longitudinal HRQOL data, effective strategies to deal with missing data are important to consider. This study aims to compare different imputation methods on the detection of reprioritization RS in the HRQOL of caregivers of stroke survivors. Data were from a Canadian multi-center longitudinal study of caregivers of stroke survivors over a one-year period. The Stroke Impact Scale physical function score at baseline, with a cutoff of 75, was used to measure patient stroke severity for the reprioritization RS analysis. Mean imputation, likelihood-based expectation-maximization imputation, and multiple imputation methods were compared in test procedures based on changes in relative importance weights to detect RS in SF-36 domains over a 6-month period. Monte Carlo simulation methods were used to compare the statistical powers of relative importance test procedures for detecting RS in incomplete longitudinal data under different missing data mechanisms and imputation methods. Of the 409 caregivers, 15.9 and 31.3 % of them had missing data at baseline and 6 months, respectively. There were no statistically significant changes in relative importance weights on any of the domains when complete-case analysis was adopted. But statistical significant changes were detected on physical functioning and/or vitality domains when mean imputation or EM imputation was adopted. There were also statistically significant changes in relative importance weights for physical functioning, mental health, and vitality domains when multiple imputation method was adopted. Our simulations revealed that relative importance test procedures were least powerful under complete-case analysis method and most powerful when a mean imputation or multiple imputation method was adopted for missing data, regardless of the missing data mechanism and proportion of missing data. Test procedures based on relative importance measures are sensitive to the type and amount of missing data and imputation method. Relative importance test procedures based on mean imputation and multiple imputation are recommended for detecting RS in incomplete data.

Detecting Genomic Clustering of Risk Variants from Sequence Data: Cases vs. Controls

PubMed Central

Schaid, Daniel J.; Sinnwell, Jason P.; McDonnell, Shannon K.; Thibodeau, Stephen N.

2013-01-01

As the ability to measure dense genetic markers approaches the limit of the DNA sequence itself, taking advantage of possible clustering of genetic variants in, and around, a gene would benefit genetic association analyses, and likely provide biological insights. The greatest benefit might be realized when multiple rare variants cluster in a functional region. Several statistical tests have been developed, one of which is based on the popular Kulldorff scan statistic for spatial clustering of disease. We extended another popular spatial clustering method – Tango’s statistic – to genomic sequence data. An advantage of Tango’s method is that it is rapid to compute, and when single test statistic is computed, its distribution is well approximated by a scaled chi-square distribution, making computation of p-values very rapid. We compared the Type-I error rates and power of several clustering statistics, as well as the omnibus sequence kernel association test (SKAT). Although our version of Tango’s statistic, which we call “Kernel Distance” statistic, took approximately half the time to compute than the Kulldorff scan statistic, it had slightly less power than the scan statistic. Our results showed that the Ionita-Laza version of Kulldorff’s scan statistic had the greatest power over a range of clustering scenarios. PMID:23842950

Reporting Practices and Use of Quantitative Methods in Canadian Journal Articles in Psychology.

PubMed

Counsell, Alyssa; Harlow, Lisa L

2017-05-01

With recent focus on the state of research in psychology, it is essential to assess the nature of the statistical methods and analyses used and reported by psychological researchers. To that end, we investigated the prevalence of different statistical procedures and the nature of statistical reporting practices in recent articles from the four major Canadian psychology journals. The majority of authors evaluated their research hypotheses through the use of analysis of variance (ANOVA), t -tests, and multiple regression. Multivariate approaches were less common. Null hypothesis significance testing remains a popular strategy, but the majority of authors reported a standardized or unstandardized effect size measure alongside their significance test results. Confidence intervals on effect sizes were infrequently employed. Many authors provided minimal details about their statistical analyses and less than a third of the articles presented on data complications such as missing data and violations of statistical assumptions. Strengths of and areas needing improvement for reporting quantitative results are highlighted. The paper concludes with recommendations for how researchers and reviewers can improve comprehension and transparency in statistical reporting.

Targeted versus statistical approaches to selecting parameters for modelling sediment provenance

NASA Astrophysics Data System (ADS)

Laceby, J. Patrick

2017-04-01

One effective field-based approach to modelling sediment provenance is the source fingerprinting technique. Arguably, one of the most important steps for this approach is selecting the appropriate suite of parameters or fingerprints used to model source contributions. Accordingly, approaches to selecting parameters for sediment source fingerprinting will be reviewed. Thereafter, opportunities and limitations of these approaches and some future research directions will be presented. For properties to be effective tracers of sediment, they must discriminate between sources whilst behaving conservatively. Conservative behavior is characterized by constancy in sediment properties, where the properties of sediment sources remain constant, or at the very least, any variation in these properties should occur in a predictable and measurable way. Therefore, properties selected for sediment source fingerprinting should remain constant through sediment detachment, transportation and deposition processes, or vary in a predictable and measurable way. One approach to select conservative properties for sediment source fingerprinting is to identify targeted tracers, such as caesium-137, that provide specific source information (e.g. surface versus subsurface origins). A second approach is to use statistical tests to select an optimal suite of conservative properties capable of modelling sediment provenance. In general, statistical approaches use a combination of a discrimination (e.g. Kruskal Wallis H-test, Mann-Whitney U-test) and parameter selection statistics (e.g. Discriminant Function Analysis or Principle Component Analysis). The challenge is that modelling sediment provenance is often not straightforward and there is increasing debate in the literature surrounding the most appropriate approach to selecting elements for modelling. Moving forward, it would be beneficial if researchers test their results with multiple modelling approaches, artificial mixtures, and multiple lines of evidence to provide secondary support to their initial modelling results. Indeed, element selection can greatly impact modelling results and having multiple lines of evidence will help provide confidence when modelling sediment provenance.

Test anxiety and academic performance in chiropractic students.

PubMed

Zhang, Niu; Henderson, Charles N R

2014-01-01

Objective : We assessed the level of students' test anxiety, and the relationship between test anxiety and academic performance. Methods : We recruited 166 third-quarter students. The Test Anxiety Inventory (TAI) was administered to all participants. Total scores from written examinations and objective structured clinical examinations (OSCEs) were used as response variables. Results : Multiple regression analysis shows that there was a modest, but statistically significant negative correlation between TAI scores and written exam scores, but not OSCE scores. Worry and emotionality were the best predictive models for written exam scores. Mean total anxiety and emotionality scores for females were significantly higher than those for males, but not worry scores. Conclusion : Moderate-to-high test anxiety was observed in 85% of the chiropractic students examined. However, total test anxiety, as measured by the TAI score, was a very weak predictive model for written exam performance. Multiple regression analysis demonstrated that replacing total anxiety (TAI) with worry and emotionality (TAI subscales) produces a much more effective predictive model of written exam performance. Sex, age, highest current academic degree, and ethnicity contributed little additional predictive power in either regression model. Moreover, TAI scores were not found to be statistically significant predictors of physical exam skill performance, as measured by OSCEs.

Normality of raw data in general linear models: The most widespread myth in statistics

USGS Publications Warehouse

Kery, Marc; Hatfield, Jeff S.

2003-01-01

In years of statistical consulting for ecologists and wildlife biologists, by far the most common misconception we have come across has been the one about normality in general linear models. These comprise a very large part of the statistical models used in ecology and include t tests, simple and multiple linear regression, polynomial regression, and analysis of variance (ANOVA) and covariance (ANCOVA). There is a widely held belief that the normality assumption pertains to the raw data rather than to the model residuals. We suspect that this error may also occur in countless published studies, whenever the normality assumption is tested prior to analysis. This may lead to the use of nonparametric alternatives (if there are any), when parametric tests would indeed be appropriate, or to use of transformations of raw data, which may introduce hidden assumptions such as multiplicative effects on the natural scale in the case of log-transformed data. Our aim here is to dispel this myth. We very briefly describe relevant theory for two cases of general linear models to show that the residuals need to be normally distributed if tests requiring normality are to be used, such as t and F tests. We then give two examples demonstrating that the distribution of the response variable may be nonnormal, and yet the residuals are well behaved. We do not go into the issue of how to test normality; instead we display the distributions of response variables and residuals graphically.

LP-search and its use in analysis of the accuracy of control systems with acoustical models

NASA Technical Reports Server (NTRS)

Sergeyev, V. I.; Sobol, I. M.; Statnikov, R. B.; Statnikov, I. N.

1973-01-01

The LP-search is proposed as an analog of the Monte Carlo method for finding values in nonlinear statistical systems. It is concluded that: To attain the required accuracy in solution to the problem of control for a statistical system in the LP-search, a considerably smaller number of tests is required than in the Monte Carlo method. The LP-search allows the possibility of multiple repetitions of tests under identical conditions and observability of the output variables of the system.

The Effect of Multiple Firings on the Shear Bond Strength of Porcelain to a New Millable Alloy and a Conventional Casting Alloy

PubMed Central

Farzin, Mitra; Giti, Rashin; Asalforush-Rezaiye, Amin

2018-01-01

This study compared the effect of multiple firings on the shear bond strength (SBS) of porcelain to the new millable alloy (Ceramill Sintron) and a conventional casting alloy (4-all). Thirty-six cylindrical cores (6.8 × 9 mm) were made of millable and castable alloy through CAD/CAM and casting techniques, respectively (n = 18). In the center of each bar, a 4 × 4 × 2-mm shot of porcelain was fused. Having divided each group into 3 subgroups based on the number of firing cycles (3, 5, 7), the specimens were fixed in a universal testing machine and underwent a shear force test (1.5 mm/min crosshead speed) until fractured. Then the SBS values (MPa) were calculated, and the failure patterns were microscopically characterized as adhesive, cohesive, or mixed. Two-way ANOVA statistical test revealed that the number of porcelain firings had no significant effect on the SBS of any of the metal groups (p = 0.1); however, it was statistically higher in the millable group than the castable group (p < 0.05). Moreover, detecting the mixed failure pattern in all the specimens implied that the multiple firings had no significant effect on the failure pattern. The multiple porcelain firings had no significant effect on the SBS of porcelain to neither the millable nor castable alloys. PMID:29565827

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments.

PubMed

Ramadas, Gisela C V; Rocha, Ana Maria A C; Fernandes, Edite M G P

2015-01-01

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

A Bayesian test for Hardy–Weinberg equilibrium of biallelic X-chromosomal markers

PubMed Central

Puig, X; Ginebra, J; Graffelman, J

2017-01-01

The X chromosome is a relatively large chromosome, harboring a lot of genetic information. Much of the statistical analysis of X-chromosomal information is complicated by the fact that males only have one copy. Recently, frequentist statistical tests for Hardy–Weinberg equilibrium have been proposed specifically for dealing with markers on the X chromosome. Bayesian test procedures for Hardy–Weinberg equilibrium for the autosomes have been described, but Bayesian work on the X chromosome in this context is lacking. This paper gives the first Bayesian approach for testing Hardy–Weinberg equilibrium with biallelic markers at the X chromosome. Marginal and joint posterior distributions for the inbreeding coefficient in females and the male to female allele frequency ratio are computed, and used for statistical inference. The paper gives a detailed account of the proposed Bayesian test, and illustrates it with data from the 1000 Genomes project. In that implementation, a novel approach to tackle multiple testing from a Bayesian perspective through posterior predictive checks is used. PMID:28900292

A new statistical method for transfer coefficient calculations in the framework of the general multiple-compartment model of transport for radionuclides in biological systems.

PubMed

Garcia, F; Arruda-Neto, J D; Manso, M V; Helene, O M; Vanin, V R; Rodriguez, O; Mesa, J; Likhachev, V P; Filho, J W; Deppman, A; Perez, G; Guzman, F; de Camargo, S P

1999-10-01

A new and simple statistical procedure (STATFLUX) for the calculation of transfer coefficients of radionuclide transport to animals and plants is proposed. The method is based on the general multiple-compartment model, which uses a system of linear equations involving geometrical volume considerations. By using experimentally available curves of radionuclide concentrations versus time, for each animal compartment (organs), flow parameters were estimated by employing a least-squares procedure, whose consistency is tested. Some numerical results are presented in order to compare the STATFLUX transfer coefficients with those from other works and experimental data.

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

PubMed

Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

2009-11-01

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrices

NASA Astrophysics Data System (ADS)

Passemier, Damien; McKay, Matthew R.; Chen, Yang

2015-07-01

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked correlation), non-central Wishart with rank-one non-centrality, and a related class of non-central matrices. For a generic linear statistic, we derive simple and explicit CLT expressions as the matrix dimensions grow large. For all three ensembles under consideration, we find that the primary effect of the spike is to introduce an correction term to the asymptotic mean of the linear spectral statistic, which we characterize with simple formulas. The utility of our proposed framework is demonstrated through application to three different linear statistics problems: the classical likelihood ratio test for a population covariance, the capacity analysis of multi-antenna wireless communication systems with a line-of-sight transmission path, and a classical multiple sample significance testing problem.

The results of STEM education methods for enhancing critical thinking and problem solving skill in physics the 10th grade level

NASA Astrophysics Data System (ADS)

Soros, P.; Ponkham, K.; Ekkapim, S.

2018-01-01

This research aimed to: 1) compare the critical think and problem solving skills before and after learning using STEM Education plan, 2) compare student achievement before and after learning about force and laws of motion using STEM Education plan, and 3) the satisfaction of learning by using STEM Education. The sample used were 37 students from grade 10 at Borabu School, Borabu District, Mahasarakham Province, semester 2, Academic year 2016. Tools used in this study consist of: 1) STEM Education plan about the force and laws of motion for grade 10 students of 1 schemes with total of 14 hours, 2) The test of critical think and problem solving skills with multiple-choice type of 5 options and 2 option of 30 items, 3) achievement test on force and laws of motion with multiple-choice of 4 options of 30 items, 4) satisfaction learning with 5 Rating Scale of 20 items. The statistics used in data analysis were percentage, mean, standard deviation, and t-test (Dependent). The results showed that 1) The student with learning using STEM Education plan have score of critical think and problem solving skills on post-test higher than pre-test with statistically significant level .01. 2) The student with learning using STEM Education plan have achievement score on post-test higher than pre-test with statistically significant level of .01. 3) The student'level of satisfaction toward the learning by using STEM Education plan was at a high level (X ¯ = 4.51, S.D=0.56).

Statistics Clinic

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Foy, Millennia; Ploutz-Snyder, Robert; Fiedler, James

2014-01-01

Do you have elevated p-values? Is the data analysis process getting you down? Do you experience anxiety when you need to respond to criticism of statistical methods in your manuscript? You may be suffering from Insufficient Statistical Support Syndrome (ISSS). For symptomatic relief of ISSS, come for a free consultation with JSC biostatisticians at our help desk during the poster sessions at the HRP Investigators Workshop. Get answers to common questions about sample size, missing data, multiple testing, when to trust the results of your analyses and more. Side effects may include sudden loss of statistics anxiety, improved interpretation of your data, and increased confidence in your results.

A MULTIPLE TESTING OF THE ABC METHOD AND THE DEVELOPMENT OF A SECOND-GENERATION MODEL. PART II, TEST RESULTS AND AN ANALYSIS OF RECALL RATIO.

ERIC Educational Resources Information Center

ALTMANN, BERTHOLD

AFTER A BRIEF SUMMARY OF THE TEST PROGRAM (DESCRIBED MORE FULLY IN LI 000 318), THE STATISTICAL RESULTS TABULATED AS OVERALL "ABC (APPROACH BY CONCEPT)-RELEVANCE RATIOS" AND "ABC-RECALL FIGURES" ARE PRESENTED AND REVIEWED. AN ABSTRACT MODEL DEVELOPED IN ACCORDANCE WITH MAX WEBER'S "IDEALTYPUS" ("DIE OBJEKTIVITAET…

The Design and Development of a Context-Rich, Photo-Based Online Testing to Assess Students' Science Learning

ERIC Educational Resources Information Center

Lin, Min-Jin; Guo, Chorng-Jee; Hsu, Chia-Er

2011-01-01

This study designed and developed a CP-MCT (content-rich, photo-based multiple choice online test) to assess whether college students can apply the basic light concept to interpret daily light phenomena. One hundred college students volunteered to take the CP-MCT, and the results were statistically analyzed by applying t-test or ANOVA (Analysis of…

Statistical analysis of the electrocatalytic activity of Pt nanoparticles supported on novel functionalized reduced graphene oxide-chitosan for methanol electrooxidation

NASA Astrophysics Data System (ADS)

Ekrami-Kakhki, Mehri-Saddat; Abbasi, Sedigheh; Farzaneh, Nahid

2018-01-01

The purpose of this study is to statistically analyze the anodic current density and peak potential of methanol oxidation at Pt nanoparticles supported on functionalized reduced graphene oxide (RGO), using design of experiments methodology. RGO is functionalized with methyl viologen (MV) and chitosan (CH). The novel Pt/MV-RGO-CH catalyst is successfully prepared and characterized with transmission electron microscopy (TEM) image. The electrocatalytic activity of Pt/MV-RGOCH catalyst is experimentally evaluated for methanol oxidation. The effects of methanol concentration and scan rate factors are also investigated experimentally and statistically. The effects of these two main factors and their interactions are investigated, using analysis of variance test, Duncan's multiple range test and response surface method. The results of the analysis of variance show that all the main factors and their interactions have a significant effect on anodic current density and peak potential of methanol oxidation at α = 0.05. The suggested models which encompass significant factors can predict the variation of the anodic current density and peak potential of methanol oxidation. The results of Duncan's multiple range test confirmed that there is a significant difference between the studied levels of the main factors. [Figure not available: see fulltext.

English Placement Testing, Multiple Measures, and Disproportionate Impact: An Analysis of the Criterion- and Content-Related Validity Evidence for the Reading & Writing Placement Tests in the San Diego Community College District.

ERIC Educational Resources Information Center

Armstrong, William B.

As part of an effort to statistically validate the placement tests used in California's San Diego Community College District (SDCCD) a study was undertaken to review the criteria- and content-related validity of the Assessment and Placement Services (APS) reading and writing tests. Evidence of criteria and content validity was gathered from…

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

PubMed

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.

Determination of Type I Error Rates and Power of Answer Copying Indices under Various Conditions

ERIC Educational Resources Information Center

Yormaz, Seha; Sünbül, Önder

2017-01-01

This study aims to determine the Type I error rates and power of S[subscript 1] , S[subscript 2] indices and kappa statistic at detecting copying on multiple-choice tests under various conditions. It also aims to determine how copying groups are created in order to calculate how kappa statistics affect Type I error rates and power. In this study,…

On the Optimality of Answer-Copying Indices: Theory and Practice

ERIC Educational Resources Information Center

Romero, Mauricio; Riascos, Álvaro; Jara, Diego

2015-01-01

Multiple-choice exams are frequently used as an efficient and objective method to assess learning, but they are more vulnerable to answer copying than tests based on open questions. Several statistical tests (known as indices in the literature) have been proposed to detect cheating; however, to the best of our knowledge, they all lack mathematical…

Fusion And Inference From Multiple And Massive Disparate Distributed Dynamic Data Sets

DTIC Science & Technology

2017-07-01

principled methodology for two-sample graph testing; designed a provably almost-surely perfect vertex clustering algorithm for block model graphs; proved...3.7 Semi-Supervised Clustering Methodology ...................................................................... 9 3.8 Robust Hypothesis Testing...dimensional Euclidean space – allows the full arsenal of statistical and machine learning methodology for multivariate Euclidean data to be deployed for

Testing and Evaluating C3I Systems That Employ AI. Volume 1. Handbook for Testing Expert Systems

DTIC Science & Technology

1991-01-31

Designs ....... ............. .. 6-29 Nonequivalent Control Group Design ...does not receive the system; and (c) nonequivalent (and nonrandomized) control group designs that rely on statistical techniques like analysis of...implementation); (b) multiple time-series designs using a control group ; and (c) nonequivalent control group designs that obtain pretest and

A twelve-year profile of students' SAT scores, GPAs, and MCAT scores from a small university's premedical program.

PubMed

Montague, J R; Frei, J K

1993-04-01

To determine whether significant correlations existed among quantitative and qualitative predictors of students' academic success and quantitative outcomes of such success over a 12-year period in a small university's premedical program. A database was assembled from information on the 199 graduates who earned BS degrees in biology from Barry University's School of Natural and Health Sciences from 1980 through 1991. The quantitative variables were year of BS degree, total score on the Scholastic Aptitude Test (SAT), various measures of undergraduate grade-point averages (GPAs), and total score on the Medical College Admission Test (MCAT); and the qualitative variables were minority (54% of the students) or majority status and transfer (about one-third of the students) or nontransfer status. The statistical methods were multiple analysis of variance and stepwise multiple regression. Statistically significant positive correlations were found among SAT total scores, final GPAs, biology GPAs versus nonbiology GPAs, and MCAT total scores. These correlations held for transfer versus nontransfer students and for minority versus majority students. Over the 12-year period there were significant fluctuations in mean MCAT scores. The students' SAT scores and GPAs proved to be statistically reliable predictors of MCAT scores, but the minority or majority status and the transfer or nontransfer status of the students were statistically insignificant.

Balance exercise for persons with multiple sclerosis using Wii games: a randomised, controlled multi-centre study.

PubMed

Nilsagård, Ylva E; Forsberg, Anette S; von Koch, Lena

2013-02-01

The use of interactive video games is expanding within rehabilitation. The evidence base is, however, limited. Our aim was to evaluate the effects of a Nintendo Wii Fit® balance exercise programme on balance function and walking ability in people with multiple sclerosis (MS). A multi-centre, randomised, controlled single-blinded trial with random allocation to exercise or no exercise. The exercise group participated in a programme of 12 supervised 30-min sessions of balance exercises using Wii games, twice a week for 6-7 weeks. Primary outcome was the Timed Up and Go test (TUG). In total, 84 participants were enrolled; four were lost to follow-up. After the intervention, there were no statistically significant differences between groups but effect sizes for the TUG, TUGcognitive and, the Dynamic Gait Index (DGI) were moderate and small for all other measures. Statistically significant improvements within the exercise group were present for all measures (large to moderate effect sizes) except in walking speed and balance confidence. The non-exercise group showed statistically significant improvements for the Four Square Step Test and the DGI. In comparison with no intervention, a programme of supervised balance exercise using Nintendo Wii Fit® did not render statistically significant differences, but presented moderate effect sizes for several measures of balance performance.

GPUs for statistical data analysis in HEP: a performance study of GooFit on GPUs vs. RooFit on CPUs

NASA Astrophysics Data System (ADS)

Pompili, Alexis; Di Florio, Adriano; CMS Collaboration

2016-10-01

In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the Jψϕ invariant mass in the three-body decay B +→JψϕK +. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerably resulting speed-up, while comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may apply or does not apply because its regularity conditions are not satisfied.

Statistical significance estimation of a signal within the GooFit framework on GPUs

NASA Astrophysics Data System (ADS)

Cristella, Leonardo; Di Florio, Adriano; Pompili, Alexis

2017-03-01

In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B+ → J/ψϕK+. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

Performance studies of GooFit on GPUs vs RooFit on CPUs while estimating the statistical significance of a new physical signal

NASA Astrophysics Data System (ADS)

Di Florio, Adriano

2017-10-01

In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B + → J/ψϕK +. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

Society of Thoracic Surgeons 2008 cardiac risk models predict in-hospital mortality of heart valve surgery in a Chinese population: a multicenter study.

PubMed

Wang, Lv; Lu, Fang-Lin; Wang, Chong; Tan, Meng-Wei; Xu, Zhi-yun

2014-12-01

The Society of Thoracic Surgeons 2008 cardiac surgery risk models have been developed for heart valve surgery with and without coronary artery bypass grafting. The aim of our study was to evaluate the performance of Society of Thoracic Surgeons 2008 cardiac risk models in Chinese patients undergoing single valve surgery and the predicted mortality rates of those undergoing multiple valve surgery derived from the Society of Thoracic Surgeons 2008 risk models. A total of 12,170 patients underwent heart valve surgery from January 2008 to December 2011. Combined congenital heart surgery and aortal surgery cases were excluded. A relatively small number of valve surgery combinations were excluded. The final research population included the following isolated heart valve surgery types: aortic valve replacement, mitral valve replacement, and mitral valve repair. The following combined valve surgery types were included: mitral valve replacement plus tricuspid valve repair, mitral valve replacement plus aortic valve replacement, and mitral valve replacement plus aortic valve replacement and tricuspid valve repair. Evaluation was performed by using the Hosmer-Lemeshow test and C-statistics. Data from 9846 patients were analyzed. The Society of Thoracic Surgeons 2008 cardiac risk models showed reasonable discrimination and poor calibration (C-statistic, 0.712; P = .00006 in Hosmer-Lemeshow test). Society of Thoracic Surgeons 2008 models had better discrimination (C-statistic, 0.734) and calibration (P = .5805) in patients undergoing isolated valve surgery than in patients undergoing multiple valve surgery (C-statistic, 0.694; P = .00002 in Hosmer-Lemeshow test). Estimates derived from the Society of Thoracic Surgeons 2008 models exceeded the mortality rates of multiple valve surgery (observed/expected ratios of 1.44 for multiple valve surgery and 1.17 for single valve surgery). The Society of Thoracic Surgeons 2008 cardiac surgery risk models performed well when predicting the mortality for Chinese patients undergoing valve surgery. The Society of Thoracic Surgeons 2008 models were suitable for single valve surgery in a Chinese population; estimates of mortality for multiple valve surgery derived from the Society of Thoracic Surgeons 2008 models were less accurate. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Preliminary criteria for the definition of allergic rhinitis: a systematic evaluation of clinical parameters in a disease cohort (I).

PubMed

Ng, M L; Warlow, R S; Chrishanthan, N; Ellis, C; Walls, R

2000-09-01

The aim of this study is to formulate criteria for the definition of allergic rhinitis. Other studies have sought to develop scoring systems to categorize the severity of allergic rhinitis symptoms but it was never used for the formulation of diagnostic criteria. These other scoring systems were arbitrarily chosen and were not derived by any statistical analysis. To date, a study of this kind has not been performed. The hypothesis of this study is that it is possible to formulate criteria for the definition of allergic rhinitis. This is the first study to systematically examine and evaluate the relative importance of symptoms, signs and investigative tests in allergic rhinitis. We sought to statistically rank, from the most to the least important, the multiplicity of symptoms, signs and test results. Forty-seven allergic rhinitis and 23 normal subjects were evaluated with a detailed questionnaire and history, physical examination, serum total immunoglobulin E, skin prick tests and serum enzyme allergosorbent tests (EAST). Statistical ranking of variables indicated rhinitis symptoms (nasal, ocular and oronasal) were the most commonly occurring, followed by a history of allergen provocation, then serum total IgE, positive skin prick tests and positive EAST's to house dust mite, perennial rye and bermuda/couch grass. Throat symptoms ranked even lower whilst EAST's to cat epithelia, plantain and cockroach were the least important. Not all symptoms, signs and tests evaluated proved to be statistically significant when compared to a control group; this included symtoms and signs which had been considered historically to be traditionally associated with allergic rhinitis, e.g. sore throat and bleeding nose. In performing statistical analyses, we were able to rank from most to least important, the multiplicity of symptoms signs and test results. The most important symptoms and signs were identified for the first time, even though some of these were not included in our original selection criteria for defining the disease cohort i.e. sniffing, postnasal drip, oedematous nasal mucosa, impaired sense of smell, mouth breathing, itchy nose and many of the specific provocation factors.

An introduction to multiplicity issues in clinical trials: the what, why, when and how.

PubMed

Li, Guowei; Taljaard, Monica; Van den Heuvel, Edwin R; Levine, Mitchell Ah; Cook, Deborah J; Wells, George A; Devereaux, Philip J; Thabane, Lehana

2017-04-01

In clinical trials it is not uncommon to face a multiple testing problem which can have an impact on both type I and type II error rates, leading to inappropriate interpretation of trial results. Multiplicity issues may need to be considered at the design, analysis and interpretation stages of a trial. The proportion of trial reports not adequately correcting for multiple testing remains substantial. The purpose of this article is to provide an introduction to multiple testing issues in clinical trials, and to reduce confusion around the need for multiplicity adjustments. We use a tutorial, question-and-answer approach to address the key issues of why, when and how to consider multiplicity adjustments in trials. We summarize the relevant circumstances under which multiplicity adjustments ought to be considered, as well as options for carrying out multiplicity adjustments in terms of trial design factors including Population, Intervention/Comparison, Outcome, Time frame and Analysis (PICOTA). Results are presented in an easy-to-use table and flow diagrams. Confusion about multiplicity issues can be reduced or avoided by considering the potential impact of multiplicity on type I and II errors and, if necessary pre-specifying statistical approaches to either avoid or adjust for multiplicity in the trial protocol or analysis plan. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Fisher's method of combining dependent statistics using generalizations of the gamma distribution with applications to genetic pleiotropic associations.

PubMed

Li, Qizhai; Hu, Jiyuan; Ding, Juan; Zheng, Gang

2014-04-01

A classical approach to combine independent test statistics is Fisher's combination of $p$-values, which follows the $\\chi ^2$ distribution. When the test statistics are dependent, the gamma distribution (GD) is commonly used for the Fisher's combination test (FCT). We propose to use two generalizations of the GD: the generalized and the exponentiated GDs. We study some properties of mis-using the GD for the FCT to combine dependent statistics when one of the two proposed distributions are true. Our results show that both generalizations have better control of type I error rates than the GD, which tends to have inflated type I error rates at more extreme tails. In practice, common model selection criteria (e.g. Akaike information criterion/Bayesian information criterion) can be used to help select a better distribution to use for the FCT. A simple strategy of the two generalizations of the GD in genome-wide association studies is discussed. Applications of the results to genetic pleiotrophic associations are described, where multiple traits are tested for association with a single marker.

Robust inference for group sequential trials.

PubMed

Ganju, Jitendra; Lin, Yunzhi; Zhou, Kefei

2017-03-01

For ethical reasons, group sequential trials were introduced to allow trials to stop early in the event of extreme results. Endpoints in such trials are usually mortality or irreversible morbidity. For a given endpoint, the norm is to use a single test statistic and to use that same statistic for each analysis. This approach is risky because the test statistic has to be specified before the study is unblinded, and there is loss in power if the assumptions that ensure optimality for each analysis are not met. To minimize the risk of moderate to substantial loss in power due to a suboptimal choice of a statistic, a robust method was developed for nonsequential trials. The concept is analogous to diversification of financial investments to minimize risk. The method is based on combining P values from multiple test statistics for formal inference while controlling the type I error rate at its designated value.This article evaluates the performance of 2 P value combining methods for group sequential trials. The emphasis is on time to event trials although results from less complex trials are also included. The gain or loss in power with the combination method relative to a single statistic is asymmetric in its favor. Depending on the power of each individual test, the combination method can give more power than any single test or give power that is closer to the test with the most power. The versatility of the method is that it can combine P values from different test statistics for analysis at different times. The robustness of results suggests that inference from group sequential trials can be strengthened with the use of combined tests. Copyright © 2017 John Wiley & Sons, Ltd.

Data-driven inference for the spatial scan statistic.

PubMed

Almeida, Alexandre C L; Duarte, Anderson R; Duczmal, Luiz H; Oliveira, Fernando L P; Takahashi, Ricardo H C

2011-08-02

Kulldorff's spatial scan statistic for aggregated area maps searches for clusters of cases without specifying their size (number of areas) or geographic location in advance. Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not done in an even manner for all possible cluster sizes. A modification is proposed to the usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster found. A new interpretation of the results of the spatial scan statistic is done, posing a modified inference question: what is the probability that the null hypothesis is rejected for the original observed cases map with a most likely cluster of size k, taking into account only those most likely clusters of size k found under null hypothesis for comparison? This question is especially important when the p-value computed by the usual inference process is near the alpha significance level, regarding the correctness of the decision based in this inference. A practical procedure is provided to make more accurate inferences about the most likely cluster found by the spatial scan statistic.

Statistical prediction of space motion sickness

NASA Technical Reports Server (NTRS)

Reschke, Millard F.

1990-01-01

Studies designed to empirically examine the etiology of motion sickness to develop a foundation for enhancing its prediction are discussed. Topics addressed include early attempts to predict space motion sickness, multiple test data base that uses provocative and vestibular function tests, and data base subjects; reliability of provocative tests of motion sickness susceptibility; prediction of space motion sickness using linear discriminate analysis; and prediction of space motion sickness susceptibility using the logistic model.

Effects of Coaching on Standardized Admission Examinations. Revised Statistical Analyses of Data Gathered By Boston Regional Office of the Federal Trade Commission.

ERIC Educational Resources Information Center

Federal Trade Commission, Washington, DC. Bureau of Consumer Protection.

The effect of commercial coaching on Scholastic Aptitude Test (SAT) scores was analyzed, using 1974-1977 test results of 2,500 non-coached students and 1,568 enrollees in two coaching schools. (The Stanley H. Kaplan Educational Center, Inc., and the Test Preparation Center, Inc.). Multiple regression analysis was used to control for student…

General Framework for Meta-analysis of Rare Variants in Sequencing Association Studies

PubMed Central

Lee, Seunggeun; Teslovich, Tanya M.; Boehnke, Michael; Lin, Xihong

2013-01-01

We propose a general statistical framework for meta-analysis of gene- or region-based multimarker rare variant association tests in sequencing association studies. In genome-wide association studies, single-marker meta-analysis has been widely used to increase statistical power by combining results via regression coefficients and standard errors from different studies. In analysis of rare variants in sequencing studies, region-based multimarker tests are often used to increase power. We propose meta-analysis methods for commonly used gene- or region-based rare variants tests, such as burden tests and variance component tests. Because estimation of regression coefficients of individual rare variants is often unstable or not feasible, the proposed method avoids this difficulty by calculating score statistics instead that only require fitting the null model for each study and then aggregating these score statistics across studies. Our proposed meta-analysis rare variant association tests are conducted based on study-specific summary statistics, specifically score statistics for each variant and between-variant covariance-type (linkage disequilibrium) relationship statistics for each gene or region. The proposed methods are able to incorporate different levels of heterogeneity of genetic effects across studies and are applicable to meta-analysis of multiple ancestry groups. We show that the proposed methods are essentially as powerful as joint analysis by directly pooling individual level genotype data. We conduct extensive simulations to evaluate the performance of our methods by varying levels of heterogeneity across studies, and we apply the proposed methods to meta-analysis of rare variant effects in a multicohort study of the genetics of blood lipid levels. PMID:23768515

Evaluation of Evidence of Statistical Support and Corroboration of Subgroup Claims in Randomized Clinical Trials.

PubMed

Wallach, Joshua D; Sullivan, Patrick G; Trepanowski, John F; Sainani, Kristin L; Steyerberg, Ewout W; Ioannidis, John P A

2017-04-01

Many published randomized clinical trials (RCTs) make claims for subgroup differences. To evaluate how often subgroup claims reported in the abstracts of RCTs are actually supported by statistical evidence (P < .05 from an interaction test) and corroborated by subsequent RCTs and meta-analyses. This meta-epidemiological survey examines data sets of trials with at least 1 subgroup claim, including Subgroup Analysis of Trials Is Rarely Easy (SATIRE) articles and Discontinuation of Randomized Trials (DISCO) articles. We used Scopus (updated July 2016) to search for English-language articles citing each of the eligible index articles with at least 1 subgroup finding in the abstract. Articles with a subgroup claim in the abstract with or without evidence of statistical heterogeneity (P < .05 from an interaction test) in the text and articles attempting to corroborate the subgroup findings. Study characteristics of trials with at least 1 subgroup claim in the abstract were recorded. Two reviewers extracted the data necessary to calculate subgroup-level effect sizes, standard errors, and the P values for interaction. For individual RCTs and meta-analyses that attempted to corroborate the subgroup findings from the index articles, trial characteristics were extracted. Cochran Q test was used to reevaluate heterogeneity with the data from all available trials. The number of subgroup claims in the abstracts of RCTs, the number of subgroup claims in the abstracts of RCTs with statistical support (subgroup findings), and the number of subgroup findings corroborated by subsequent RCTs and meta-analyses. Sixty-four eligible RCTs made a total of 117 subgroup claims in their abstracts. Of these 117 claims, only 46 (39.3%) in 33 articles had evidence of statistically significant heterogeneity from a test for interaction. In addition, out of these 46 subgroup findings, only 16 (34.8%) ensured balance between randomization groups within the subgroups (eg, through stratified randomization), 13 (28.3%) entailed a prespecified subgroup analysis, and 1 (2.2%) was adjusted for multiple testing. Only 5 (10.9%) of the 46 subgroup findings had at least 1 subsequent pure corroboration attempt by a meta-analysis or an RCT. In all 5 cases, the corroboration attempts found no evidence of a statistically significant subgroup effect. In addition, all effect sizes from meta-analyses were attenuated toward the null. A minority of subgroup claims made in the abstracts of RCTs are supported by their own data (ie, a significant interaction effect). For those that have statistical support (P < .05 from an interaction test), most fail to meet other best practices for subgroup tests, including prespecification, stratified randomization, and adjustment for multiple testing. Attempts to corroborate statistically significant subgroup differences are rare; when done, the initially observed subgroup differences are not reproduced.

Does rational selection of training and test sets improve the outcome of QSAR modeling?

PubMed

Martin, Todd M; Harten, Paul; Young, Douglas M; Muratov, Eugene N; Golbraikh, Alexander; Zhu, Hao; Tropsha, Alexander

2012-10-22

Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods can divide data sets into training and test sets in an intelligent fashion. The purpose of this study was to determine whether rational division methods lead to more predictive models compared to random division. A special data splitting procedure was used to facilitate the comparison between random and rational division methods. For each toxicity end point, the overall data set was divided into a modeling set (80% of the overall set) and an external evaluation set (20% of the overall set) using random division. The modeling set was then subdivided into a training set (80% of the modeling set) and a test set (20% of the modeling set) using rational division methods and by using random division. The Kennard-Stone, minimal test set dissimilarity, and sphere exclusion algorithms were used as the rational division methods. The hierarchical clustering, random forest, and k-nearest neighbor (kNN) methods were used to develop QSAR models based on the training sets. For kNN QSAR, multiple training and test sets were generated, and multiple QSAR models were built. The results of this study indicate that models based on rational division methods generate better statistical results for the test sets than models based on random division, but the predictive power of both types of models are comparable.

The optimal hormonal replacement modality selection for multiple organ procurement from brain-dead organ donors

PubMed Central

Mi, Zhibao; Novitzky, Dimitri; Collins, Joseph F; Cooper, David KC

2015-01-01

The management of brain-dead organ donors is complex. The use of inotropic agents and replacement of depleted hormones (hormonal replacement therapy) is crucial for successful multiple organ procurement, yet the optimal hormonal replacement has not been identified, and the statistical adjustment to determine the best selection is not trivial. Traditional pair-wise comparisons between every pair of treatments, and multiple comparisons to all (MCA), are statistically conservative. Hsu’s multiple comparisons with the best (MCB) – adapted from the Dunnett’s multiple comparisons with control (MCC) – has been used for selecting the best treatment based on continuous variables. We selected the best hormonal replacement modality for successful multiple organ procurement using a two-step approach. First, we estimated the predicted margins by constructing generalized linear models (GLM) or generalized linear mixed models (GLMM), and then we applied the multiple comparison methods to identify the best hormonal replacement modality given that the testing of hormonal replacement modalities is independent. Based on 10-year data from the United Network for Organ Sharing (UNOS), among 16 hormonal replacement modalities, and using the 95% simultaneous confidence intervals, we found that the combination of thyroid hormone, a corticosteroid, antidiuretic hormone, and insulin was the best modality for multiple organ procurement for transplantation. PMID:25565890

Gram-Negative Bacterial Wound Infections

DTIC Science & Technology

2015-05-01

not statistically differ- ent from that of the control group . The levels (CFU/g) of bacteria in lung tissue correlated with the survival curves. The...median levels in the control and 2.5 mg/kg- treated groups were almost identical, at 9.04 and 9.07 log CFU/g, respectively. Figure 6B shows a decrease...Dunn’s multiple comparison test, found a statistically significant difference in bacterial burden when the control group was com- pared to animals

Pitfalls in interpretation of CT-values of RT-PCR in children with acute respiratory tract infections.

PubMed

Wishaupt, Jérôme O; Ploeg, Tjeerd van der; Smeets, Leo C; Groot, Ronald de; Versteegh, Florens G A; Hartwig, Nico G

2017-05-01

The relation between viral load and disease severity in childhood acute respiratory tract infections (ARI) is not fully understood. To assess the clinical relevance of the relation between viral load, determined by cycle threshold (CT) value of real-time reverse transcription-polymerase chain reaction assays and disease severity in children with single- and multiple viral ARI. 582 children with ARI were prospectively followed and tested for 15 viruses. Correlations were calculated between CT values and clinical parameters. In single viral ARI, statistically significant correlations were found between viral loads of Respiratory Syncytial Virus (RSV) and hospitalization and between viral loads of Human Coronavirus (HCoV) and a disease severity score. In multiple-viral ARI, statistically significant correlations between viral load and clinical parameters were found. In RSV-Rhinovirus (RV) multiple infections, a low viral load of RV was correlated with a high length of hospital stay and a high duration of extra oxygen use. The mean CT value for RV, HCoV and Parainfluenza virus was significantly lower in single- versus multiple infections. Although correlations between CT values and clinical parameters in patients with single and multiple viral infection were found, the clinical importance of these findings is limited because individual differences in host-, viral and laboratory factors complicate the interpretation of statistically significant findings. In multiple infections, viral load cannot be used to differentiate between disease causing virus and innocent bystanders. Copyright © 2017 Elsevier B.V. All rights reserved.

Statistical Significance for Hierarchical Clustering

PubMed Central

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Validation of the Fatigue Impact Scale in Hungarian patients with multiple sclerosis.

PubMed

Losonczi, Erika; Bencsik, Krisztina; Rajda, Cecília; Lencsés, Gyula; Török, Margit; Vécsei, László

2011-03-01

Fatigue is one of the most frequent complaints of patients with multiple sclerosis (MS). The Fatigue Impact Scale (FIS), one of the 30 available fatigue questionnaires, is commonly applied because it evaluates multidimensional aspects of fatigue. The main purposes of this study were to test the validity, test-retest reliability, and internal consistency of the Hungarian version of the FIS. One hundred and eleven MS patients and 85 healthy control (HC) subjects completed the FIS and the Beck Depression Inventory, a large majority of them on two occasions, 3 months apart. The total FIS score and subscale scores differed statistically between the MS patients and the HC subjects in both FIS sessions. In the test-retest reliability assessment, statistically, the intraclass correlation coefficients were high in both the MS and HC groups. Cronbach's alpha values were also notably high. The results of this study indicate that the FIS can be regarded as a valid and reliable scale with which to improve our understanding of the impact of fatigue on the health-related quality of life in MS patients without severe disability.

Accurate Modeling of Galaxy Clustering on Small Scales: Testing the Standard ΛCDM + Halo Model

NASA Astrophysics Data System (ADS)

Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron; Scoccimarro, Roman

2015-01-01

The large-scale distribution of galaxies can be explained fairly simply by assuming (i) a cosmological model, which determines the dark matter halo distribution, and (ii) a simple connection between galaxies and the halos they inhabit. This conceptually simple framework, called the halo model, has been remarkably successful at reproducing the clustering of galaxies on all scales, as observed in various galaxy redshift surveys. However, none of these previous studies have carefully modeled the systematics and thus truly tested the halo model in a statistically rigorous sense. We present a new accurate and fully numerical halo model framework and test it against clustering measurements from two luminosity samples of galaxies drawn from the SDSS DR7. We show that the simple ΛCDM cosmology + halo model is not able to simultaneously reproduce the galaxy projected correlation function and the group multiplicity function. In particular, the more luminous sample shows significant tension with theory. We discuss the implications of our findings and how this work paves the way for constraining galaxy formation by accurate simultaneous modeling of multiple galaxy clustering statistics.

Condenser: a statistical aggregation tool for multi-sample quantitative proteomic data from Matrix Science Mascot Distiller™.

PubMed

Knudsen, Anders Dahl; Bennike, Tue; Kjeldal, Henrik; Birkelund, Svend; Otzen, Daniel Erik; Stensballe, Allan

2014-05-30

We describe Condenser, a freely available, comprehensive open-source tool for merging multidimensional quantitative proteomics data from the Matrix Science Mascot Distiller Quantitation Toolbox into a common format ready for subsequent bioinformatic analysis. A number of different relative quantitation technologies, such as metabolic (15)N and amino acid stable isotope incorporation, label-free and chemical-label quantitation are supported. The program features multiple options for curative filtering of the quantified peptides, allowing the user to choose data quality thresholds appropriate for the current dataset, and ensure the quality of the calculated relative protein abundances. Condenser also features optional global normalization, peptide outlier removal, multiple testing and calculation of t-test statistics for highlighting and evaluating proteins with significantly altered relative protein abundances. Condenser provides an attractive addition to the gold-standard quantitative workflow of Mascot Distiller, allowing easy handling of larger multi-dimensional experiments. Source code, binaries, test data set and documentation are available at http://condenser.googlecode.com/. Copyright © 2014 Elsevier B.V. All rights reserved.

Imputation of Test Scores in the National Education Longitudinal Study of 1988 (NELS:88). Working Paper Series.

ERIC Educational Resources Information Center

Bokossa, Maxime C.; Huang, Gary G.

This report describes the imputation procedures used to deal with missing data in the National Education Longitudinal Study of 1988 (NELS:88), the only current National Center for Education Statistics (NCES) dataset that contains scores from cognitive tests given the same set of students at multiple time points. As is inevitable, cognitive test…

catcher: A Software Program to Detect Answer Copying in Multiple-Choice Tests Based on Nominal Response Model

ERIC Educational Resources Information Center

Kalender, Ilker

2012-01-01

catcher is a software program designed to compute the [omega] index, a common statistical index for the identification of collusions (cheating) among examinees taking an educational or psychological test. It requires (a) responses and (b) ability estimations of individuals, and (c) item parameters to make computations and outputs the results of…

Do You Catch Undersized Fish? Let's Go Fishing to Learn Some Important Concepts in Multiple Testing

ERIC Educational Resources Information Center

Zheng, Qiujie; Lu, Yonggang

2016-01-01

In the era of Big Data, because of diminishing cost of data collection and storage, a large number of statistical tests may even possibly be conducted all together by a high school student to seek for some "exciting" new scientific findings. In this article, we propose an interesting approach to introduce students to some important…

Statistics in biomedical laboratory and clinical science: applications, issues and pitfalls.

PubMed

Ludbrook, John

2008-01-01

This review is directed at biomedical scientists who want to gain a better understanding of statistics: what tests to use, when, and why. In my view, even during the planning stage of a study it is very important to seek the advice of a qualified biostatistician. When designing and analyzing a study, it is important to construct and test global hypotheses, rather than to make multiple tests on the data. If the latter cannot be avoided, it is essential to control the risk of making false-positive inferences by applying multiple comparison procedures. For comparing two means or two proportions, it is best to use exact permutation tests rather then the better known, classical, ones. For comparing many means, analysis of variance, often of a complex type, is the most powerful approach. The correlation coefficient should never be used to compare the performances of two methods of measurement, or two measures, because it does not detect bias. Instead the Altman-Bland method of differences or least-products linear regression analysis should be preferred. Finally, the educational value to investigators of interaction with a biostatistician, before, during and after a study, cannot be overemphasized. (c) 2007 S. Karger AG, Basel.

Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

NASA Technical Reports Server (NTRS)

Kenny, R. Jeremy; Lee, Erik; Hulka, James R.; Casiano, Matthew

2011-01-01

The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response's frequency over the test duration. This characterization process assists in evaluating the discreteness of a signal as well as the stability of the chamber response. Broadband stability was assessed using a running root-mean-square evaluation. These techniques were also employed, in a comparative analysis, on available Fastrac data, and these results are presented here.

Bon-EV: an improved multiple testing procedure for controlling false discovery rates.

PubMed

Li, Dongmei; Xie, Zidian; Zand, Martin; Fogg, Thomas; Dye, Timothy

2017-01-03

Stability of multiple testing procedures, defined as the standard deviation of total number of discoveries, can be used as an indicator of variability of multiple testing procedures. Improving stability of multiple testing procedures can help to increase the consistency of findings from replicated experiments. Benjamini-Hochberg's and Storey's q-value procedures are two commonly used multiple testing procedures for controlling false discoveries in genomic studies. Storey's q-value procedure has higher power and lower stability than Benjamini-Hochberg's procedure. To improve upon the stability of Storey's q-value procedure and maintain its high power in genomic data analysis, we propose a new multiple testing procedure, named Bon-EV, to control false discovery rate (FDR) based on Bonferroni's approach. Simulation studies show that our proposed Bon-EV procedure can maintain the high power of the Storey's q-value procedure and also result in better FDR control and higher stability than Storey's q-value procedure for samples of large size(30 in each group) and medium size (15 in each group) for either independent, somewhat correlated, or highly correlated test statistics. When sample size is small (5 in each group), our proposed Bon-EV procedure has performance between the Benjamini-Hochberg procedure and the Storey's q-value procedure. Examples using RNA-Seq data show that the Bon-EV procedure has higher stability than the Storey's q-value procedure while maintaining equivalent power, and higher power than the Benjamini-Hochberg's procedure. For medium or large sample sizes, the Bon-EV procedure has improved FDR control and stability compared with the Storey's q-value procedure and improved power compared with the Benjamini-Hochberg procedure. The Bon-EV multiple testing procedure is available as the BonEV package in R for download at https://CRAN.R-project.org/package=BonEV .

A fast algorithm for determining bounds and accurate approximate p-values of the rank product statistic for replicate experiments.

PubMed

Heskes, Tom; Eisinga, Rob; Breitling, Rainer

2014-11-21

The rank product method is a powerful statistical technique for identifying differentially expressed molecules in replicated experiments. A critical issue in molecule selection is accurate calculation of the p-value of the rank product statistic to adequately address multiple testing. Both exact calculation and permutation and gamma approximations have been proposed to determine molecule-level significance. These current approaches have serious drawbacks as they are either computationally burdensome or provide inaccurate estimates in the tail of the p-value distribution. We derive strict lower and upper bounds to the exact p-value along with an accurate approximation that can be used to assess the significance of the rank product statistic in a computationally fast manner. The bounds and the proposed approximation are shown to provide far better accuracy over existing approximate methods in determining tail probabilities, with the slightly conservative upper bound protecting against false positives. We illustrate the proposed method in the context of a recently published analysis on transcriptomic profiling performed in blood. We provide a method to determine upper bounds and accurate approximate p-values of the rank product statistic. The proposed algorithm provides an order of magnitude increase in throughput as compared with current approaches and offers the opportunity to explore new application domains with even larger multiple testing issue. The R code is published in one of the Additional files and is available at http://www.ru.nl/publish/pages/726696/rankprodbounds.zip .

The issue of multiple univariate comparisons in the context of neuroelectric brain mapping: an application in a neuromarketing experiment.

PubMed

Vecchiato, G; De Vico Fallani, F; Astolfi, L; Toppi, J; Cincotti, F; Mattia, D; Salinari, S; Babiloni, F

2010-08-30

This paper presents some considerations about the use of adequate statistical techniques in the framework of the neuroelectromagnetic brain mapping. With the use of advanced EEG/MEG recording setup involving hundred of sensors, the issue of the protection against the type I errors that could occur during the execution of hundred of univariate statistical tests, has gained interest. In the present experiment, we investigated the EEG signals from a mannequin acting as an experimental subject. Data have been collected while performing a neuromarketing experiment and analyzed with state of the art computational tools adopted in specialized literature. Results showed that electric data from the mannequin's head presents statistical significant differences in power spectra during the visualization of a commercial advertising when compared to the power spectra gathered during a documentary, when no adjustments were made on the alpha level of the multiple univariate tests performed. The use of the Bonferroni or Bonferroni-Holm adjustments returned correctly no differences between the signals gathered from the mannequin in the two experimental conditions. An partial sample of recently published literature on different neuroscience journals suggested that at least the 30% of the papers do not use statistical protection for the type I errors. While the occurrence of type I errors could be easily managed with appropriate statistical techniques, the use of such techniques is still not so largely adopted in the literature. Copyright (c) 2010 Elsevier B.V. All rights reserved.

A model for multiple-drop-impact erosion of brittle solids

NASA Technical Reports Server (NTRS)

Engel, O. G.

1971-01-01

A statistical model for the multiple-drop-impact erosion of brittle solids was developed. An equation for calculating the rate of erosion is given. The development is not complete since two quantities that are needed to calculate the rate of erosion with use of the equation must be assessed from experimental data. A partial test of the equation shows that it gives results that are in good agreement with experimental observation.

MODELING A MIXTURE: PBPK/PD APPROACHES FOR PREDICTING CHEMICAL INTERACTIONS.

EPA Science Inventory

Since environmental chemical exposures generally involve multiple chemicals, there are both regulatory and scientific drivers to develop methods to predict outcomes of these exposures. Even using efficient statistical and experimental designs, it is not possible to test in vivo a...

Estimating Required Contingency Funds for Construction Projects using Multiple Linear Regression

DTIC Science & Technology

2006-03-01

Breusch - Pagan test , in which the null hypothesis states that the residuals have constant variance. The alternate hypothesis is that the residuals do not...variance, the Breusch - Pagan test provides statistical evidence that the assumption is justified. For the proposed model, the p-value is 0.173...entire test sample. v Acknowledgments First, I would like to acknowledge the influence and help of Greg Hoffman. His work served as the

Performance of fuselage pressure structure

NASA Technical Reports Server (NTRS)

Maclin, James R.

1992-01-01

There are currently more than 1,000 Boeing airplanes around the world over 20 years old. That number is expected to double by the year 1995. With these statistics comes the reality that structural airworthiness will be in the forefront of aviation issues well into the next century. The results of previous and recent test programs Boeing has implemented to study the structural performance of older airplanes relative to pressurized fuselage sections are described. Included in testing were flat panels with multiple site damage (MSD), a full-scale 737 and 2 747s as well as panels representing a 737 and 777, and a generic aircraft in large pressure-test fixtures. Because damage is a normal part of aging, focus is on the degree to which structural integrity is maintained after failure or partial failure of any structural element, including multiple site damage (MSD), and multiple element damage (MED).

Methods for meta-analysis of multiple traits using GWAS summary statistics.

PubMed

Ray, Debashree; Boehnke, Michael

2018-03-01

Genome-wide association studies (GWAS) for complex diseases have focused primarily on single-trait analyses for disease status and disease-related quantitative traits. For example, GWAS on risk factors for coronary artery disease analyze genetic associations of plasma lipids such as total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycerides (TGs) separately. However, traits are often correlated and a joint analysis may yield increased statistical power for association over multiple univariate analyses. Recently several multivariate methods have been proposed that require individual-level data. Here, we develop metaUSAT (where USAT is unified score-based association test), a novel unified association test of a single genetic variant with multiple traits that uses only summary statistics from existing GWAS. Although the existing methods either perform well when most correlated traits are affected by the genetic variant in the same direction or are powerful when only a few of the correlated traits are associated, metaUSAT is designed to be robust to the association structure of correlated traits. metaUSAT does not require individual-level data and can test genetic associations of categorical and/or continuous traits. One can also use metaUSAT to analyze a single trait over multiple studies, appropriately accounting for overlapping samples, if any. metaUSAT provides an approximate asymptotic P-value for association and is computationally efficient for implementation at a genome-wide level. Simulation experiments show that metaUSAT maintains proper type-I error at low error levels. It has similar and sometimes greater power to detect association across a wide array of scenarios compared to existing methods, which are usually powerful for some specific association scenarios only. When applied to plasma lipids summary data from the METSIM and the T2D-GENES studies, metaUSAT detected genome-wide significant loci beyond the ones identified by univariate analyses. Evidence from larger studies suggest that the variants additionally detected by our test are, indeed, associated with lipid levels in humans. In summary, metaUSAT can provide novel insights into the genetic architecture of a common disease or traits. © 2017 WILEY PERIODICALS, INC.

The Effects of Statistical Multiplicity of Infection on Virus Quantification and Infectivity Assays.

PubMed

Mistry, Bhaven A; D'Orsogna, Maria R; Chou, Tom

2018-06-19

Many biological assays are employed in virology to quantify parameters of interest. Two such classes of assays, virus quantification assays (VQAs) and infectivity assays (IAs), aim to estimate the number of viruses present in a solution and the ability of a viral strain to successfully infect a host cell, respectively. VQAs operate at extremely dilute concentrations, and results can be subject to stochastic variability in virus-cell interactions. At the other extreme, high viral-particle concentrations are used in IAs, resulting in large numbers of viruses infecting each cell, enough for measurable change in total transcription activity. Furthermore, host cells can be infected at any concentration regime by multiple particles, resulting in a statistical multiplicity of infection and yielding potentially significant variability in the assay signal and parameter estimates. We develop probabilistic models for statistical multiplicity of infection at low and high viral-particle-concentration limits and apply them to the plaque (VQA), endpoint dilution (VQA), and luciferase reporter (IA) assays. A web-based tool implementing our models and analysis is also developed and presented. We test our proposed new methods for inferring experimental parameters from data using numerical simulations and show improvement on existing procedures in all limits. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Comparison of the effect of multiple intelligence pedagogy and traditional pedagogy on grade 5 students' achievement and attitudes towards science

NASA Astrophysics Data System (ADS)

Mussen, Kimberly S.

This quantitative research study evaluated the effectiveness of employing pedagogy based on the theory of multiple intelligences (MI). Currently, not all students are performing at the rate mandated by the government. When schools do not meet the required state standards, the school is labeled as not achieving adequate yearly progress (AYP), which may lead to the loss of funding. Any school not achieving AYP would be interested in this study. Due to low state standardized test scores in the district for science, student achievement and attitudes towards learning science were evaluated on a pretest, posttest, essay question, and one attitudinal survey. Statistical significance existed on one of the four research questions. Utilizing the Analysis of Covariance (ANCOVA) for data analysis, student attitudes towards learning science were statically significant in the MI (experimental) group. No statistical significance was found in student achievement on the posttest, delayed posttest, or the essay question test. Social change can result from this study because studying the effects of the multiple intelligence theory incorporated into classroom instruction can have significant effect on how children learn, allowing them to compete in a knowledge society.

Improving Clinical Trial Efficiency: Thinking outside the Box.

PubMed

Mandrekar, Sumithra J; Dahlberg, Suzanne E; Simon, Richard

2015-01-01

Clinical trial design strategies have evolved over the past few years as a means to accelerate the drug development process so that the right therapies can be delivered to the right patients. Basket, umbrella, and adaptive enrichment strategies represent a class of novel designs for testing targeted therapeutics in oncology. Umbrella trials include a central infrastructure for screening and identification of patients, and focus on a single tumor type or histology with multiple subtrials, each testing a targeted therapy within a molecularly defined subset. Basket trial designs offer the possibility to include multiple molecularly defined subpopulations, often across histology or tumor types, but included in one cohesive design to evaluate the targeted therapy in question. Adaptive enrichment designs offer the potential to enrich for patients with a particular molecular feature that is predictive of benefit for the test treatment based on accumulating evidence from the trial. This review will aim to discuss the fundamentals of these design strategies, the underlying statistical framework, the logistical barriers of implementation, and, ultimately, the interpretation of the trial results. New statistical approaches, extensive multidisciplinary collaboration, and state of the art data capture technologies are needed to implement these strategies in practice. Logistical challenges to implementation arising from centralized assay testing, requirement of multiple specimens, multidisciplinary collaboration, and infrastructure requirements will also be discussed. This review will present these concepts in the context of the National Cancer Institute's precision medicine initiative trials: MATCH, ALCHEMIST, Lung MAP, as well as other trials such as FOCUS4.

Rare Variant Association Test with Multiple Phenotypes

PubMed Central

Lee, Selyeong; Won, Sungho; Kim, Young Jin; Kim, Yongkang; Kim, Bong-Jo; Park, Taesung

2016-01-01

Although genome-wide association studies (GWAS) have now discovered thousands of genetic variants associated with common traits, such variants cannot explain the large degree of “missing heritability,” likely due to rare variants. The advent of next generation sequencing technology has allowed rare variant detection and association with common traits, often by investigating specific genomic regions for rare variant effects on a trait. Although multiply correlated phenotypes are often concurrently observed in GWAS, most studies analyze only single phenotypes, which may lessen statistical power. To increase power, multivariate analyses, which consider correlations between multiple phenotypes, can be used. However, few existing multi-variant analyses can identify rare variants for assessing multiple phenotypes. Here, we propose Multivariate Association Analysis using Score Statistics (MAAUSS), to identify rare variants associated with multiple phenotypes, based on the widely used Sequence Kernel Association Test (SKAT) for a single phenotype. We applied MAAUSS to Whole Exome Sequencing (WES) data from a Korean population of 1,058 subjects, to discover genes associated with multiple traits of liver function. We then assessed validation of those genes by a replication study, using an independent dataset of 3,445 individuals. Notably, we detected the gene ZNF620 among five significant genes. We then performed a simulation study to compare MAAUSS's performance with existing methods. Overall, MAAUSS successfully conserved type 1 error rates and in many cases, had a higher power than the existing methods. This study illustrates a feasible and straightforward approach for identifying rare variants correlated with multiple phenotypes, with likely relevance to missing heritability. PMID:28039885

A Powerful Test for Comparing Multiple Regression Functions.

PubMed

Maity, Arnab

2012-09-01

In this article, we address the important problem of comparison of two or more population regression functions. Recently, Pardo-Fernández, Van Keilegom and González-Manteiga (2007) developed test statistics for simple nonparametric regression models: Y(ij) = θ(j)(Z(ij)) + σ(j)(Z(ij))∊(ij), based on empirical distributions of the errors in each population j = 1, … , J. In this paper, we propose a test for equality of the θ(j)(·) based on the concept of generalized likelihood ratio type statistics. We also generalize our test for other nonparametric regression setups, e.g, nonparametric logistic regression, where the loglikelihood for population j is any general smooth function [Formula: see text]. We describe a resampling procedure to obtain the critical values of the test. In addition, we present a simulation study to evaluate the performance of the proposed test and compare our results to those in Pardo-Fernández et al. (2007).

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

PubMed

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 updated information and newly added models.

Determining the lifetime of detectable amounts of gunshot residue on the hands of a shooter using laser-induced breakdown spectroscopy.

PubMed

Rosenberg, Matthew B; Dockery, Christopher R

2008-11-01

Laser-induced breakdown spectroscopy (LIBS) has been used to determine the period of time that a shooter will test positive for gunshot residue (GSR) after firing a revolver. Multiple rounds of primer were fired and samples collected at multiple hour intervals using an adhesive tape pressed against the skin. Samples were analyzed directly using a commercially available laser-induced breakdown spectrometer where barium emission (originating from barium nitrate in the primer) was observed. Population statistics were used to compare suspected GSR to a library of blank samples from which a threshold value was established. Statistically significant results, positive for GSR, are obtained 5.27 days after a firearm discharge using these techniques.

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

PubMed

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.

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

PubMed Central

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

2016-01-01

Motivation: 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. Results: 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. Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco Contacts: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153689

fMRI reliability: influences of task and experimental design.

PubMed

Bennett, Craig M; Miller, Michael B

2013-12-01

As scientists, it is imperative that we understand not only the power of our research tools to yield results, but also their ability to obtain similar results over time. This study is an investigation into how common decisions made during the design and analysis of a functional magnetic resonance imaging (fMRI) study can influence the reliability of the statistical results. To that end, we gathered back-to-back test-retest fMRI data during an experiment involving multiple cognitive tasks (episodic recognition and two-back working memory) and multiple fMRI experimental designs (block, event-related genetic sequence, and event-related m-sequence). Using these data, we were able to investigate the relative influences of task, design, statistical contrast (task vs. rest, target vs. nontarget), and statistical thresholding (unthresholded, thresholded) on fMRI reliability, as measured by the intraclass correlation (ICC) coefficient. We also utilized data from a second study to investigate test-retest reliability after an extended, six-month interval. We found that all of the factors above were statistically significant, but that they had varying levels of influence on the observed ICC values. We also found that these factors could interact, increasing or decreasing the relative reliability of certain Task × Design combinations. The results suggest that fMRI reliability is a complex construct whose value may be increased or decreased by specific combinations of factors.

Predicting Slag Generation in Sub-Scale Test Motors Using a Neural Network

NASA Technical Reports Server (NTRS)

Wiesenberg, Brent

1999-01-01

Generation of slag (aluminum oxide) is an important issue for the Reusable Solid Rocket Motor (RSRM). Thiokol performed testing to quantify the relationship between raw material variations and slag generation in solid propellants by testing sub-scale motors cast with propellant containing various combinations of aluminum fuel and ammonium perchlorate (AP) oxidizer particle sizes. The test data were analyzed using statistical methods and an artificial neural network. This paper primarily addresses the neural network results with some comparisons to the statistical results. The neural network showed that the particle sizes of both the aluminum and unground AP have a measurable effect on slag generation. The neural network analysis showed that aluminum particle size is the dominant driver in slag generation, about 40% more influential than AP. The network predictions of the amount of slag produced during firing of sub-scale motors were 16% better than the predictions of a statistically derived empirical equation. Another neural network successfully characterized the slag generated during full-scale motor tests. The success is attributable to the ability of neural networks to characterize multiple complex factors including interactions that affect slag generation.

Physical characteristics of experienced and junior open-wheel car drivers.

PubMed

Raschner, Christian; Platzer, Hans-Peter; Patterson, Carson

2013-01-01

Despite the popularity of open-wheel car racing, scientific literature about the physical characteristics of competitive race car drivers is scarce. The purpose of this study was to compare selected fitness parameters of experienced and junior open-wheel race car drivers. The experienced drivers consisted of five Formula One, two GP2 and two Formula 3 drivers, and the nine junior drivers drove in the Formula Master, Koenig, BMW and Renault series. The following fitness parameters were tested: multiple reactions, multiple anticipation, postural stability, isometric upper body strength, isometric leg extension strength, isometric grip strength, cyclic foot speed and jump height. The group differences were calculated using the Mann-Whitney U-test. Because of the multiple testing strategy used, the statistical significance was Bonferroni corrected and set at P < 0.004. Significant differences between the experienced and junior drivers were found only for the jump height parameter (P = 0.002). The experienced drivers tended to perform better in leg strength (P = 0.009), cyclic foot speed (P = 0.024) and grip strength (P = 0.058). None of the other variables differed between the groups. The results suggested that the experienced drivers were significantly more powerful than the junior drivers: they tended to be quicker and stronger (18% to 25%) but without statistical significance. The experienced drivers demonstrated excellent strength and power compared with other high-performance athletes.

Transitioning to multiple imputation : a new method to impute missing blood alcohol concentration (BAC) values in FARS

DOT National Transportation Integrated Search

2002-01-01

The National Center for Statistics and Analysis (NCSA) of the National Highway Traffic Safety : Administration (NHTSA) has undertaken several approaches to remedy the problem of missing blood alcohol : test results in the Fatality Analysis Reporting ...

Polymer Principles in the Undergraduate Physical Chemistry Course. Part 2.

ERIC Educational Resources Information Center

Journal of Chemical Education, 1985

1985-01-01

Part l (SE 538 305) covered application of classical thermodynamics, polymer crystallinity, and phase diagrams to teaching physical chemistry. This part covers statistical thermodynamics, conformation, molecular weights, rubber elasticity and viscoelasticity, and kinetics of polymerization. Eight polymer-oriented, multiple-choice test questions…

Controlling Guessing Bias in the Dichotomous Rasch Model Applied to a Large-Scale, Vertically Scaled Testing Program

ERIC Educational Resources Information Center

Andrich, David; Marais, Ida; Humphry, Stephen Mark

2016-01-01

Recent research has shown how the statistical bias in Rasch model difficulty estimates induced by guessing in multiple-choice items can be eliminated. Using vertical scaling of a high-profile national reading test, it is shown that the dominant effect of removing such bias is a nonlinear change in the unit of scale across the continuum. The…

Estimating the Proportion of True Null Hypotheses Using the Pattern of Observed p-values

PubMed Central

Tong, Tiejun; Feng, Zeny; Hilton, Julia S.; Zhao, Hongyu

2013-01-01

Estimating the proportion of true null hypotheses, π0, has attracted much attention in the recent statistical literature. Besides its apparent relevance for a set of specific scientific hypotheses, an accurate estimate of this parameter is key for many multiple testing procedures. Most existing methods for estimating π0 in the literature are motivated from the independence assumption of test statistics, which is often not true in reality. Simulations indicate that most existing estimators in the presence of the dependence among test statistics can be poor, mainly due to the increase of variation in these estimators. In this paper, we propose several data-driven methods for estimating π0 by incorporating the distribution pattern of the observed p-values as a practical approach to address potential dependence among test statistics. Specifically, we use a linear fit to give a data-driven estimate for the proportion of true-null p-values in (λ, 1] over the whole range [0, 1] instead of using the expected proportion at 1 − λ. We find that the proposed estimators may substantially decrease the variance of the estimated true null proportion and thus improve the overall performance. PMID:24078762

Estimating the Proportion of True Null Hypotheses Using the Pattern of Observed p-values.

PubMed

Tong, Tiejun; Feng, Zeny; Hilton, Julia S; Zhao, Hongyu

2013-01-01

Estimating the proportion of true null hypotheses, π 0 , has attracted much attention in the recent statistical literature. Besides its apparent relevance for a set of specific scientific hypotheses, an accurate estimate of this parameter is key for many multiple testing procedures. Most existing methods for estimating π 0 in the literature are motivated from the independence assumption of test statistics, which is often not true in reality. Simulations indicate that most existing estimators in the presence of the dependence among test statistics can be poor, mainly due to the increase of variation in these estimators. In this paper, we propose several data-driven methods for estimating π 0 by incorporating the distribution pattern of the observed p -values as a practical approach to address potential dependence among test statistics. Specifically, we use a linear fit to give a data-driven estimate for the proportion of true-null p -values in (λ, 1] over the whole range [0, 1] instead of using the expected proportion at 1 - λ. We find that the proposed estimators may substantially decrease the variance of the estimated true null proportion and thus improve the overall performance.

Neuromuscular taping versus sham therapy on muscular strength and motor performance in multiple sclerosis patients.

PubMed

Costantino, Cosimo; Pedrini, Martina Francesca; Licari, Oriana

2016-01-01

Purpose of this study is to evaluate differences in leg muscles strength and motor performance between neuromuscular taping (NT) and sham tape groups. Relapsing-remitting (RR) multiple sclerosis (MS) patients were recruited and randomly assigned to NT or sham tape groups. All patients underwent the treatment 5 times at 5-d intervals. They were submitted to a 6-minute walk test and isokinetic test (peak torque) at the beginning (T0), at the end (T1) and 2 months after the end of the treatment (T2). Forty MS patients (38 F; 2 M; mean age 45.5 ± 6.5 years) were assigned to NT group (n = 20) and to sham tape group (n = 20). Delta Peak Torque T1-T0 and T2-T0 between two groups were statistically significant in quadriceps (p = 0.007; 0.000) and hamstrings (p = 0.011; 0.007). The difference between the two groups according to 6-minute walk test was not statistically significant but in NT group it was noticed an increasing trend about the distance run. In this single-blind randomized controlled trial, NT seemed to increase strength in leg muscles, compared to a sham device, in RR MS patients. Further studies are needed to consider this therapy as a complement to classic physical therapy. Neuromuscular taping (NT) in multiple sclerosis: NT is well tolerated by multiple sclerosis patients and should be a complement to classic physical therapy. This technique normalizes muscular function, strengthens weakened muscles and assists the postural alignment.

An extended sequential goodness-of-fit multiple testing method for discrete data.

PubMed

Castro-Conde, Irene; Döhler, Sebastian; de Uña-Álvarez, Jacobo

2017-10-01

The sequential goodness-of-fit (SGoF) multiple testing method has recently been proposed as an alternative to the familywise error rate- and the false discovery rate-controlling procedures in high-dimensional problems. For discrete data, the SGoF method may be very conservative. In this paper, we introduce an alternative SGoF-type procedure that takes into account the discreteness of the test statistics. Like the original SGoF, our new method provides weak control of the false discovery rate/familywise error rate but attains false discovery rate levels closer to the desired nominal level, and thus it is more powerful. We study the performance of this method in a simulation study and illustrate its application to a real pharmacovigilance data set.

Integral criteria for large-scale multiple fingerprint solutions

NASA Astrophysics Data System (ADS)

Ushmaev, Oleg S.; Novikov, Sergey O.

2004-08-01

We propose the definition and analysis of the optimal integral similarity score criterion for large scale multmodal civil ID systems. Firstly, the general properties of score distributions for genuine and impostor matches for different systems and input devices are investigated. The empirical statistics was taken from the real biometric tests. Then we carry out the analysis of simultaneous score distributions for a number of combined biometric tests and primary for ultiple fingerprint solutions. The explicit and approximate relations for optimal integral score, which provides the least value of the FRR while the FAR is predefined, have been obtained. The results of real multiple fingerprint test show good correspondence with the theoretical results in the wide range of the False Acceptance and the False Rejection Rates.

Meteor trail footprint statistics

NASA Astrophysics Data System (ADS)

Mui, S. Y.; Ellicott, R. C.

Footprint statistics derived from field-test data are presented. The statistics are the probability that two receivers will lie in the same footprint. The dependence of the footprint statistics on the transmitter range, link orientation, and antenna polarization are examined. Empirical expressions for the footprint statistics are presented. The need to distinguish the instantaneous footprint, which is the area illuminated at a particular instant, from the composite footprint, which is the total area illuminated during the lifetime of the meteor trail, is explained. The statistics for the instantaneous and composite footprints have been found to be similar. The only significant difference lies in the parameter that represents the probability of two colocated receivers being in the same footprint. The composite footprint statistics can be used to calculate the space diversity gain of a multiple-receiver system. The instantaneous footprint statistics are useful in the evaluation of the interference probability in a network of meteor burst communication nodes.

Statistics for Radiology Research.

PubMed

Obuchowski, Nancy A; Subhas, Naveen; Polster, Joshua

2017-02-01

Biostatistics is an essential component in most original research studies in imaging. In this article we discuss five key statistical concepts for study design and analyses in modern imaging research: statistical hypothesis testing, particularly focusing on noninferiority studies; imaging outcomes especially when there is no reference standard; dealing with the multiplicity problem without spending all your study power; relevance of confidence intervals in reporting and interpreting study results; and finally tools for assessing quantitative imaging biomarkers. These concepts are presented first as examples of conversations between investigator and biostatistician, and then more detailed discussions of the statistical concepts follow. Three skeletal radiology examples are used to illustrate the concepts. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

A Residual Mass Ballistic Testing Method to Compare Armor Materials or Components (Residual Mass Ballistic Testing Method)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benjamin Langhorst; Thomas M Lillo; Henry S Chu

2014-05-01

A statistics based ballistic test method is presented for use when comparing multiple groups of test articles of unknown relative ballistic perforation resistance. The method is intended to be more efficient than many traditional methods for research and development testing. To establish the validity of the method, it is employed in this study to compare test groups of known relative ballistic performance. Multiple groups of test articles were perforated using consistent projectiles and impact conditions. Test groups were made of rolled homogeneous armor (RHA) plates and differed in thickness. After perforation, each residual projectile was captured behind the target andmore » its mass was measured. The residual masses measured for each test group were analyzed to provide ballistic performance rankings with associated confidence levels. When compared to traditional V50 methods, the residual mass (RM) method was found to require fewer test events and be more tolerant of variations in impact conditions.« less

Bayesian modelling of lung function data from multiple-breath washout tests.

PubMed

Mahar, Robert K; Carlin, John B; Ranganathan, Sarath; Ponsonby, Anne-Louise; Vuillermin, Peter; Vukcevic, Damjan

2018-05-30

Paediatric respiratory researchers have widely adopted the multiple-breath washout (MBW) test because it allows assessment of lung function in unsedated infants and is well suited to longitudinal studies of lung development and disease. However, a substantial proportion of MBW tests in infants fail current acceptability criteria. We hypothesised that a model-based approach to analysing the data, in place of traditional simple empirical summaries, would enable more efficient use of these tests. We therefore developed a novel statistical model for infant MBW data and applied it to 1197 tests from 432 individuals from a large birth cohort study. We focus on Bayesian estimation of the lung clearance index, the most commonly used summary of lung function from MBW tests. Our results show that the model provides an excellent fit to the data and shed further light on statistical properties of the standard empirical approach. Furthermore, the modelling approach enables the lung clearance index to be estimated by using tests with different degrees of completeness, something not possible with the standard approach. Our model therefore allows previously unused data to be used rather than discarded, as well as routine use of shorter tests without significant loss of precision. Beyond our specific application, our work illustrates a number of important aspects of Bayesian modelling in practice, such as the importance of hierarchical specifications to account for repeated measurements and the value of model checking via posterior predictive distributions. Copyright © 2018 John Wiley & Sons, Ltd.

Higher certainty of the laser-induced damage threshold test with a redistributing data treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jensen, Lars; Mrohs, Marius; Gyamfi, Mark

2015-10-15

As a consequence of its statistical nature, the measurement of the laser-induced damage threshold holds always risks to over- or underestimate the real threshold value. As one of the established measurement procedures, the results of S-on-1 (and 1-on-1) tests outlined in the corresponding ISO standard 21 254 depend on the amount of data points and their distribution over the fluence scale. With the limited space on a test sample as well as the requirements on test site separation and beam sizes, the amount of data from one test is restricted. This paper reports on a way to treat damage testmore » data in order to reduce the statistical error and therefore measurement uncertainty. Three simple assumptions allow for the assignment of one data point to multiple data bins and therefore virtually increase the available data base.« less

Significance tests for functional data with complex dependence structure.

PubMed

Staicu, Ana-Maria; Lahiri, Soumen N; Carroll, Raymond J

2015-01-01

We propose an L 2 -norm based global testing procedure for the null hypothesis that multiple group mean functions are equal, for functional data with complex dependence structure. Specifically, we consider the setting of functional data with a multilevel structure of the form groups-clusters or subjects-units, where the unit-level profiles are spatially correlated within the cluster, and the cluster-level data are independent. Orthogonal series expansions are used to approximate the group mean functions and the test statistic is estimated using the basis coefficients. The asymptotic null distribution of the test statistic is developed, under mild regularity conditions. To our knowledge this is the first work that studies hypothesis testing, when data have such complex multilevel functional and spatial structure. Two small-sample alternatives, including a novel block bootstrap for functional data, are proposed, and their performance is examined in simulation studies. The paper concludes with an illustration of a motivating experiment.

Equal Employment + Equal Pay = Multiple Problems for Colleges and Universities

ERIC Educational Resources Information Center

Steinbach, Sheldon Elliot; Reback, Joyce E.

1974-01-01

Issues involved in government regulation of university employment practices are discussed: confidentiality of records, pregnancy as a disability, alleged discrimination in benefits, tests and other employment criteria, seniority and layoff, reverse discrimination, use of statistics for determination of discrimination, and the Equal Pay Act. (JT)

Most Likely to Succeed: Exploring Predictor Variables for the Counselor Preparation Comprehensive Examination

ERIC Educational Resources Information Center

Hartwig, Elizabeth Kjellstrand; Van Overschelde, James P.

2016-01-01

The authors investigated predictor variables for the Counselor Preparation Comprehensive Examination (CPCE) to examine whether academic variables, demographic variables, and test version were associated with graduate counseling students' CPCE scores. Multiple regression analyses revealed all 3 variables were statistically significant predictors of…

Statistical and sampling issues when using multiple particle tracking

NASA Astrophysics Data System (ADS)

Savin, Thierry; Doyle, Patrick S.

2007-08-01

Video microscopy can be used to simultaneously track several microparticles embedded in a complex material. The trajectories are used to extract a sample of displacements at random locations in the material. From this sample, averaged quantities characterizing the dynamics of the probes are calculated to evaluate structural and/or mechanical properties of the assessed material. However, the sampling of measured displacements in heterogeneous systems is singular because the volume of observation with video microscopy is finite. By carefully characterizing the sampling design in the experimental output of the multiple particle tracking technique, we derive estimators for the mean and variance of the probes’ dynamics that are independent of the peculiar statistical characteristics. We expose stringent tests of these estimators using simulated and experimental complex systems with a known heterogeneous structure. Up to a certain fundamental limitation, which we characterize through a material degree of sampling by the embedded probe tracking, these estimators can be applied to quantify the heterogeneity of a material, providing an original and intelligible kind of information on complex fluid properties. More generally, we show that the precise assessment of the statistics in the multiple particle tracking output sample of observations is essential in order to provide accurate unbiased measurements.

Data Analysis Techniques for Physical Scientists

NASA Astrophysics Data System (ADS)

Pruneau, Claude A.

2017-10-01

Preface; How to read this book; 1. The scientific method; Part I. Foundation in Probability and Statistics: 2. Probability; 3. Probability models; 4. Classical inference I: estimators; 5. Classical inference II: optimization; 6. Classical inference III: confidence intervals and statistical tests; 7. Bayesian inference; Part II. Measurement Techniques: 8. Basic measurements; 9. Event reconstruction; 10. Correlation functions; 11. The multiple facets of correlation functions; 12. Data correction methods; Part III. Simulation Techniques: 13. Monte Carlo methods; 14. Collision and detector modeling; List of references; Index.

Testing multiple statistical hypotheses resulted in spurious associations: a study of astrological signs and health.

PubMed

Austin, Peter C; Mamdani, Muhammad M; Juurlink, David N; Hux, Janet E

2006-09-01

To illustrate how multiple hypotheses testing can produce associations with no clinical plausibility. We conducted a study of all 10,674,945 residents of Ontario aged between 18 and 100 years in 2000. Residents were randomly assigned to equally sized derivation and validation cohorts and classified according to their astrological sign. Using the derivation cohort, we searched through 223 of the most common diagnoses for hospitalization until we identified two for which subjects born under one astrological sign had a significantly higher probability of hospitalization compared to subjects born under the remaining signs combined (P<0.05). We tested these 24 associations in the independent validation cohort. Residents born under Leo had a higher probability of gastrointestinal hemorrhage (P=0.0447), while Sagittarians had a higher probability of humerus fracture (P=0.0123) compared to all other signs combined. After adjusting the significance level to account for multiple comparisons, none of the identified associations remained significant in either the derivation or validation cohort. Our analyses illustrate how the testing of multiple, non-prespecified hypotheses increases the likelihood of detecting implausible associations. Our findings have important implications for the analysis and interpretation of clinical studies.

Multicollinearity is a red herring in the search for moderator variables: A guide to interpreting moderated multiple regression models and a critique of Iacobucci, Schneider, Popovich, and Bakamitsos (2016).

PubMed

McClelland, Gary H; Irwin, Julie R; Disatnik, David; Sivan, Liron

2017-02-01

Multicollinearity is irrelevant to the search for moderator variables, contrary to the implications of Iacobucci, Schneider, Popovich, and Bakamitsos (Behavior Research Methods, 2016, this issue). Multicollinearity is like the red herring in a mystery novel that distracts the statistical detective from the pursuit of a true moderator relationship. We show multicollinearity is completely irrelevant for tests of moderator variables. Furthermore, readers of Iacobucci et al. might be confused by a number of their errors. We note those errors, but more positively, we describe a variety of methods researchers might use to test and interpret their moderated multiple regression models, including two-stage testing, mean-centering, spotlighting, orthogonalizing, and floodlighting without regard to putative issues of multicollinearity. We cite a number of recent studies in the psychological literature in which the researchers used these methods appropriately to test, to interpret, and to report their moderated multiple regression models. We conclude with a set of recommendations for the analysis and reporting of moderated multiple regression that should help researchers better understand their models and facilitate generalizations across studies.

Extending local canonical correlation analysis to handle general linear contrasts for FMRI data.

PubMed

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

PubMed Central

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic. PMID:22461786

Predicting future protection of respirator users: Statistical approaches and practical implications.

PubMed

Hu, Chengcheng; Harber, Philip; Su, Jing

2016-01-01

The purpose of this article is to describe a statistical approach for predicting a respirator user's fit factor in the future based upon results from initial tests. A statistical prediction model was developed based upon joint distribution of multiple fit factor measurements over time obtained from linear mixed effect models. The model accounts for within-subject correlation as well as short-term (within one day) and longer-term variability. As an example of applying this approach, model parameters were estimated from a research study in which volunteers were trained by three different modalities to use one of two types of respirators. They underwent two quantitative fit tests at the initial session and two on the same day approximately six months later. The fitted models demonstrated correlation and gave the estimated distribution of future fit test results conditional on past results for an individual worker. This approach can be applied to establishing a criterion value for passing an initial fit test to provide reasonable likelihood that a worker will be adequately protected in the future; and to optimizing the repeat fit factor test intervals individually for each user for cost-effective testing.

Assessment of statistical significance and clinical relevance.

PubMed

Kieser, Meinhard; Friede, Tim; Gondan, Matthias

2013-05-10

In drug development, it is well accepted that a successful study will demonstrate not only a statistically significant result but also a clinically relevant effect size. Whereas standard hypothesis tests are used to demonstrate the former, it is less clear how the latter should be established. In the first part of this paper, we consider the responder analysis approach and study the performance of locally optimal rank tests when the outcome distribution is a mixture of responder and non-responder distributions. We find that these tests are quite sensitive to their planning assumptions and have therefore not really any advantage over standard tests such as the t-test and the Wilcoxon-Mann-Whitney test, which perform overall well and can be recommended for applications. In the second part, we present a new approach to the assessment of clinical relevance based on the so-called relative effect (or probabilistic index) and derive appropriate sample size formulae for the design of studies aiming at demonstrating both a statistically significant and clinically relevant effect. Referring to recent studies in multiple sclerosis, we discuss potential issues in the application of this approach. Copyright © 2012 John Wiley & Sons, Ltd.

Perception of ensemble statistics requires attention.

PubMed

Jackson-Nielsen, Molly; Cohen, Michael A; Pitts, Michael A

2017-02-01

To overcome inherent limitations in perceptual bandwidth, many aspects of the visual world are represented as summary statistics (e.g., average size, orientation, or density of objects). Here, we investigated the relationship between summary (ensemble) statistics and visual attention. Recently, it was claimed that one ensemble statistic in particular, color diversity, can be perceived without focal attention. However, a broader debate exists over the attentional requirements of conscious perception, and it is possible that some form of attention is necessary for ensemble perception. To test this idea, we employed a modified inattentional blindness paradigm and found that multiple types of summary statistics (color and size) often go unnoticed without attention. In addition, we found attentional costs in dual-task situations, further implicating a role for attention in statistical perception. Overall, we conclude that while visual ensembles may be processed efficiently, some amount of attention is necessary for conscious perception of ensemble statistics. Copyright © 2016 Elsevier Inc. All rights reserved.

Supratentorial lesions contribute to trigeminal neuralgia in multiple sclerosis.

PubMed

Fröhlich, Kilian; Winder, Klemens; Linker, Ralf A; Engelhorn, Tobias; Dörfler, Arnd; Lee, De-Hyung; Hilz, Max J; Schwab, Stefan; Seifert, Frank

2018-06-01

Background It has been proposed that multiple sclerosis lesions afflicting the pontine trigeminal afferents contribute to trigeminal neuralgia in multiple sclerosis. So far, there are no imaging studies that have evaluated interactions between supratentorial lesions and trigeminal neuralgia in multiple sclerosis patients. Methods We conducted a retrospective study and sought multiple sclerosis patients with trigeminal neuralgia and controls in a local database. Multiple sclerosis lesions were manually outlined and transformed into stereotaxic space. We determined the lesion overlap and performed a voxel-wise subtraction analysis. Secondly, we conducted a voxel-wise non-parametric analysis using the Liebermeister test. Results From 12,210 multiple sclerosis patient records screened, we identified 41 patients with trigeminal neuralgia. The voxel-wise subtraction analysis yielded associations between trigeminal neuralgia and multiple sclerosis lesions in the pontine trigeminal afferents, as well as larger supratentorial lesion clusters in the contralateral insula and hippocampus. The non-parametric statistical analysis using the Liebermeister test yielded similar areas to be associated with multiple sclerosis-related trigeminal neuralgia. Conclusions Our study confirms previous data on associations between multiple sclerosis-related trigeminal neuralgia and pontine lesions, and showed for the first time an association with lesions in the insular region, a region involved in pain processing and endogenous pain modulation.

Evaluation of the impact of fetal fibronectin test implementation on hospital admissions for preterm labour in Ontario: a multiple baseline time-series design.

PubMed

Fell, D B; Sprague, A E; Grimshaw, J M; Yasseen, A S; Coyle, D; Dunn, S I; Perkins, S L; Peterson, W E; Johnson, M; Bunting, P S; Walker, M C

2014-03-01

To determine the impact of a health system-wide fetal fibronectin (fFN) testing programme on the rates of hospital admission for preterm labour (PTL). Multiple baseline time-series design. Canadian province of Ontario. A retrospective population-based cohort of antepartum and delivered obstetrical admissions in all Ontario hospitals between 1 April 2002 and 31 March 2010. International Classification of Diseases codes in a health system-wide hospital administrative database were used to identify the study population and define the outcome measure. An aggregate time series of monthly rates of hospital admissions for PTL was analysed using segmented regression models after aligning the fFN test implementation date for each institution. Rate of obstetrical hospital admission for PTL. Estimated rates of hospital admission for PTL following fFN implementation were lower than predicted had pre-implementation trends prevailed. The reduction in the rate was modest, but statistically significant, when estimated at 12 months following fFN implementation (-0.96 hospital admissions for PTL per 100 preterm births; 95% confidence interval [CI], -1.02 to -0.90, P = 0.04). The statistically significant reduction was sustained at 24 and 36 months following implementation. Using a robust quasi-experimental study design to overcome confounding as a result of underlying secular trends or concurrent interventions, we found evidence of a small but statistically significant reduction in the health system-level rate of hospital admissions for PTL following implementation of fFN testing in a large Canadian province. © 2013 Royal College of Obstetricians and Gynaecologists.

Heterogeneity Between Ducts of the Same Nuclear Grade Involved by Duct Carcinoma In Situ (DCIS) of the Breast

PubMed Central

Miller, Naomi A.; Chapman, Judith-Anne W.; Qian, Jin; Christens-Barry, William A.; Fu, Yuejiao; Yuan, Yan; Lickley, H. Lavina A.; Axelrod, David E.

2010-01-01

Purpose Nuclear grade of breast DCIS is considered during patient management decision-making although it may have only a modest prognostic association with therapeutic outcome. We hypothesized that visual inspection may miss substantive differences in nuclei classified as having the same nuclear grade. To test this hypothesis, we measured subvisual nuclear features by quantitative image cytometry for nuclei with the same grade, and tested for statistical differences in these features. Experimental design and statistical analysis Thirty-nine nuclear digital image features of about 100 nuclei were measured in digital images of H&E stained slides of 81 breast biopsy specimens. One field with at least 5 ducts was evaluated for each patient. We compared features of nuclei with the same grade in multiple ducts of the same patient with ANOVA (or Welch test), and compared features of nuclei with the same grade in two ducts of different patients using 2-sided t-tests (P ≤ 0.05). Also, we compared image features for nuclei in patients with single grade to those with the same grade in patients with multiple grades using t-tests. Results Statistically significant differences were detected in nuclear features between ducts with the same nuclear grade, both in different ducts of the same patient, and between ducts in different patients with DCIS of more than one grade. Conclusion Nuclei in ducts visually described as having the same nuclear grade had significantly different subvisual digital image features. These subvisual differences may be considered additional manifestations of heterogeneity over and above differences that can be observed microscopically. This heterogeneity may explain the inconsistency of nuclear grading as a prognostic factor. PMID:20981137

A unified framework for weighted parametric multiple test procedures.

PubMed

Xi, Dong; Glimm, Ekkehard; Maurer, Willi; Bretz, Frank

2017-09-01

We describe a general framework for weighted parametric multiple test procedures based on the closure principle. We utilize general weighting strategies that can reflect complex study objectives and include many procedures in the literature as special cases. The proposed weighted parametric tests bridge the gap between rejection rules using either adjusted significance levels or adjusted p-values. This connection is made by allowing intersection hypotheses of the underlying closed test procedure to be tested at level smaller than α. This may be also necessary to take certain study situations into account. For such cases we introduce a subclass of exact α-level parametric tests that satisfy the consonance property. When the correlation is known only for certain subsets of the test statistics, a new procedure is proposed to fully utilize this knowledge within each subset. We illustrate the proposed weighted parametric tests using a clinical trial example and conduct a simulation study to investigate its operating characteristics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Diagramming the Never Ending Story: Student-generated diagrammatic stories integrate and retain science concepts improving science literacy

NASA Astrophysics Data System (ADS)

Pillsbury, Ralph T.

This research examined an instructional strategy called Diagramming the Never Ending Story: A method called diagramming was taught to sixth grade students via an outdoor science inquiry ecology unit. Students generated diagrams of the new ecology concepts they encountered, creating explanatory 'captions' for their newly drawn diagrams while connecting them in a memorable story. The diagramming process culminates in 20-30 meter-long murals called the Never Ending Story: Months of science instruction are constructed as pictorial scrolls, making sense of all new science concepts they encounter. This method was taught at a North Carolina "Public" Charter School, Children's Community School, to measure its efficacy in helping students comprehend scientific concepts and retain them thereby increasing science literacy. There were four demographically similar classes of 20 students each. Two 'treatment' classes, randomly chosen from the four classes, generated their own Never Ending Stories after being taught the diagramming method. A Solomon Four-Group Design was employed: Two Classes (one control, one treatment) were administered pre- and post; two classes received post tests only. The tests were comprised of multiple choice, fill-in and extended response (open-ended) sections. Multiple choice and fill-in test data were not statistically significant whereas extended response test data confirm that treatment classes made statistically significant gains.

Using Multi-Objective Genetic Programming to Synthesize Stochastic Processes

NASA Astrophysics Data System (ADS)

Ross, Brian; Imada, Janine

Genetic programming is used to automatically construct stochastic processes written in the stochastic π-calculus. Grammar-guided genetic programming constrains search to useful process algebra structures. The time-series behaviour of a target process is denoted with a suitable selection of statistical feature tests. Feature tests can permit complex process behaviours to be effectively evaluated. However, they must be selected with care, in order to accurately characterize the desired process behaviour. Multi-objective evaluation is shown to be appropriate for this application, since it permits heterogeneous statistical feature tests to reside as independent objectives. Multiple undominated solutions can be saved and evaluated after a run, for determination of those that are most appropriate. Since there can be a vast number of candidate solutions, however, strategies for filtering and analyzing this set are required.

Observational Word Learning: Beyond Propose-But-Verify and Associative Bean Counting.

PubMed

Roembke, Tanja; McMurray, Bob

2016-04-01

Learning new words is difficult. In any naming situation, there are multiple possible interpretations of a novel word. Recent approaches suggest that learners may solve this problem by tracking co-occurrence statistics between words and referents across multiple naming situations (e.g. Yu & Smith, 2007), overcoming the ambiguity in any one situation. Yet, there remains debate around the underlying mechanisms. We conducted two experiments in which learners acquired eight word-object mappings using cross-situational statistics while eye-movements were tracked. These addressed four unresolved questions regarding the learning mechanism. First, eye-movements during learning showed evidence that listeners maintain multiple hypotheses for a given word and bring them all to bear in the moment of naming. Second, trial-by-trial analyses of accuracy suggested that listeners accumulate continuous statistics about word/object mappings, over and above prior hypotheses they have about a word. Third, consistent, probabilistic context can impede learning, as false associations between words and highly co-occurring referents are formed. Finally, a number of factors not previously considered in prior analysis impact observational word learning: knowledge of the foils, spatial consistency of the target object, and the number of trials between presentations of the same word. This evidence suggests that observational word learning may derive from a combination of gradual statistical or associative learning mechanisms and more rapid real-time processes such as competition, mutual exclusivity and even inference or hypothesis testing.

Viewpoint: observations on scaled average bioequivalence.

PubMed

Patterson, Scott D; Jones, Byron

2012-01-01

The two one-sided test procedure (TOST) has been used for average bioequivalence testing since 1992 and is required when marketing new formulations of an approved drug. TOST is known to require comparatively large numbers of subjects to demonstrate bioequivalence for highly variable drugs, defined as those drugs having intra-subject coefficients of variation greater than 30%. However, TOST has been shown to protect public health when multiple generic formulations enter the marketplace following patent expiration. Recently, scaled average bioequivalence (SABE) has been proposed as an alternative statistical analysis procedure for such products by multiple regulatory agencies. SABE testing requires that a three-period partial replicate cross-over or full replicate cross-over design be used. Following a brief summary of SABE analysis methods applied to existing data, we will consider three statistical ramifications of the proposed additional decision rules and the potential impact of implementation of scaled average bioequivalence in the marketplace using simulation. It is found that a constraint being applied is biased, that bias may also result from the common problem of missing data and that the SABE methods allow for much greater changes in exposure when generic-generic switching occurs in the marketplace. Copyright © 2011 John Wiley & Sons, Ltd.

Influences of environment and disturbance on forest patterns in coastal Oregon watersheds.

Treesearch

Michael C. Wimberly; Thomas A. Spies

2001-01-01

Modern ecology often emphasizes the distinction between traditional theories of stable, environmentally structured communities and a new paradigm of disturbance driven, nonequilibrium dynamics. However, multiple hypotheses for observed vegetation patterns have seldom been explicitly tested. We used multivariate statistics and variation partitioning methods to assess...

MGAS: a powerful tool for multivariate gene-based genome-wide association analysis.

PubMed

Van der Sluis, Sophie; Dolan, Conor V; Li, Jiang; Song, Youqiang; Sham, Pak; Posthuma, Danielle; Li, Miao-Xin

2015-04-01

Standard genome-wide association studies, testing the association between one phenotype and a large number of single nucleotide polymorphisms (SNPs), are limited in two ways: (i) traits are often multivariate, and analysis of composite scores entails loss in statistical power and (ii) gene-based analyses may be preferred, e.g. to decrease the multiple testing problem. Here we present a new method, multivariate gene-based association test by extended Simes procedure (MGAS), that allows gene-based testing of multivariate phenotypes in unrelated individuals. Through extensive simulation, we show that under most trait-generating genotype-phenotype models MGAS has superior statistical power to detect associated genes compared with gene-based analyses of univariate phenotypic composite scores (i.e. GATES, multiple regression), and multivariate analysis of variance (MANOVA). Re-analysis of metabolic data revealed 32 False Discovery Rate controlled genome-wide significant genes, and 12 regions harboring multiple genes; of these 44 regions, 30 were not reported in the original analysis. MGAS allows researchers to conduct their multivariate gene-based analyses efficiently, and without the loss of power that is often associated with an incorrectly specified genotype-phenotype models. MGAS is freely available in KGG v3.0 (http://statgenpro.psychiatry.hku.hk/limx/kgg/download.php). Access to the metabolic dataset can be requested at dbGaP (https://dbgap.ncbi.nlm.nih.gov/). The R-simulation code is available from http://ctglab.nl/people/sophie_van_der_sluis. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

The effects of multiple repairs on Inconel 718 weld mechanical properties

NASA Technical Reports Server (NTRS)

Russell, C. K.; Nunes, A. C., Jr.; Moore, D.

1991-01-01

Inconel 718 weldments were repaired 3, 6, 9, and 13 times using the gas tungsten arc welding process. The welded panels were machined into mechanical test specimens, postweld heat treated, and nondestructively tested. Tensile properties and high cycle fatigue life were evaluated and the results compared to unrepaired weld properties. Mechanical property data were analyzed using the statistical methods of difference in means for tensile properties and difference in log means and Weibull analysis for high cycle fatigue properties. Statistical analysis performed on the data did not show a significant decrease in tensile or high cycle fatigue properties due to the repeated repairs. Some degradation was observed in all properties, however, it was minimal.

Integrating the ACR Appropriateness Criteria Into the Radiology Clerkship: Comparison of Didactic Format and Group-Based Learning.

PubMed

Stein, Marjorie W; Frank, Susan J; Roberts, Jeffrey H; Finkelstein, Malka; Heo, Moonseong

2016-05-01

The aim of this study was to determine whether group-based or didactic teaching is more effective to teach ACR Appropriateness Criteria to medical students. An identical pretest, posttest, and delayed multiple-choice test was used to evaluate the efficacy of the two teaching methods. Descriptive statistics comparing test scores were obtained. On the posttest, the didactic group gained 12.5 points (P < .0001), and the group-based learning students gained 16.3 points (P < .0001). On the delayed test, the didactic group gained 14.4 points (P < .0001), and the group-based learning students gained 11.8 points (P < .001). The gains in scores on both tests were statistically significant for both groups. However, the differences in scores were not statistically significant comparing the two educational methods. Compared with didactic lectures, group-based learning is more enjoyable, time efficient, and equally efficacious. The choice of educational method can be individualized for each institution on the basis of group size, time constraints, and faculty availability. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Towards Accurate Modelling of Galaxy Clustering on Small Scales: Testing the Standard ΛCDM + Halo Model

NASA Astrophysics Data System (ADS)

Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.

2018-04-01

Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter halos. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the "accurate" regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard ΛCDM + halo model against the clustering of SDSS DR7 galaxies. Specifically, we use the projected correlation function, group multiplicity function and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir halos) matches the clustering of low luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the "standard" halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.

Fully Bayesian tests of neutrality using genealogical summary statistics.

PubMed

Drummond, Alexei J; Suchard, Marc A

2008-10-31

Many data summary statistics have been developed to detect departures from neutral expectations of evolutionary models. However questions about the neutrality of the evolution of genetic loci within natural populations remain difficult to assess. One critical cause of this difficulty is that most methods for testing neutrality make simplifying assumptions simultaneously about the mutational model and the population size model. Consequentially, rejecting the null hypothesis of neutrality under these methods could result from violations of either or both assumptions, making interpretation troublesome. Here we harness posterior predictive simulation to exploit summary statistics of both the data and model parameters to test the goodness-of-fit of standard models of evolution. We apply the method to test the selective neutrality of molecular evolution in non-recombining gene genealogies and we demonstrate the utility of our method on four real data sets, identifying significant departures of neutrality in human influenza A virus, even after controlling for variation in population size. Importantly, by employing a full model-based Bayesian analysis, our method separates the effects of demography from the effects of selection. The method also allows multiple summary statistics to be used in concert, thus potentially increasing sensitivity. Furthermore, our method remains useful in situations where analytical expectations and variances of summary statistics are not available. This aspect has great potential for the analysis of temporally spaced data, an expanding area previously ignored for limited availability of theory and methods.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

RAId_DbS: Peptide Identification using Database Searches with Realistic Statistics

PubMed Central

Alves, Gelio; Ogurtsov, Aleksey Y; Yu, Yi-Kuo

2007-01-01

Background The key to mass-spectrometry-based proteomics is peptide identification. A major challenge in peptide identification is to obtain realistic E-values when assigning statistical significance to candidate peptides. Results Using a simple scoring scheme, we propose a database search method with theoretically characterized statistics. Taking into account possible skewness in the random variable distribution and the effect of finite sampling, we provide a theoretical derivation for the tail of the score distribution. For every experimental spectrum examined, we collect the scores of peptides in the database, and find good agreement between the collected score statistics and our theoretical distribution. Using Student's t-tests, we quantify the degree of agreement between the theoretical distribution and the score statistics collected. The T-tests may be used to measure the reliability of reported statistics. When combined with reported P-value for a peptide hit using a score distribution model, this new measure prevents exaggerated statistics. Another feature of RAId_DbS is its capability of detecting multiple co-eluted peptides. The peptide identification performance and statistical accuracy of RAId_DbS are assessed and compared with several other search tools. The executables and data related to RAId_DbS are freely available upon request. PMID:17961253

The role of empirical Bayes methodology as a leading principle in modern medical statistics.

PubMed

van Houwelingen, Hans C

2014-11-01

This paper reviews and discusses the role of Empirical Bayes methodology in medical statistics in the last 50 years. It gives some background on the origin of the empirical Bayes approach and its link with the famous Stein estimator. The paper describes the application in four important areas in medical statistics: disease mapping, health care monitoring, meta-analysis, and multiple testing. It ends with a warning that the application of the outcome of an empirical Bayes analysis to the individual "subjects" is a delicate matter that should be handled with prudence and care. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Correction of the significance level when attempting multiple transformations of an explanatory variable in generalized linear models

PubMed Central

2013-01-01

Background In statistical modeling, finding the most favorable coding for an exploratory quantitative variable involves many tests. This process involves multiple testing problems and requires the correction of the significance level. Methods For each coding, a test on the nullity of the coefficient associated with the new coded variable is computed. The selected coding corresponds to that associated with the largest statistical test (or equivalently the smallest pvalue). In the context of the Generalized Linear Model, Liquet and Commenges (Stat Probability Lett,71:33–38,2005) proposed an asymptotic correction of the significance level. This procedure, based on the score test, has been developed for dichotomous and Box-Cox transformations. In this paper, we suggest the use of resampling methods to estimate the significance level for categorical transformations with more than two levels and, by definition those that involve more than one parameter in the model. The categorical transformation is a more flexible way to explore the unknown shape of the effect between an explanatory and a dependent variable. Results The simulations we ran in this study showed good performances of the proposed methods. These methods were illustrated using the data from a study of the relationship between cholesterol and dementia. Conclusion The algorithms were implemented using R, and the associated CPMCGLM R package is available on the CRAN. PMID:23758852

Statistical technique for analysing functional connectivity of multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman

2011-03-15

A new statistical technique, the Cox method, used for analysing functional connectivity of simultaneously recorded multiple spike trains is presented. This method is based on the theory of modulated renewal processes and it estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connectivity an "influence function" is identified. This function recognises the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. In comparison to existing techniques, the Cox method has the following advantages: it does not use bins (binless method); it is applicable to cases where the sample size is small; it is sufficiently sensitive such that it estimates weak influences; it supports the simultaneous analysis of multiple influences; it is able to identify a correct connectivity scheme in difficult cases of "common source" or "indirect" connectivity. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analysing functional connectivity of simultaneously recorded multiple spike trains. Copyright © 2011 Elsevier B.V. All rights reserved.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.

PubMed

Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

2017-08-01

Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.

Statistical methods for quantitative mass spectrometry proteomic experiments with labeling.

PubMed

Oberg, Ann L; Mahoney, Douglas W

2012-01-01

Mass Spectrometry utilizing labeling allows multiple specimens to be subjected to mass spectrometry simultaneously. As a result, between-experiment variability is reduced. Here we describe use of fundamental concepts of statistical experimental design in the labeling framework in order to minimize variability and avoid biases. We demonstrate how to export data in the format that is most efficient for statistical analysis. We demonstrate how to assess the need for normalization, perform normalization, and check whether it worked. We describe how to build a model explaining the observed values and test for differential protein abundance along with descriptive statistics and measures of reliability of the findings. Concepts are illustrated through the use of three case studies utilizing the iTRAQ 4-plex labeling protocol.

[The influence of high-tone power therapy on the functional status of patients with multiple sclerosis].

PubMed

Kubsik, Anna; Klimkiewicz, Paulina; Klimkiewicz, Robert; Jankowska, Katarzyna; Jankowska, Agnieszka; Woldańska-Okońska, Marta

2014-07-01

Multiple sclerosis is a chronic, inflammatory, demyelinating disease of the central nervous system, which is characterized by diverse symptomatology. Most often affects people at a young age gradually leading to their disability. Looking for new therapies to alleviate neurological deficits caused by the disease. One of the alternative methods of therapy is high - tone power therapy. The article is a comparison of high-tone power therapy and kinesis in improving patients with multiple sclerosis. The aim of this study was to evaluate the effectiveness of high-tone power therapy and exercises in kinesis on the functional status of patients with multiple sclerosis. The study involved 20 patients with multiple sclerosis, both sexes, treated at the Department of Rehabilitation and Physical Medicine in Lodz. Patients were randomly divided into two groups studied. In group high-tone power therapy applied for 60 minutes, while in group II were used exercises for kinesis. Treatment time for both groups of patients was 15 days. To assess the functional status scale was used: Expanded Disability Status Scale of Kurtzke (EDSS), as well as by Barthel ADL Index. Assessment of quality of life were made using MSQOL Questionnaire-54. For the evaluation of gait and balance using Tinetti scale, and pain VAS rated, and Laitinen. Changes in muscle tone was assessed on the basis of the Ashworth scale. Both group I and II improved on scales conducted before and after therapy. In group I, in which the applied high-tone power therapy, reported statistically significant results in 9 out of 10 tested parameters, while in group II, which was used in the exercises in kinesis an improvement in 6 out of 10 tested parameters. Correlating the results of both the test groups in relation to each other did not show statistically significant differences. High-Tone Power Therapy beneficial effect on the functional status of patients with multiple sclerosis. Obtaining results in terms of number of tested parameters allows for the use of this therapy in the comprehensive improvement of patients with multiple sclerosis. Exercises from the scheme kinesis favorable impact on the functional status of patients with MS and are essential in the rehabilitation of these patients. In any group, no adverse effects were observed.

Bone scan as a screening test for missed fractures in severely injured patients.

PubMed

Lee, K-J; Jung, K; Kim, J; Kwon, J

2014-12-01

In many cases, patients with severe blunt trauma have multiple fractures throughout the body. These fractures are not often detectable by history or physical examination, and their diagnosis can be delayed or even missed. Thus, screening test fractures of the whole body is required after initial management. We performed this study to evaluate the reliability of bone scans for detecting missed fractures in patients with multiple severe traumas and we analyzed the causes of missed fractures by using bone scan. A bone scan is useful as a screening test for fractures of the entire body of severe trauma patients who are passed the acute phase. We reviewed the electronic medical records of severe trauma patients who underwent a bone scan from September 2009 to December 2010. Demographic and medical data were compared and statistically analyzed to determine whether missed fractures were detected after bone scan in the two groups. A total of 382 patients who had an injury severity score [ISS] greater than 16 points with multiple traumas visited the emergency room. One hundred and thirty-one patients underwent bone scan and 81 patients were identified with missed fractures by bone scan. The most frequent location for missed fractures was the rib area (55 cases, 41.98%), followed by the extremities (42 cases, 32.06%). The missed fractures that required surgery or splint were most common in extremities (11 cases). In univariate analysis, higher ISS scores and mechanism of injury were related with the probability that missed fractures would be found with a bone scan. The ISS score was statistically significant in multivariate analysis. Bone scan is an effective method of detecting missed fractures among patients with multiple severe traumas. Level IV, retrospective study. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Analysis of Gene Expression Profiles of Soft Tissue Sarcoma Using a Combination of Knowledge-Based Filtering with Integration of Multiple Statistics

PubMed Central

Doi, Ayano; Ichinohe, Risa; Ikuyo, Yoriko; Takahashi, Teruyoshi; Marui, Shigetaka; Yasuhara, Koji; Nakamura, Tetsuro; Sugita, Shintaro; Sakamoto, Hiromi; Yoshida, Teruhiko; Hasegawa, Tadashi

2014-01-01

The diagnosis and treatment of soft tissue sarcomas (STS) have been difficult. Of the diverse histological subtypes, undifferentiated pleomorphic sarcoma (UPS) is particularly difficult to diagnose accurately, and its classification per se is still controversial. Recent advances in genomic technologies provide an excellent way to address such problems. However, it is often difficult, if not impossible, to identify definitive disease-associated genes using genome-wide analysis alone, primarily because of multiple testing problems. In the present study, we analyzed microarray data from 88 STS patients using a combination method that used knowledge-based filtering and a simulation based on the integration of multiple statistics to reduce multiple testing problems. We identified 25 genes, including hypoxia-related genes (e.g., MIF, SCD1, P4HA1, ENO1, and STAT1) and cell cycle- and DNA repair-related genes (e.g., TACC3, PRDX1, PRKDC, and H2AFY). These genes showed significant differential expression among histological subtypes, including UPS, and showed associations with overall survival. STAT1 showed a strong association with overall survival in UPS patients (logrank p = 1.84×10−6 and adjusted p value 2.99×10−3 after the permutation test). According to the literature, the 25 genes selected are useful not only as markers of differential diagnosis but also as prognostic/predictive markers and/or therapeutic targets for STS. Our combination method can identify genes that are potential prognostic/predictive factors and/or therapeutic targets in STS and possibly in other cancers. These disease-associated genes deserve further preclinical and clinical validation. PMID:25188299

A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits

PubMed Central

Yang, Runqing; Gao, Huijiang; Wang, Xin; Zhang, Ji; Zeng, Zhao-Bang; Wu, Rongling

2007-01-01

Functional mapping has emerged as a powerful tool for mapping quantitative trait loci (QTL) that control developmental patterns of complex dynamic traits. Original functional mapping has been constructed within the context of simple interval mapping, without consideration of separate multiple linked QTL for a dynamic trait. In this article, we present a statistical framework for mapping QTL that affect dynamic traits by capitalizing on the strengths of functional mapping and composite interval mapping. Within this so-called composite functional-mapping framework, functional mapping models the time-dependent genetic effects of a QTL tested within a marker interval using a biologically meaningful parametric function, whereas composite interval mapping models the time-dependent genetic effects of the markers outside the test interval to control the genome background using a flexible nonparametric approach based on Legendre polynomials. Such a semiparametric framework was formulated by a maximum-likelihood model and implemented with the EM algorithm, allowing for the estimation and the test of the mathematical parameters that define the QTL effects and the regression coefficients of the Legendre polynomials that describe the marker effects. Simulation studies were performed to investigate the statistical behavior of composite functional mapping and compare its advantage in separating multiple linked QTL as compared to functional mapping. We used the new mapping approach to analyze a genetic mapping example in rice, leading to the identification of multiple QTL, some of which are linked on the same chromosome, that control the developmental trajectory of leaf age. PMID:17947431

An efficient genome-wide association test for mixed binary and continuous phenotypes with applications to substance abuse research.

PubMed

Buu, Anne; Williams, L Keoki; Yang, James J

2018-03-01

We propose a new genome-wide association test for mixed binary and continuous phenotypes that uses an efficient numerical method to estimate the empirical distribution of the Fisher's combination statistic under the null hypothesis. Our simulation study shows that the proposed method controls the type I error rate and also maintains its power at the level of the permutation method. More importantly, the computational efficiency of the proposed method is much higher than the one of the permutation method. The simulation results also indicate that the power of the test increases when the genetic effect increases, the minor allele frequency increases, and the correlation between responses decreases. The statistical analysis on the database of the Study of Addiction: Genetics and Environment demonstrates that the proposed method combining multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests.

Correlation Between University Students' Kinematic Achievement and Learning Styles

NASA Astrophysics Data System (ADS)

Çirkinoǧlu, A. G.; Dem&ircidot, N.

2007-04-01

In the literature, some researches on kinematics revealed that students have many difficulties in connecting graphs and physics. Also some researches showed that the method used in classroom affects students' further learning. In this study the correlation between university students' kinematics achieve and learning style are investigated. In this purpose Kinematics Achievement Test and Learning Style Inventory were applied to 573 students enrolled in general physics 1 courses at Balikesir University in the fall semester of 2005-2006. Kinematics Test, consists of 12 multiple choose and 6 open ended questions, was developed by researchers to assess students' understanding, interpreting, and drawing graphs. Learning Style Inventory, a 24 items test including visual, auditory, and kinesthetic learning styles, was developed and used by Barsch. The data obtained from in this study were analyzed necessary statistical calculations (T-test, correlation, ANOVA, etc.) by using SPSS statistical program. Based on the research findings, the tentative recommendations are made.

Legitimate Techniques for Improving the R-Square and Related Statistics of a Multiple Regression Model

DTIC Science & Technology

1981-01-01

explanatory variable has been ommitted. Ramsey (1974) has developed a rather interesting test for detecting specification errors using estimates of the...Peter. (1979) A Guide to Econometrics , Cambridge, MA: The MIT Press. Ramsey , J.B. (1974), "Classical Model Selection Through Specification Error... Tests ," in P. Zarembka, Ed. Frontiers in Econometrics , New York: Academia Press. Theil, Henri. (1971), Principles of Econometrics , New York: John Wiley

Efficacy of Social Media Adoption on Client Growth for Independent Management Consultants

DTIC Science & Technology

2017-02-01

design , a linear multiple regression with three predictor variables and one dependent variable per testing were used. Under those circumstances...regression test was used to compare the social media adoption of two groups on a single measure to determine if there was a statistical difference...number and types of social media platforms used and their influence on client growth was examined in this research design that used a descriptive

Shuttle payload minimum cost vibroacoustic tests

NASA Technical Reports Server (NTRS)

Stahle, C. V.; Gongloff, H. R.; Young, J. P.; Keegan, W. B.

1977-01-01

This paper is directed toward the development of the methodology needed to evaluate cost effective vibroacoustic test plans for Shuttle Spacelab payloads. Statistical decision theory is used to quantitatively evaluate seven alternate test plans by deriving optimum test levels and the expected cost for each multiple mission payload considered. The results indicate that minimum costs can vary by as much as $6 million for the various test plans. The lowest cost approach eliminates component testing and maintains flight vibration reliability by performing subassembly tests at a relatively high acoustic level. Test plans using system testing or combinations of component and assembly level testing are attractive alternatives. Component testing alone is shown not to be cost effective.

[Effect of preventive treatment on cognitive performance in patients with multiple sclerosis].

PubMed

Shorobura, Maria S

2018-01-01

Introduction: cognitive, emotional and psychopathological changes play a significant role in the clinical picture of multiple sclerosis and influence the effectiveness of drug therapy, working capacity, quality of life, and the process of rehabilitation of patients with multiple sclerosis. The aim: investigate the changes in cognitive function in patients with multiple sclerosis, such as information processing speed and working memory of patients before and after treatment with immunomodulating drug. Materials and methods:33 patients examined reliably diagnosed with multiple sclerosis who were treated with preventive examinations and treatment from 2012 to 2016. For all patients with multiple sclerosis had clinical-neurological examination (neurological status using the EDSS scale) and the cognitive status was evaluated using the PASAT auditory test. Patient screening was performed before, during and after the therapy. Statistical analysis of the results was performed in the system Statistica 8.0. We used Student's t-test (t), Mann-Whitney test (Z). Person evaluated the correlation coefficients and Spearman (r, R), Wilcoxon criterion (T), Chi-square (X²). Results: The age of patients with multiple sclerosis affects the growth and EDSS scale score decrease PASAT to treatment. Duration of illness affects the EDSS scale score and performance PASAT. Indicators PASAT not significantly decreased throughout the treatment. Conclusions: glatiramer acetate has a positive effect on cognitive function, information processing speed and working memory patients with multiple sclerosis, which is one of the important components of the therapeutic effect of this drug.

Potential Mediators in Parenting and Family Intervention: Quality of Mediation Analyses

PubMed Central

Patel, Chandni C.; Fairchild, Amanda J.; Prinz, Ronald J.

2017-01-01

Parenting and family interventions have repeatedly shown effectiveness in preventing and treating a range of youth outcomes. Accordingly, investigators in this area have conducted a number of studies using statistical mediation to examine some of the potential mechanisms of action by which these interventions work. This review examined from a methodological perspective in what ways and how well the family-based intervention studies tested statistical mediation. A systematic search identified 73 published outcome studies that tested mediation for family-based interventions across a wide range of child and adolescent outcomes (i.e., externalizing, internalizing, and substance-abuse problems; high-risk sexual activity; and academic achievement), for putative mediators pertaining to positive and negative parenting, family functioning, youth beliefs and coping skills, and peer relationships. Taken as a whole, the studies used designs that adequately addressed temporal precedence. The majority of studies used the product of coefficients approach to mediation, which is preferred, and less limiting than the causal steps approach. Statistical significance testing did not always make use of the most recently developed approaches, which would better accommodate small sample sizes and more complex functions. Specific recommendations are offered for future mediation studies in this area with respect to full longitudinal design, mediation approach, significance testing method, documentation and reporting of statistics, testing of multiple mediators, and control for Type I error. PMID:28028654

SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit

PubMed Central

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

2011-01-01

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 updated information and newly added models. PMID:21546994

Multiple comparisons permutation test for image based data mining in radiotherapy.

PubMed

Chen, Chun; Witte, Marnix; Heemsbergen, Wilma; van Herk, Marcel

2013-12-23

: Comparing incidental dose distributions (i.e. images) of patients with different outcomes is a straightforward way to explore dose-response hypotheses in radiotherapy. In this paper, we introduced a permutation test that compares images, such as dose distributions from radiotherapy, while tackling the multiple comparisons problem. A test statistic Tmax was proposed that summarizes the differences between the images into a single value and a permutation procedure was employed to compute the adjusted p-value. We demonstrated the method in two retrospective studies: a prostate study that relates 3D dose distributions to failure, and an esophagus study that relates 2D surface dose distributions of the esophagus to acute esophagus toxicity. As a result, we were able to identify suspicious regions that are significantly associated with failure (prostate study) or toxicity (esophagus study). Permutation testing allows direct comparison of images from different patient categories and is a useful tool for data mining in radiotherapy.

Second Language Experience Facilitates Statistical Learning of Novel Linguistic Materials.

PubMed

Potter, Christine E; Wang, Tianlin; Saffran, Jenny R

2017-04-01

Recent research has begun to explore individual differences in statistical learning, and how those differences may be related to other cognitive abilities, particularly their effects on language learning. In this research, we explored a different type of relationship between language learning and statistical learning: the possibility that learning a new language may also influence statistical learning by changing the regularities to which learners are sensitive. We tested two groups of participants, Mandarin Learners and Naïve Controls, at two time points, 6 months apart. At each time point, participants performed two different statistical learning tasks: an artificial tonal language statistical learning task and a visual statistical learning task. Only the Mandarin-learning group showed significant improvement on the linguistic task, whereas both groups improved equally on the visual task. These results support the view that there are multiple influences on statistical learning. Domain-relevant experiences may affect the regularities that learners can discover when presented with novel stimuli. Copyright © 2016 Cognitive Science Society, Inc.

Second language experience facilitates statistical learning of novel linguistic materials

PubMed Central

Potter, Christine E.; Wang, Tianlin; Saffran, Jenny R.

2016-01-01

Recent research has begun to explore individual differences in statistical learning, and how those differences may be related to other cognitive abilities, particularly their effects on language learning. In the present research, we explored a different type of relationship between language learning and statistical learning: the possibility that learning a new language may also influence statistical learning by changing the regularities to which learners are sensitive. We tested two groups of participants, Mandarin Learners and Naïve Controls, at two time points, six months apart. At each time point, participants performed two different statistical learning tasks: an artificial tonal language statistical learning task and a visual statistical learning task. Only the Mandarin-learning group showed significant improvement on the linguistic task, while both groups improved equally on the visual task. These results support the view that there are multiple influences on statistical learning. Domain-relevant experiences may affect the regularities that learners can discover when presented with novel stimuli. PMID:27988939

Configural Frequency Analysis as a Statistical Tool for Developmental Research.

ERIC Educational Resources Information Center

Lienert, Gustav A.; Oeveste, Hans Zur

1985-01-01

Configural frequency analysis (CFA) is suggested as a technique for longitudinal research in developmental psychology. Stability and change in answers to multiple choice and yes-no item patterns obtained with repeated measurements are identified by CFA and illustrated by developmental analysis of an item from Gorham's Proverb Test. (Author/DWH)

Precipitation Under Cyclic Strain in Solution-Treated Al-4wt%Cu I: Mechanical Behavior

DTIC Science & Technology

2009-02-01

minutes and quenched into ice water immediately prior to mechanical testing. Orientation Imaging Microscopy (OIM) was performed on a FEI XL30 SEM...sampled in order to gain statistical significance with a grain size of 350 µm, it was necessary to condense the data from multiple low-magnification

Applying Item Response Theory Methods to Examine the Impact of Different Response Formats

ERIC Educational Resources Information Center

Hohensinn, Christine; Kubinger, Klaus D.

2011-01-01

In aptitude and achievement tests, different response formats are usually used. A fundamental distinction must be made between the class of multiple-choice formats and the constructed response formats. Previous studies have examined the impact of different response formats applying traditional statistical approaches, but these influences can also…

A comparison of forest canopy transmittance estimators

Treesearch

E.R. Smith; Kurt H. Riitters

1994-01-01

Multiple sensors, and alternate statistical estimators, were tested for measuring canopy transmittance in four stands under a variety of sky conditions. On a given day, stand average transmittance estimates were insensitive to degree of synchronization of the sensors used to measure under-canopy and incoming radiation. In comparisons to periodic measurement of incoming...

Child Abuse and Neglect: Training Needs of Student Teachers

ERIC Educational Resources Information Center

McKee, Bronagh E.; Dillenburger, Karola

2009-01-01

Increasing awareness of child abuse and neglect (CAN) raises questions about how well teachers are prepared for their role in child protection. This paper assesses and differentiates training needs of first-year students (n = 216) in Northern Ireland. Multiple-choice tests were used to assess knowledge of CAN statistics; recognising and reporting;…

Forecasting the discomfort levels within the greater Athens area, Greece using artificial neural networks and multiple criteria analysis

NASA Astrophysics Data System (ADS)

Vouterakos, P. A.; Moustris, K. P.; Bartzokas, A.; Ziomas, I. C.; Nastos, P. T.; Paliatsos, A. G.

2012-12-01

In this work, artificial neural networks (ANNs) were developed and applied in order to forecast the discomfort levels due to the combination of high temperature and air humidity, during the hot season of the year, in eight different regions within the Greater Athens area (GAA), Greece. For the selection of the best type and architecture of ANNs-forecasting models, the multiple criteria analysis (MCA) technique was applied. Three different types of ANNs were developed and tested with the MCA method. Concretely, the multilayer perceptron, the generalized feed forward networks (GFFN), and the time-lag recurrent networks were developed and tested. Results showed that the best ANNs type performance was achieved by using the GFFN model for the prediction of discomfort levels due to high temperature and air humidity within GAA. For the evaluation of the constructed ANNs, appropriate statistical indices were used. The analysis proved that the forecasting ability of the developed ANNs models is very satisfactory at a significant statistical level of p < 0.01.

[Sem: a suitable statistical software adaptated for research in oncology].

PubMed

Kwiatkowski, F; Girard, M; Hacene, K; Berlie, J

2000-10-01

Many softwares have been adapted for medical use; they rarely enable conveniently both data management and statistics. A recent cooperative work ended up in a new software, Sem (Statistics Epidemiology Medicine), which allows data management of trials and, as well, statistical treatments on them. Very convenient, it can be used by non professional in statistics (biologists, doctors, researchers, data managers), since usually (excepted with multivariate models), the software performs by itself the most adequate test, after what complementary tests can be requested if needed. Sem data base manager (DBM) is not compatible with usual DBM: this constitutes a first protection against loss of privacy. Other shields (passwords, cryptage...) strengthen data security, all the more necessary today since Sem can be run on computers nets. Data organization enables multiplicity: forms can be duplicated by patient. Dates are treated in a special but transparent manner (sorting, date and delay calculations...). Sem communicates with common desktop softwares, often with a simple copy/paste. So, statistics can be easily performed on data stored in external calculation sheets, and slides by pasting graphs with a single mouse click (survival curves...). Already used over fifty places in different hospitals for daily work, this product, combining data management and statistics, appears to be a convenient and innovative solution.

Evaluating Composite Sampling Methods of Bacillus Spores at Low Concentrations

PubMed Central

Hess, Becky M.; Amidan, Brett G.; Anderson, Kevin K.; Hutchison, Janine R.

2016-01-01

Restoring all facility operations after the 2001 Amerithrax attacks took years to complete, highlighting the need to reduce remediation time. Some of the most time intensive tasks were environmental sampling and sample analyses. Composite sampling allows disparate samples to be combined, with only a single analysis needed, making it a promising method to reduce response times. We developed a statistical experimental design to test three different composite sampling methods: 1) single medium single pass composite (SM-SPC): a single cellulose sponge samples multiple coupons with a single pass across each coupon; 2) single medium multi-pass composite: a single cellulose sponge samples multiple coupons with multiple passes across each coupon (SM-MPC); and 3) multi-medium post-sample composite (MM-MPC): a single cellulose sponge samples a single surface, and then multiple sponges are combined during sample extraction. Five spore concentrations of Bacillus atrophaeus Nakamura spores were tested; concentrations ranged from 5 to 100 CFU/coupon (0.00775 to 0.155 CFU/cm2). Study variables included four clean surface materials (stainless steel, vinyl tile, ceramic tile, and painted dry wallboard) and three grime coated/dirty materials (stainless steel, vinyl tile, and ceramic tile). Analysis of variance for the clean study showed two significant factors: composite method (p< 0.0001) and coupon material (p = 0.0006). Recovery efficiency (RE) was higher overall using the MM-MPC method compared to the SM-SPC and SM-MPC methods. RE with the MM-MPC method for concentrations tested (10 to 100 CFU/coupon) was similar for ceramic tile, dry wall, and stainless steel for clean materials. RE was lowest for vinyl tile with both composite methods. Statistical tests for the dirty study showed RE was significantly higher for vinyl and stainless steel materials, but lower for ceramic tile. These results suggest post-sample compositing can be used to reduce sample analysis time when responding to a Bacillus anthracis contamination event of clean or dirty surfaces. PMID:27736999

Evaluating Composite Sampling Methods of Bacillus Spores at Low Concentrations.

PubMed

Hess, Becky M; Amidan, Brett G; Anderson, Kevin K; Hutchison, Janine R

2016-01-01

Restoring all facility operations after the 2001 Amerithrax attacks took years to complete, highlighting the need to reduce remediation time. Some of the most time intensive tasks were environmental sampling and sample analyses. Composite sampling allows disparate samples to be combined, with only a single analysis needed, making it a promising method to reduce response times. We developed a statistical experimental design to test three different composite sampling methods: 1) single medium single pass composite (SM-SPC): a single cellulose sponge samples multiple coupons with a single pass across each coupon; 2) single medium multi-pass composite: a single cellulose sponge samples multiple coupons with multiple passes across each coupon (SM-MPC); and 3) multi-medium post-sample composite (MM-MPC): a single cellulose sponge samples a single surface, and then multiple sponges are combined during sample extraction. Five spore concentrations of Bacillus atrophaeus Nakamura spores were tested; concentrations ranged from 5 to 100 CFU/coupon (0.00775 to 0.155 CFU/cm2). Study variables included four clean surface materials (stainless steel, vinyl tile, ceramic tile, and painted dry wallboard) and three grime coated/dirty materials (stainless steel, vinyl tile, and ceramic tile). Analysis of variance for the clean study showed two significant factors: composite method (p< 0.0001) and coupon material (p = 0.0006). Recovery efficiency (RE) was higher overall using the MM-MPC method compared to the SM-SPC and SM-MPC methods. RE with the MM-MPC method for concentrations tested (10 to 100 CFU/coupon) was similar for ceramic tile, dry wall, and stainless steel for clean materials. RE was lowest for vinyl tile with both composite methods. Statistical tests for the dirty study showed RE was significantly higher for vinyl and stainless steel materials, but lower for ceramic tile. These results suggest post-sample compositing can be used to reduce sample analysis time when responding to a Bacillus anthracis contamination event of clean or dirty surfaces.

cit: hypothesis testing software for mediation analysis in genomic applications.

PubMed

Millstein, Joshua; Chen, Gary K; Breton, Carrie V

2016-08-01

The challenges of successfully applying causal inference methods include: (i) satisfying underlying assumptions, (ii) limitations in data/models accommodated by the software and (iii) low power of common multiple testing approaches. The causal inference test (CIT) is based on hypothesis testing rather than estimation, allowing the testable assumptions to be evaluated in the determination of statistical significance. A user-friendly software package provides P-values and optionally permutation-based FDR estimates (q-values) for potential mediators. It can handle single and multiple binary and continuous instrumental variables, binary or continuous outcome variables and adjustment covariates. Also, the permutation-based FDR option provides a non-parametric implementation. Simulation studies demonstrate the validity of the cit package and show a substantial advantage of permutation-based FDR over other common multiple testing strategies. The cit open-source R package is freely available from the CRAN website (https://cran.r-project.org/web/packages/cit/index.html) with embedded C ++ code that utilizes the GNU Scientific Library, also freely available (http://www.gnu.org/software/gsl/). joshua.millstein@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

USGS Publications Warehouse

Lee, L.; Helsel, D.

2007-01-01

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

A robust and efficient statistical method for genetic association studies using case and control samples from multiple cohorts

PubMed Central

2013-01-01

Background The theoretical basis of genome-wide association studies (GWAS) is statistical inference of linkage disequilibrium (LD) between any polymorphic marker and a putative disease locus. Most methods widely implemented for such analyses are vulnerable to several key demographic factors and deliver a poor statistical power for detecting genuine associations and also a high false positive rate. Here, we present a likelihood-based statistical approach that accounts properly for non-random nature of case–control samples in regard of genotypic distribution at the loci in populations under study and confers flexibility to test for genetic association in presence of different confounding factors such as population structure, non-randomness of samples etc. Results We implemented this novel method together with several popular methods in the literature of GWAS, to re-analyze recently published Parkinson’s disease (PD) case–control samples. The real data analysis and computer simulation show that the new method confers not only significantly improved statistical power for detecting the associations but also robustness to the difficulties stemmed from non-randomly sampling and genetic structures when compared to its rivals. In particular, the new method detected 44 significant SNPs within 25 chromosomal regions of size < 1 Mb but only 6 SNPs in two of these regions were previously detected by the trend test based methods. It discovered two SNPs located 1.18 Mb and 0.18 Mb from the PD candidates, FGF20 and PARK8, without invoking false positive risk. Conclusions We developed a novel likelihood-based method which provides adequate estimation of LD and other population model parameters by using case and control samples, the ease in integration of these samples from multiple genetically divergent populations and thus confers statistically robust and powerful analyses of GWAS. On basis of simulation studies and analysis of real datasets, we demonstrated significant improvement of the new method over the non-parametric trend test, which is the most popularly implemented in the literature of GWAS. PMID:23394771

Estimating times of surgeries with two component procedures: comparison of the lognormal and normal models.

PubMed

Strum, David P; May, Jerrold H; Sampson, Allan R; Vargas, Luis G; Spangler, William E

2003-01-01

Variability inherent in the duration of surgical procedures complicates surgical scheduling. Modeling the duration and variability of surgeries might improve time estimates. Accurate time estimates are important operationally to improve utilization, reduce costs, and identify surgeries that might be considered outliers. Surgeries with multiple procedures are difficult to model because they are difficult to segment into homogenous groups and because they are performed less frequently than single-procedure surgeries. The authors studied, retrospectively, 10,740 surgeries each with exactly two CPTs and 46,322 surgical cases with only one CPT from a large teaching hospital to determine if the distribution of dual-procedure surgery times fit more closely a lognormal or a normal model. The authors tested model goodness of fit to their data using Shapiro-Wilk tests, studied factors affecting the variability of time estimates, and examined the impact of coding permutations (ordered combinations) on modeling. The Shapiro-Wilk tests indicated that the lognormal model is statistically superior to the normal model for modeling dual-procedure surgeries. Permutations of component codes did not appear to differ significantly with respect to total procedure time and surgical time. To improve individual models for infrequent dual-procedure surgeries, permutations may be reduced and estimates may be based on the longest component procedure and type of anesthesia. The authors recommend use of the lognormal model for estimating surgical times for surgeries with two component procedures. Their results help legitimize the use of log transforms to normalize surgical procedure times prior to hypothesis testing using linear statistical models. Multiple-procedure surgeries may be modeled using the longest (statistically most important) component procedure and type of anesthesia.

Identifying Pleiotropic Genes in Genome-Wide Association Studies for Multivariate Phenotypes with Mixed Measurement Scales

PubMed Central

Williams, L. Keoki; Buu, Anne

2017-01-01

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies. PMID:28081206

Towards accurate modelling of galaxy clustering on small scales: testing the standard ΛCDM + halo model

NASA Astrophysics Data System (ADS)

Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.

2018-07-01

Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter haloes. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the `accurate' regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard Λ cold dark matter (ΛCDM) + halo model against the clustering of Sloan Digital Sky Survey (SDSS) seventh data release (DR7) galaxies. Specifically, we use the projected correlation function, group multiplicity function, and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir haloes) matches the clustering of low-luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the `standard' halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.

Implementing and testing theoretical fission fragment yields in a Hauser-Feshbach statistical decay framework

NASA Astrophysics Data System (ADS)

Jaffke, Patrick; Möller, Peter; Stetcu, Ionel; Talou, Patrick; Schmitt, Christelle

2018-03-01

We implement fission fragment yields, calculated using Brownian shape-motion on a macroscopic-microscopic potential energy surface in six dimensions, into the Hauser-Feshbach statistical decay code CGMF. This combination allows us to test the impact of utilizing theoretically-calculated fission fragment yields on the subsequent prompt neutron and γ-ray emission. We draw connections between the fragment yields and the total kinetic energy TKE of the fission fragments and demonstrate that the use of calculated yields can introduce a difference in the 〈TKE〉 and, thus, the prompt neutron multiplicity v, as compared with experimental fragment yields. We deduce the uncertainty on the 〈TKE〉 and v from this procedure and identify possible applications.

QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

2013-03-01

A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial

PubMed Central

Hallgren, Kevin A.

2012-01-01

Many research designs require the assessment of inter-rater reliability (IRR) to demonstrate consistency among observational ratings provided by multiple coders. However, many studies use incorrect statistical procedures, fail to fully report the information necessary to interpret their results, or do not address how IRR affects the power of their subsequent analyses for hypothesis testing. This paper provides an overview of methodological issues related to the assessment of IRR with a focus on study design, selection of appropriate statistics, and the computation, interpretation, and reporting of some commonly-used IRR statistics. Computational examples include SPSS and R syntax for computing Cohen’s kappa and intra-class correlations to assess IRR. PMID:22833776

Design and fabrication of composite wing panels containing a production splice

NASA Technical Reports Server (NTRS)

Reed, D. L.

1975-01-01

Bolted specimens representative of both upper and lower wing surface splices of a transport aircraft were designed and manufactured for static and random load tension and compression fatigue testing including ground-air-ground load reversals. The specimens were fabricated with graphite-epoxy composite material. Multiple tests were conducted at various load levels and the results were used as input to a statistical wearout model. The statically designed specimens performed very well under highly magnified fatigue loadings. Two large panels, one tension and compression, were fabricated for testing by NASA-LRC.

Gene genealogies for genetic association mapping, with application to Crohn's disease

PubMed Central

Burkett, Kelly M.; Greenwood, Celia M. T.; McNeney, Brad; Graham, Jinko

2013-01-01

A gene genealogy describes relationships among haplotypes sampled from a population. Knowledge of the gene genealogy for a set of haplotypes is useful for estimation of population genetic parameters and it also has potential application in finding disease-predisposing genetic variants. As the true gene genealogy is unknown, Markov chain Monte Carlo (MCMC) approaches have been used to sample genealogies conditional on data at multiple genetic markers. We previously implemented an MCMC algorithm to sample from an approximation to the distribution of the gene genealogy conditional on haplotype data. Our approach samples ancestral trees, recombination and mutation rates at a genomic focal point. In this work, we describe how our sampler can be used to find disease-predisposing genetic variants in samples of cases and controls. We use a tree-based association statistic that quantifies the degree to which case haplotypes are more closely related to each other around the focal point than control haplotypes, without relying on a disease model. As the ancestral tree is a latent variable, so is the tree-based association statistic. We show how the sampler can be used to estimate the posterior distribution of the latent test statistic and corresponding latent p-values, which together comprise a fuzzy p-value. We illustrate the approach on a publicly-available dataset from a study of Crohn's disease that consists of genotypes at multiple SNP markers in a small genomic region. We estimate the posterior distribution of the tree-based association statistic and the recombination rate at multiple focal points in the region. Reassuringly, the posterior mean recombination rates estimated at the different focal points are consistent with previously published estimates. The tree-based association approach finds multiple sub-regions where the case haplotypes are more genetically related than the control haplotypes, and that there may be one or multiple disease-predisposing loci. PMID:24348515

A novel statistical method for quantitative comparison of multiple ChIP-seq datasets.

PubMed

Chen, Li; Wang, Chi; Qin, Zhaohui S; Wu, Hao

2015-06-15

ChIP-seq is a powerful technology to measure the protein binding or histone modification strength in the whole genome scale. Although there are a number of methods available for single ChIP-seq data analysis (e.g. 'peak detection'), rigorous statistical method for quantitative comparison of multiple ChIP-seq datasets with the considerations of data from control experiment, signal to noise ratios, biological variations and multiple-factor experimental designs is under-developed. In this work, we develop a statistical method to perform quantitative comparison of multiple ChIP-seq datasets and detect genomic regions showing differential protein binding or histone modification. We first detect peaks from all datasets and then union them to form a single set of candidate regions. The read counts from IP experiment at the candidate regions are assumed to follow Poisson distribution. The underlying Poisson rates are modeled as an experiment-specific function of artifacts and biological signals. We then obtain the estimated biological signals and compare them through the hypothesis testing procedure in a linear model framework. Simulations and real data analyses demonstrate that the proposed method provides more accurate and robust results compared with existing ones. An R software package ChIPComp is freely available at http://web1.sph.emory.edu/users/hwu30/software/ChIPComp.html. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Prediction system of hydroponic plant growth and development using algorithm Fuzzy Mamdani method

NASA Astrophysics Data System (ADS)

Sudana, I. Made; Purnawirawan, Okta; Arief, Ulfa Mediaty

2017-03-01

Hydroponics is a method of farming without soil. One of the Hydroponic plants is Watercress (Nasturtium Officinale). The development and growth process of hydroponic Watercress was influenced by levels of nutrients, acidity and temperature. The independent variables can be used as input variable system to predict the value level of plants growth and development. The prediction system is using Fuzzy Algorithm Mamdani method. This system was built to implement the function of Fuzzy Inference System (Fuzzy Inference System/FIS) as a part of the Fuzzy Logic Toolbox (FLT) by using MATLAB R2007b. FIS is a computing system that works on the principle of fuzzy reasoning which is similar to humans' reasoning. Basically FIS consists of four units which are fuzzification unit, fuzzy logic reasoning unit, base knowledge unit and defuzzification unit. In addition to know the effect of independent variables on the plants growth and development that can be visualized with the function diagram of FIS output surface that is shaped three-dimensional, and statistical tests based on the data from the prediction system using multiple linear regression method, which includes multiple linear regression analysis, T test, F test, the coefficient of determination and donations predictor that are calculated using SPSS (Statistical Product and Service Solutions) software applications.

Tests for a disease-susceptibility locus allowing for an inbreeding coefficient (F).

PubMed

Song, Kijoung; Elston, Robert C

2003-11-01

We begin by discussing the false positive test results that arise because of cryptic relatedness and population substructure when testing a disease susceptibility locus. We extend and evaluate the Hardy-Weinberg disequilibrium (HWD) method, allowing for an inbreeding coefficient (F) in a similar way that Devlin and Roeder (1999) allowed for inbreeding in a case-control study. Then we compare the HWD measure and the common direct measure of linkage disequilibrium, both when there is no population substructure (F = 0) and when there is population substructure (F not = 0), for a single marker. The HWD test statistic gives rise to false positives caused by population stratification. These false positives can be controlled by adjusting the test statistic for the amount of variance inflation caused by the inbreeding coefficient (F). The power loss for the HWD test that arises when controlling for population structure is much less than that which arises for the common direct measure of linkage disequilibrium. However, in the multiplicative model, the HWD test has virtually no power even when allowing for non-zero F.

Meta-analysis of diagnostic test data: a bivariate Bayesian modeling approach.

PubMed

Verde, Pablo E

2010-12-30

In the last decades, the amount of published results on clinical diagnostic tests has expanded very rapidly. The counterpart to this development has been the formal evaluation and synthesis of diagnostic results. However, published results present substantial heterogeneity and they can be regarded as so far removed from the classical domain of meta-analysis, that they can provide a rather severe test of classical statistical methods. Recently, bivariate random effects meta-analytic methods, which model the pairs of sensitivities and specificities, have been presented from the classical point of view. In this work a bivariate Bayesian modeling approach is presented. This approach substantially extends the scope of classical bivariate methods by allowing the structural distribution of the random effects to depend on multiple sources of variability. Meta-analysis is summarized by the predictive posterior distributions for sensitivity and specificity. This new approach allows, also, to perform substantial model checking, model diagnostic and model selection. Statistical computations are implemented in the public domain statistical software (WinBUGS and R) and illustrated with real data examples. Copyright © 2010 John Wiley & Sons, Ltd.

Fukunaga-Koontz feature transformation for statistical structural damage detection and hierarchical neuro-fuzzy damage localisation

NASA Astrophysics Data System (ADS)

Hoell, Simon; Omenzetter, Piotr

2017-07-01

Considering jointly damage sensitive features (DSFs) of signals recorded by multiple sensors, applying advanced transformations to these DSFs and assessing systematically their contribution to damage detectability and localisation can significantly enhance the performance of structural health monitoring systems. This philosophy is explored here for partial autocorrelation coefficients (PACCs) of acceleration responses. They are interrogated with the help of the linear discriminant analysis based on the Fukunaga-Koontz transformation using datasets of the healthy and selected reference damage states. Then, a simple but efficient fast forward selection procedure is applied to rank the DSF components with respect to statistical distance measures specialised for either damage detection or localisation. For the damage detection task, the optimal feature subsets are identified based on the statistical hypothesis testing. For damage localisation, a hierarchical neuro-fuzzy tool is developed that uses the DSF ranking to establish its own optimal architecture. The proposed approaches are evaluated experimentally on data from non-destructively simulated damage in a laboratory scale wind turbine blade. The results support our claim of being able to enhance damage detectability and localisation performance by transforming and optimally selecting DSFs. It is demonstrated that the optimally selected PACCs from multiple sensors or their Fukunaga-Koontz transformed versions can not only improve the detectability of damage via statistical hypothesis testing but also increase the accuracy of damage localisation when used as inputs into a hierarchical neuro-fuzzy network. Furthermore, the computational effort of employing these advanced soft computing models for damage localisation can be significantly reduced by using transformed DSFs.

Statistical analysis of long-term monitoring data for persistent organic pollutants in the atmosphere at 20 monitoring stations broadly indicates declining concentrations.

PubMed

Kong, Deguo; MacLeod, Matthew; Hung, Hayley; Cousins, Ian T

2014-11-04

During recent decades concentrations of persistent organic pollutants (POPs) in the atmosphere have been monitored at multiple stations worldwide. We used three statistical methods to analyze a total of 748 time series of selected POPs in the atmosphere to determine if there are statistically significant reductions in levels of POPs that have had control actions enacted to restrict or eliminate manufacture, use and emissions. Significant decreasing trends were identified in 560 (75%) of the 748 time series collected from the Arctic, North America, and Europe, indicating that the atmospheric concentrations of these POPs are generally decreasing, consistent with the overall effectiveness of emission control actions. Statistically significant trends in synthetic time series could be reliably identified with the improved Mann-Kendall (iMK) test and the digital filtration (DF) technique in time series longer than 5 years. The temporal trends of new (or emerging) POPs in the atmosphere are often unclear because time series are too short. A statistical detrending method based on the iMK test was not able to identify abrupt changes in the rates of decline of atmospheric POP concentrations encoded into synthetic time series.

Commentary: Decaying Numerical Skills. "I Can't Divide by 60 in My Head!"

ERIC Educational Resources Information Center

Parslow, Graham R.

2010-01-01

As an undergraduate in the 1960s, the author mostly used a slide rule for calculations and a Marchant-brand motor-operated mechanical calculator for statistics. This was after an elementary education replete with learning multiplication tables and taking speed and accuracy tests in arithmetic. Times have changed and assuming even basic calculation…

Market structure in U.S. southern pine roundwood

Treesearch

Matthew F. Bingham; Jeffrey P. Prestemon; Douglas J. MacNair; Robert C. Abt

2003-01-01

Time series of commodity prices from multiple locations can behave as if responding to forces of spatial arbitrage. cvcn while such prices may instead be responding similarly to common factors aside from spatial arbitrage. Hence, while the Law of One Price may hold as a statistical concept, its acceptance is not sufficient to conclude market integration. We tested...

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers. PMID:28264422

Conceptual and statistical problems associated with the use of diversity indices in ecology.

PubMed

Barrantes, Gilbert; Sandoval, Luis

2009-09-01

Diversity indices, particularly the Shannon-Wiener index, have extensively been used in analyzing patterns of diversity at different geographic and ecological scales. These indices have serious conceptual and statistical problems which make comparisons of species richness or species abundances across communities nearly impossible. There is often no a single statistical method that retains all information needed to answer even a simple question. However, multivariate analyses could be used instead of diversity indices, such as cluster analyses or multiple regressions. More complex multivariate analyses, such as Canonical Correspondence Analysis, provide very valuable information on environmental variables associated to the presence and abundance of the species in a community. In addition, particular hypotheses associated to changes in species richness across localities, or change in abundance of one, or a group of species can be tested using univariate, bivariate, and/or rarefaction statistical tests. The rarefaction method has proved to be robust to standardize all samples to a common size. Even the simplest method as reporting the number of species per taxonomic category possibly provides more information than a diversity index value.

HYPOTHESIS SETTING AND ORDER STATISTIC FOR ROBUST GENOMIC META-ANALYSIS.

PubMed

Song, Chi; Tseng, George C

2014-01-01

Meta-analysis techniques have been widely developed and applied in genomic applications, especially for combining multiple transcriptomic studies. In this paper, we propose an order statistic of p-values ( r th ordered p-value, rOP) across combined studies as the test statistic. We illustrate different hypothesis settings that detect gene markers differentially expressed (DE) "in all studies", "in the majority of studies", or "in one or more studies", and specify rOP as a suitable method for detecting DE genes "in the majority of studies". We develop methods to estimate the parameter r in rOP for real applications. Statistical properties such as its asymptotic behavior and a one-sided testing correction for detecting markers of concordant expression changes are explored. Power calculation and simulation show better performance of rOP compared to classical Fisher's method, Stouffer's method, minimum p-value method and maximum p-value method under the focused hypothesis setting. Theoretically, rOP is found connected to the naïve vote counting method and can be viewed as a generalized form of vote counting with better statistical properties. The method is applied to three microarray meta-analysis examples including major depressive disorder, brain cancer and diabetes. The results demonstrate rOP as a more generalizable, robust and sensitive statistical framework to detect disease-related markers.

Clonality: an R package for testing clonal relatedness of two tumors from the same patient based on their genomic profiles.

PubMed

Ostrovnaya, Irina; Seshan, Venkatraman E; Olshen, Adam B; Begg, Colin B

2011-06-15

If a cancer patient develops multiple tumors, it is sometimes impossible to determine whether these tumors are independent or clonal based solely on pathological characteristics. Investigators have studied how to improve this diagnostic challenge by comparing the presence of loss of heterozygosity (LOH) at selected genetic locations of tumor samples, or by comparing genomewide copy number array profiles. We have previously developed statistical methodology to compare such genomic profiles for an evidence of clonality. We assembled the software for these tests in a new R package called 'Clonality'. For LOH profiles, the package contains significance tests. The analysis of copy number profiles includes a likelihood ratio statistic and reference distribution, as well as an option to produce various plots that summarize the results. Bioconductor (http://bioconductor.org/packages/release/bioc/html/Clonality.html) and http://www.mskcc.org/mskcc/html/13287.cfm.

Disconnection as a mechanism for social cognition impairment in multiple sclerosis.

PubMed

Batista, Sonia; Alves, Carolina; d'Almeida, Otília C; Afonso, Ana; Félix-Morais, Ricardo; Pereira, João; Macário, Carmo; Sousa, Lívia; Castelo-Branco, Miguel; Santana, Isabel; Cunha, Luís

2017-07-04

To assess the contribution of microstructural normal-appearing white matter (NAWM) damage to social cognition impairment, specifically in the theory of mind (ToM), in multiple sclerosis (MS). We enrolled consecutively 60 patients with MS and 60 healthy controls (HC) matched on age, sex, and education level. All participants underwent ToM testing (Eyes Test, Videos Test) and 3T brain MRI including conventional and diffusion tensor imaging sequences. Tract-based spatial statistics (TBSS) were applied for whole-brain voxel-wise analysis of fractional anisotropy (FA) and mean diffusivity (MD) on NAWM. Patients with MS performed worse on both tasks of ToM compared to HC (Eyes Test 58.7 ± 13.8 vs 81.9 ± 10.4, p < 0.001, Hedges g -1.886; Videos Test 75.3 ± 9.3 vs 88.1 ± 7.1, p < 0.001, Hedges g -1.537). Performance on ToM tests was correlated with higher values of FA and lower values of MD across widespread white matter tracts. The largest effects (≥90% of voxels with statistical significance) for the Eyes Test were body and genu of corpus callosum, fornix, tapetum, uncinate fasciculus, and left inferior cerebellar peduncle, and for the Videos Test genu and splenium of corpus callosum, fornix, uncinate fasciculus, left tapetum, and right superior fronto-occipital fasciculus. These results indicate that a diffuse pattern of NAWM damage in MS contributes to social cognition impairment in the ToM domain, probably due to a mechanism of disconnection within the social brain network. Gray matter pathology is also expected to have an important role; thus further research is required to clarify the neural basis of social cognition impairment in MS. © 2017 American Academy of Neurology.

Lifetime Prediction for Degradation of Solar Mirrors using Step-Stress Accelerated Testing (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, J.; Elmore, R.; Kennedy, C.

This research is to illustrate the use of statistical inference techniques in order to quantify the uncertainty surrounding reliability estimates in a step-stress accelerated degradation testing (SSADT) scenario. SSADT can be used when a researcher is faced with a resource-constrained environment, e.g., limits on chamber time or on the number of units to test. We apply the SSADT methodology to a degradation experiment involving concentrated solar power (CSP) mirrors and compare the results to a more traditional multiple accelerated testing paradigm. Specifically, our work includes: (1) designing a durability testing plan for solar mirrors (3M's new improved silvered acrylic "Solarmore » Reflector Film (SFM) 1100") through the ultra-accelerated weathering system (UAWS), (2) defining degradation paths of optical performance based on the SSADT model which is accelerated by high UV-radiant exposure, and (3) developing service lifetime prediction models for solar mirrors using advanced statistical inference. We use the method of least squares to estimate the model parameters and this serves as the basis for the statistical inference in SSADT. Several quantities of interest can be estimated from this procedure, e.g., mean-time-to-failure (MTTF) and warranty time. The methods allow for the estimation of quantities that may be of interest to the domain scientists.« less

Potential Values of Incorporating a Multiple-Choice Question Construction in Physics Experimentation Instruction

NASA Astrophysics Data System (ADS)

Yu, Fu-Yun; Liu, Yu-Hsin

2005-09-01

The potential value of a multiple-choice question-construction instructional strategy for the support of students’ learning of physics experiments was examined in the study. Forty-two university freshmen participated in the study for a whole semester. A constant comparison method adopted to categorize students’ qualitative data indicated that the influences of multiple-choice question construction were evident in several significant ways (promoting constructive and productive studying habits; reflecting and previewing course-related materials; increasing in-group communication and interaction; breaking passive learning style and habits, etc.), which, worked together, not only enhanced students’ comprehension and retention of the obtained knowledge, but also helped distil a sense of empowerment and learning community within the participants. Analysis with one-group t-tests, using 3 as the expected mean, on quantitative data further found that students’ satisfaction toward past learning experience, and perceptions toward this strategy’s potentials for promoting learning were statistically significant at the 0.0005 level, while learning anxiety was not statistically significant. Suggestions for incorporating question-generation activities within classroom and topics for future studies were rendered.

Properties of different selection signature statistics and a new strategy for combining them.

PubMed

Ma, Y; Ding, X; Qanbari, S; Weigend, S; Zhang, Q; Simianer, H

2015-11-01

Identifying signatures of recent or ongoing selection is of high relevance in livestock population genomics. From a statistical perspective, determining a proper testing procedure and combining various test statistics is challenging. On the basis of extensive simulations in this study, we discuss the statistical properties of eight different established selection signature statistics. In the considered scenario, we show that a reasonable power to detect selection signatures is achieved with high marker density (>1 SNP/kb) as obtained from sequencing, while rather small sample sizes (~15 diploid individuals) appear to be sufficient. Most selection signature statistics such as composite likelihood ratio and cross population extended haplotype homozogysity have the highest power when fixation of the selected allele is reached, while integrated haplotype score has the highest power when selection is ongoing. We suggest a novel strategy, called de-correlated composite of multiple signals (DCMS) to combine different statistics for detecting selection signatures while accounting for the correlation between the different selection signature statistics. When examined with simulated data, DCMS consistently has a higher power than most of the single statistics and shows a reliable positional resolution. We illustrate the new statistic to the established selective sweep around the lactase gene in human HapMap data providing further evidence of the reliability of this new statistic. Then, we apply it to scan selection signatures in two chicken samples with diverse skin color. Our analysis suggests that a set of well-known genes such as BCO2, MC1R, ASIP and TYR were involved in the divergent selection for this trait.

No-Reference Video Quality Assessment Based on Statistical Analysis in 3D-DCT Domain.

PubMed

Li, Xuelong; Guo, Qun; Lu, Xiaoqiang

2016-05-13

It is an important task to design models for universal no-reference video quality assessment (NR-VQA) in multiple video processing and computer vision applications. However, most existing NR-VQA metrics are designed for specific distortion types which are not often aware in practical applications. A further deficiency is that the spatial and temporal information of videos is hardly considered simultaneously. In this paper, we propose a new NR-VQA metric based on the spatiotemporal natural video statistics (NVS) in 3D discrete cosine transform (3D-DCT) domain. In the proposed method, a set of features are firstly extracted based on the statistical analysis of 3D-DCT coefficients to characterize the spatiotemporal statistics of videos in different views. These features are used to predict the perceived video quality via the efficient linear support vector regression (SVR) model afterwards. The contributions of this paper are: 1) we explore the spatiotemporal statistics of videos in 3DDCT domain which has the inherent spatiotemporal encoding advantage over other widely used 2D transformations; 2) we extract a small set of simple but effective statistical features for video visual quality prediction; 3) the proposed method is universal for multiple types of distortions and robust to different databases. The proposed method is tested on four widely used video databases. Extensive experimental results demonstrate that the proposed method is competitive with the state-of-art NR-VQA metrics and the top-performing FR-VQA and RR-VQA metrics.

[Evaluation of using statistical methods in selected national medical journals].

PubMed

Sych, Z

1996-01-01

The paper covers the performed evaluation of frequency with which the statistical methods were applied in analyzed works having been published in six selected, national medical journals in the years 1988-1992. For analysis the following journals were chosen, namely: Klinika Oczna, Medycyna Pracy, Pediatria Polska, Polski Tygodnik Lekarski, Roczniki Państwowego Zakładu Higieny, Zdrowie Publiczne. Appropriate number of works up to the average in the remaining medical journals was randomly selected from respective volumes of Pol. Tyg. Lek. The studies did not include works wherein the statistical analysis was not implemented, which referred both to national and international publications. That exemption was also extended to review papers, casuistic ones, reviews of books, handbooks, monographies, reports from scientific congresses, as well as papers on historical topics. The number of works was defined in each volume. Next, analysis was performed to establish the mode of finding out a suitable sample in respective studies, differentiating two categories: random and target selections. Attention was also paid to the presence of control sample in the individual works. In the analysis attention was also focussed on the existence of sample characteristics, setting up three categories: complete, partial and lacking. In evaluating the analyzed works an effort was made to present the results of studies in tables and figures (Tab. 1, 3). Analysis was accomplished with regard to the rate of employing statistical methods in analyzed works in relevant volumes of six selected, national medical journals for the years 1988-1992, simultaneously determining the number of works, in which no statistical methods were used. Concurrently the frequency of applying the individual statistical methods was analyzed in the scrutinized works. Prominence was given to fundamental statistical methods in the field of descriptive statistics (measures of position, measures of dispersion) as well as most important methods of mathematical statistics such as parametric tests of significance, analysis of variance (in single and dual classifications). non-parametric tests of significance, correlation and regression. The works, in which use was made of either multiple correlation or multiple regression or else more complex methods of studying the relationship for two or more numbers of variables, were incorporated into the works whose statistical methods were constituted by correlation and regression as well as other methods, e.g. statistical methods being used in epidemiology (coefficients of incidence and morbidity, standardization of coefficients, survival tables) factor analysis conducted by Jacobi-Hotellng's method, taxonomic methods and others. On the basis of the performed studies it has been established that the frequency of employing statistical methods in the six selected national, medical journals in the years 1988-1992 was 61.1-66.0% of the analyzed works (Tab. 3), and they generally were almost similar to the frequency provided in English language medical journals. On a whole, no significant differences were disclosed in the frequency of applied statistical methods (Tab. 4) as well as in frequency of random tests (Tab. 3) in the analyzed works, appearing in the medical journals in respective years 1988-1992. The most frequently used statistical methods in analyzed works for 1988-1992 were the measures of position 44.2-55.6% and measures of dispersion 32.5-38.5% as well as parametric tests of significance 26.3-33.1% of the works analyzed (Tab. 4). For the purpose of increasing the frequency and reliability of the used statistical methods, the didactics should be widened in the field of biostatistics at medical studies and postgraduation training designed for physicians and scientific-didactic workers.

An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance.

PubMed

Gordon, Derek; Londono, Douglas; Patel, Payal; Kim, Wonkuk; Finch, Stephen J; Heiman, Gary A

2016-01-01

Our motivation here is to calculate the power of 3 statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected) and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend the analytic power and minimum-sample-size-necessary (MSSN) formulas for 2 categorical data-based tests (genotype, linear trend test [LTT]) of genetic association to the pleiotropic model. We further compare the MSSN of the genotype test and the LTT with that of a multivariate ANOVA (Pillai). We approximate the MSSN for statistics by linear models using a factorial design and ANOVA. With ANOVA decomposition, we determine which factors most significantly change the power/MSSN for all statistics. Finally, we determine which test statistics have the smallest MSSN. In this work, MSSN calculations are for 2 traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the genotype test usually has lower MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% vs. top/bottom 10%) have higher sample size requirements. The Pillai test has a much larger MSSN than both the genotype test and the LTT, as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes. © 2017 S. Karger AG, Basel.

Stereotype threat? Effects of inquiring about test takers' gender on conceptual test performance in physics

NASA Astrophysics Data System (ADS)

Maries, Alexandru; Singh, Chandralekha

2015-12-01

It has been found that activation of a stereotype, for example by indicating one's gender before a test, typically alters performance in a way consistent with the stereotype, an effect called "stereotype threat." On a standardized conceptual physics assessment, we found that asking test takers to indicate their gender right before taking the test did not deteriorate performance compared to an equivalent group who did not provide gender information. Although a statistically significant gender gap was present on the standardized test whether or not students indicated their gender, no gender gap was observed on the multiple-choice final exam students took, which included both quantitative and conceptual questions on similar topics.

Surface hardness evaluation of different composite resin materials: influence of sports and energy drinks immersion after a short-term period

PubMed Central

ERDEMİR, Ugur; YİLDİZ, Esra; EREN, Meltem Mert; OZEL, Sevda

2013-01-01

Objectives: This study evaluated the effect of sports and energy drinks on the surface hardness of different composite resin restorative materials over a 1-month period. Material and Methods: A total of 168 specimens: Compoglass F, Filtek Z250, Filtek Supreme, and Premise were prepared using a customized cylindrical metal mould and they were divided into six groups (N=42; n=7 per group). For the control groups, the specimens were stored in distilled water for 24 hours at 37º C and the water was renewed daily. For the experimental groups, the specimens were immersed in 5 mL of one of the following test solutions: Powerade, Gatorade, X-IR, Burn, and Red Bull, for two minutes daily for up to a 1-month test period and all the solutions were refreshed daily. Surface hardness was measured using a Vickers hardness measuring instrument at baseline, after 1-week and 1-month. Data were statistically analyzed using Multivariate repeated measure ANOVA and Bonferroni's multiple comparison tests (α=0.05). Results: Multivariate repeated measures ANOVA revealed that there were statistically significant differences in the hardness of the restorative materials in different immersion times (p<0.001) in different solutions (p<0.001). The effect of different solutions on the surface hardness values of the restorative materials was tested using Bonferroni's multiple comparison tests, and it was observed that specimens stored in distilled water demonstrated statistically significant lower mean surface hardness reductions when compared to the specimens immersed in sports and energy drinks after a 1-month evaluation period (p<0.001). The compomer was the most affected by an acidic environment, whereas the composite resin materials were the least affected materials. Conclusions: The effect of sports and energy drinks on the surface hardness of a restorative material depends on the duration of exposure time, and the composition of the material. PMID:23739850

Mortality investigation of workers in an electromagnetic pulse test program.

PubMed

Muhm, J M

1992-03-01

A standardized mortality ratio study of 304 male employees of an electromagnetic pulse (EMP) test program was conducted. Outcomes were ascertained by two methods: the World Health Organization's underlying cause of death algorithm; and the National Center for Health Statistics' algorithm to identify multiple listed causes of death. In the 3362 person-years of follow-up, there was one underlying cause of death due to leukemia compared with with 0.2 expected (standard mortality ratio [SMR] = 437, 95% confidence interval [CI] = 11-2433), and two multiple listed causes of death due to leukemia compared with 0.3 expected (SMR = 775, 95% CI = 94-2801). Although the study suggested an association between death due to leukemia and employment in the EMP test program, firm conclusions could not be drawn because of limitations of the study. The findings warrant further investigation in an independent cohort.

MUSCLE: multiple sequence alignment with high accuracy and high throughput.

PubMed

Edgar, Robert C

2004-01-01

We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

Replicates in high dimensions, with applications to latent variable graphical models.

PubMed

Tan, Kean Ming; Ning, Yang; Witten, Daniela M; Liu, Han

2016-12-01

In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in this setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By collecting multiple replicates for each subject, we are able to estimate the conditional dependence relationships among the observed variables given the latent variables. To test the null hypothesis of conditional independence between two observed variables, we propose a pairwise decorrelated score test. Theoretical guarantees are established for parameter estimation and for this test. We show that our proposal is able to estimate latent variable graphical models more accurately than some existing proposals, and apply the proposed method to a brain imaging dataset.

Detecting a Weak Association by Testing its Multiple Perturbations: a Data Mining Approach

NASA Astrophysics Data System (ADS)

Lo, Min-Tzu; Lee, Wen-Chung

2014-05-01

Many risk factors/interventions in epidemiologic/biomedical studies are of minuscule effects. To detect such weak associations, one needs a study with a very large sample size (the number of subjects, n). The n of a study can be increased but unfortunately only to an extent. Here, we propose a novel method which hinges on increasing sample size in a different direction-the total number of variables (p). We construct a p-based `multiple perturbation test', and conduct power calculations and computer simulations to show that it can achieve a very high power to detect weak associations when p can be made very large. As a demonstration, we apply the method to analyze a genome-wide association study on age-related macular degeneration and identify two novel genetic variants that are significantly associated with the disease. The p-based method may set a stage for a new paradigm of statistical tests.

Estimating the Probability of Traditional Copying, Conditional on Answer-Copying Statistics.

PubMed

Allen, Jeff; Ghattas, Andrew

2016-06-01

Statistics for detecting copying on multiple-choice tests produce p values measuring the probability of a value at least as large as that observed, under the null hypothesis of no copying. The posterior probability of copying is arguably more relevant than the p value, but cannot be derived from Bayes' theorem unless the population probability of copying and probability distribution of the answer-copying statistic under copying are known. In this article, the authors develop an estimator for the posterior probability of copying that is based on estimable quantities and can be used with any answer-copying statistic. The performance of the estimator is evaluated via simulation, and the authors demonstrate how to apply the formula using actual data. Potential uses, generalizability to other types of cheating, and limitations of the approach are discussed.

Sensor Compromise Detection in Multiple-Target Tracking Systems

PubMed Central

Doucette, Emily A.; Curtis, Jess W.

2018-01-01

Tracking multiple targets using a single estimator is a problem that is commonly approached within a trusted framework. There are many weaknesses that an adversary can exploit if it gains control over the sensors. Because the number of targets that the estimator has to track is not known with anticipation, an adversary could cause a loss of information or a degradation in the tracking precision. Other concerns include the introduction of false targets, which would result in a waste of computational and material resources, depending on the application. In this work, we study the problem of detecting compromised or faulty sensors in a multiple-target tracker, starting with the single-sensor case and then considering the multiple-sensor scenario. We propose an algorithm to detect a variety of attacks in the multiple-sensor case, via the application of finite set statistics (FISST), one-class classifiers and hypothesis testing using nonparametric techniques. PMID:29466314

Resting-state fMRI data reflects default network activity rather than null data: A defense of commonly employed methods to correct for multiple comparisons.

PubMed

Slotnick, Scott D

2017-07-01

Analysis of functional magnetic resonance imaging (fMRI) data typically involves over one hundred thousand independent statistical tests; therefore, it is necessary to correct for multiple comparisons to control familywise error. In a recent paper, Eklund, Nichols, and Knutsson used resting-state fMRI data to evaluate commonly employed methods to correct for multiple comparisons and reported unacceptable rates of familywise error. Eklund et al.'s analysis was based on the assumption that resting-state fMRI data reflect null data; however, their 'null data' actually reflected default network activity that inflated familywise error. As such, Eklund et al.'s results provide no basis to question the validity of the thousands of published fMRI studies that have corrected for multiple comparisons or the commonly employed methods to correct for multiple comparisons.

Detection of multiple perturbations in multi-omics biological networks.

PubMed

Griffin, Paula J; Zhang, Yuqing; Johnson, William Evan; Kolaczyk, Eric D

2018-05-17

Cellular mechanism-of-action is of fundamental concern in many biological studies. It is of particular interest for identifying the cause of disease and learning the way in which treatments act against disease. However, pinpointing such mechanisms is difficult, due to the fact that small perturbations to the cell can have wide-ranging downstream effects. Given a snapshot of cellular activity, it can be challenging to tell where a disturbance originated. The presence of an ever-greater variety of high-throughput biological data offers an opportunity to examine cellular behavior from multiple angles, but also presents the statistical challenge of how to effectively analyze data from multiple sources. In this setting, we propose a method for mechanism-of-action inference by extending network filtering to multi-attribute data. We first estimate a joint Gaussian graphical model across multiple data types using penalized regression and filter for network effects. We then apply a set of likelihood ratio tests to identify the most likely site of the original perturbation. In addition, we propose a conditional testing procedure to allow for detection of multiple perturbations. We demonstrate this methodology on paired gene expression and methylation data from The Cancer Genome Atlas (TCGA). © 2018, The International Biometric Society.

Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses.

PubMed

Lujan, J Luis; Crago, Patrick E

2009-01-01

This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-DOF, motor system neural prostheses. The design process is based on experimental measurement of the forward input/output properties of the neuromechanical system and numerical optimization of stimulation patterns to meet muscle coactivation criteria, thus resolving the muscle redundancy (i.e., overcontrol) and the coupled DOF problems inherent in neuromechanical systems. We designed feedforward controllers to control the isometric forces at the tip of the thumb in two directions during stimulation of three thumb muscles as a model system. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. Good control of isometric force in both DOFs was observed, with rms errors less than 10% of the force range in seven experiments and statistically significant correlations between the actual and target forces in all ten experiments. Systematic bias and slope errors were observed in a few experiments, likely due to the neuromuscular fatigue. Overall, the tests demonstrated the ability of a general design approach to satisfy both control and coactivation criteria in multiple-muscle, multiple-axis neuromechanical systems, which is applicable to a wide range of neuromechanical systems and stimulation electrodes.

Statistical Analysis of CFD Solutions From the Fifth AIAA Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

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.

Testing Genetic Pleiotropy with GWAS Summary Statistics for Marginal and Conditional Analyses.

PubMed

Deng, Yangqing; Pan, Wei

2017-12-01

There is growing interest in testing genetic pleiotropy, which is when a single genetic variant influences multiple traits. Several methods have been proposed; however, these methods have some limitations. First, all the proposed methods are based on the use of individual-level genotype and phenotype data; in contrast, for logistical, and other, reasons, summary statistics of univariate SNP-trait associations are typically only available based on meta- or mega-analyzed large genome-wide association study (GWAS) data. Second, existing tests are based on marginal pleiotropy, which cannot distinguish between direct and indirect associations of a single genetic variant with multiple traits due to correlations among the traits. Hence, it is useful to consider conditional analysis, in which a subset of traits is adjusted for another subset of traits. For example, in spite of substantial lowering of low-density lipoprotein cholesterol (LDL) with statin therapy, some patients still maintain high residual cardiovascular risk, and, for these patients, it might be helpful to reduce their triglyceride (TG) level. For this purpose, in order to identify new therapeutic targets, it would be useful to identify genetic variants with pleiotropic effects on LDL and TG after adjusting the latter for LDL; otherwise, a pleiotropic effect of a genetic variant detected by a marginal model could simply be due to its association with LDL only, given the well-known correlation between the two types of lipids. Here, we develop a new pleiotropy testing procedure based only on GWAS summary statistics that can be applied for both marginal analysis and conditional analysis. Although the main technical development is based on published union-intersection testing methods, care is needed in specifying conditional models to avoid invalid statistical estimation and inference. In addition to the previously used likelihood ratio test, we also propose using generalized estimating equations under the working independence model for robust inference. We provide numerical examples based on both simulated and real data, including two large lipid GWAS summary association datasets based on ∼100,000 and ∼189,000 samples, respectively, to demonstrate the difference between marginal and conditional analyses, as well as the effectiveness of our new approach. Copyright © 2017 by the Genetics Society of America.

Advanced statistics: linear regression, part II: multiple linear regression.

PubMed

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Estimation of the Percentage of Newly Diagnosed HIV-Positive Persons Linked to HIV Medical Care in CDC-Funded HIV Testing Programs.

PubMed

Wang, Guoshen; Pan, Yi; Seth, Puja; Song, Ruiguang; Belcher, Lisa

2017-01-01

Missing data create challenges for determining progress made in linking HIV-positive persons to HIV medical care. Statistical methods are not used to address missing program data on linkage. In 2014, 61 health department jurisdictions were funded by Centers for Disease Control and Prevention (CDC) and submitted data on HIV testing, newly diagnosed HIV-positive persons, and linkage to HIV medical care. Missing or unusable data existed in our data set. A new approach using multiple imputation to address missing linkage data was proposed, and results were compared to the current approach that uses data with complete information. There were 12,472 newly diagnosed HIV-positive persons from CDC-funded HIV testing events in 2014. Using multiple imputation, 94.1% (95% confidence interval (CI): [93.7%, 94.6%]) of newly diagnosed persons were referred to HIV medical care, 88.6% (95% CI: [88.0%, 89.1%]) were linked to care within any time frame, and 83.6% (95% CI: [83.0%, 84.3%]) were linked to care within 90 days. Multiple imputation is recommended for addressing missing linkage data in future analyses when the missing percentage is high. The use of multiple imputation for missing values can result in a better understanding of how programs are performing on key HIV testing and HIV service delivery indicators.

Test order in teacher-rated behavior assessments: Is counterbalancing necessary?

PubMed

Kooken, Janice; Welsh, Megan E; McCoach, D Betsy; Miller, Faith G; Chafouleas, Sandra M; Riley-Tillman, T Chris; Fabiano, Gregory

2017-01-01

Counterbalancing treatment order in experimental research design is well established as an option to reduce threats to internal validity, but in educational and psychological research, the effect of varying the order of multiple tests to a single rater has not been examined and is rarely adhered to in practice. The current study examines the effect of test order on measures of student behavior by teachers as raters utilizing data from a behavior measure validation study. Using multilevel modeling to control for students nested within teachers, the effect of rating an earlier measure on the intercept or slope of a later behavior assessment was statistically significant in 22% of predictor main effects for the spring test period. Test order effects had potential for high stakes consequences with differences large enough to change risk classification. Results suggest that researchers and practitioners in classroom settings using multiple measures evaluate the potential impact of test order. Where possible, they should counterbalance when the risk of an order effect exists and report justification for the decision to not counterbalance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Application of Bayesian methods to habitat selection modeling of the northern spotted owl in California: new statistical methods for wildlife research

Treesearch

Howard B. Stauffer; Cynthia J. Zabel; Jeffrey R. Dunk

2005-01-01

We compared a set of competing logistic regression habitat selection models for Northern Spotted Owls (Strix occidentalis caurina) in California. The habitat selection models were estimated, compared, evaluated, and tested using multiple sample datasets collected on federal forestlands in northern California. We used Bayesian methods in interpreting...

An Alternative to the 3PL: Using Asymmetric Item Characteristic Curves to Address Guessing Effects

ERIC Educational Resources Information Center

Lee, Sora; Bolt, Daniel M.

2018-01-01

Both the statistical and interpretational shortcomings of the three-parameter logistic (3PL) model in accommodating guessing effects on multiple-choice items are well documented. We consider the use of a residual heteroscedasticity (RH) model as an alternative, and compare its performance to the 3PL with real test data sets and through simulation…

Strength and life criteria for corrugated fiberboard by three methods

Treesearch

Thomas J. Urbanik

1997-01-01

The conventional test method for determining the stacking life of corrugated containers at a fixed load level does not adequately predict a safe load when storage time is fixed. This study introduced multiple load levels and related the probability of time at failure to load. A statistical analysis of logarithm-of-time failure data varying with load level predicts the...

Influence of Family Communication Structure and Vanity Trait on Consumption Behavior: A Case Study of Adolescent Students in Taiwan

ERIC Educational Resources Information Center

Chang, Wei-Lung; Liu, Hsiang-Te; Lin, Tai-An; Wen, Yung-Sung

2008-01-01

The purpose of this research was to study the relationship between family communication structure, vanity trait, and related consumption behavior. The study used an empirical method with adolescent students from the northern part of Taiwan as the subjects. Multiple statistical methods and the SEM model were used for testing the hypotheses. The…

A Multiple Group Measurement Model of Children's Reports of Parental Socioeconomic Status. Discussion Papers No. 531-78.

ERIC Educational Resources Information Center

Mare, Robert D.; Mason, William M.

An important class of applications of measurement error or constrained factor analytic models consists of comparing models for several populations. In such cases, it is appropriate to make explicit statistical tests of model similarity across groups and to constrain some parameters of the models to be equal across groups using a priori substantive…

Informal Statistics Help Desk

NASA Technical Reports Server (NTRS)

Ploutz-Snyder, R. J.; Feiveson, A. H.

2015-01-01

Back by popular demand, the JSC Biostatistics Lab is offering an opportunity for informal conversation about challenges you may have encountered with issues of experimental design, analysis, data visualization or related topics. Get answers to common questions about sample size, repeated measures, violation of distributional assumptions, missing data, multiple testing, time-to-event data, when to trust the results of your analyses (reproducibility issues) and more.

Evaluation of geriatrics education at a Chinese University: a survey of attitudes and knowledge among undergraduate medical students.

PubMed

Shi, Sandra; Lio, Jonathan; Dong, Hongmei; Jiang, Ivy; Cooper, Brian; Sherer, Renslow

2018-05-08

Despite widespread reforms in medical education across China, nationally there has been no mandate or movement toward systemically incorporating geriatrics into curricula. To what degree medical students are trained and have exposure to geriatric topics remains unclear. We surveyed 190 medical students during their final year of medical school at a Chinese medical university, graduating from reformed and also traditional curricula. The survey was comprised of a subjective assessment of attitudes and reported knowledge, as well as an objective assessment of knowledge via a multiple choice test. Student attitudes were favorable toward geriatrics, with 91% supporting the addition of specialized clinical experiences to the curriculum. Students generally reported low exposure to geriatrics, with no statistically significant differences between reform and traditional curricula. There was a statistically significant difference in performance on the multiple choice test between curricula but at a degree unlikely to be practically significant. Students had very favorable attitudes toward geriatrics as a field and specialty; however scored poorly on competency exams, with the lowest performance around diagnosis and treatment of specific geriatric conditions. Our results suggest that there is a need and desire for increased geriatric-oriented learning at Chinese medical schools.

MC3: Multi-core Markov-chain Monte Carlo code

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Lust, Nate; Foster, AJ; Stemm, Madison; Loredo, Tom; Stevenson, Kevin; Campo, Chris; Hardin, Matt; Hardy, Ryan

2016-10-01

MC3 (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC3 can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

Multiple comparisons permutation test for image based data mining in radiotherapy

PubMed Central

2013-01-01

Comparing incidental dose distributions (i.e. images) of patients with different outcomes is a straightforward way to explore dose-response hypotheses in radiotherapy. In this paper, we introduced a permutation test that compares images, such as dose distributions from radiotherapy, while tackling the multiple comparisons problem. A test statistic Tmax was proposed that summarizes the differences between the images into a single value and a permutation procedure was employed to compute the adjusted p-value. We demonstrated the method in two retrospective studies: a prostate study that relates 3D dose distributions to failure, and an esophagus study that relates 2D surface dose distributions of the esophagus to acute esophagus toxicity. As a result, we were able to identify suspicious regions that are significantly associated with failure (prostate study) or toxicity (esophagus study). Permutation testing allows direct comparison of images from different patient categories and is a useful tool for data mining in radiotherapy. PMID:24365155

Matrix metalloproteinases and educational attainment in refractive error: evidence of gene-environment interactions in the AREDS study

PubMed Central

Wojciechowski, Robert; Yee, Stephanie S.; Simpson, Claire L.; Bailey-Wilson, Joan E.; Stambolian, Dwight

2012-01-01

Purpose A previous study of Old Order Amish families has shown association of ocular refraction with markers proximal to matrix metalloproteinase (MMP) genes MMP1 and MMP10 and intragenic to MMP2. We conducted a candidate gene replication study of association between refraction and single nucleotide polymorphisms (SNPs) within these genomic regions. Design Candidate gene genetic association study. Participants 2,000 participants drawn from the Age Related Eye Disease Study (AREDS) were chosen for genotyping. After quality control filtering, 1912 individuals were available for analysis. Methods Microarray genotyping was performed using the HumanOmni 2.5 bead array. SNPs originally typed in the previous Amish association study were extracted for analysis. In addition, haplotype tagging SNPs were genotyped using TaqMan assays. Quantitative trait association analyses of mean spherical equivalent refraction (MSE) were performed on 30 markers using linear regression models and an additive genetic risk model, while adjusting for age, sex, education, and population substructure. Post-hoc analyses were performed after stratifying on a dichotomous education variable. Pointwise (P-emp) and multiple-test study-wise (P-multi) significance levels were calculated empirically through permutation. Main outcome measures MSE was used as a quantitative measure of ocular refraction. Results The mean age and ocular refraction were 68 years (SD=4.7) and +0.55 D (SD=2.14), respectively. Pointwise statistical significance was obtained for rs1939008 (P-emp=0.0326). No SNP attained statistical significance after correcting for multiple testing. In stratified analyses, multiple SNPs reached pointwise significance in the lower-education group: 2 of these were statistically significant after multiple testing correction. The two highest-ranking SNPs in Amish families (rs1939008 and rs9928731) showed pointwise P-emp<0.01 in the lower-education stratum of AREDS participants. Conclusions We show suggestive evidence of replication of an association signal for ocular refraction to a marker between MMP1 and MMP10. We also provide evidence of a gene-environment interaction between previously-reported markers and education on refractive error. Variants in MMP1- MMP10 and MMP2 regions appear to affect population variation in ocular refraction in environmental conditions less favorable for myopia development. PMID:23098370

Effects of multiple inherited and acquired thrombophilia on outcomes of in-vitro fertilization.

PubMed

Di Nisio, Marcello; Ponzano, Adalisa; Tiboni, Gianmario; Guglielmi, Maria Domenica; Rutjes, Anne Wilhelmina Saskia; Porreca, Ettore

2018-05-09

The effects of multiple inherited and acquired thrombophilic defects on the outcome of in-vitro fertilization (IVF) remain unexplored. The aim of this study was to evaluate the association between multiple thrombophilia and clinical outcomes in a large prospective cohort of women undergoing IVF. Consecutive women scheduled for IVF were eligible. The primary study outcome was live birth. Secondary outcomes included spontaneous abortion, clinical pregnancy, and symptomatic venous thromboembolism. 687 women with a mean age of 34.6 (±3.2) years were included. Overall, 22 women (3.2%) had two or more thrombophilic defects. The probability of live birth was not statistically significantly different between women with ≥2 thrombophilia (odds ratio [OR] 0.62; 95% confidence interval [CI], 0.18 to 2.11) or ≥1 thrombophilia (OR 0.67;95% CI, 0.41 to 1.09) and women without any thrombophilia. None of the individual inherited thrombophilia nor positivity to antiphospholipid antibodies or lupus anticoagulant were associated with live birth. Single positivity for lupus anticoagulant carried a more than threefold higher risk of abortion (OR 3.74; 95% CI, 1.30 to 10.75). There were no statistically significant associations between individual or multiple thrombophilic defects and clinical pregnancy or pregnancy test results. No woman had a history of venous thromboembolism and none developed a thrombotic event during the study. In women undergoing IVF, the presence of two or more thrombophilic defects was rare and showed no statistically significant associations with IVF outcomes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Three-dimensional volume-rendering technique in the angiographic follow-up of intracranial aneurysms embolized with coils.

PubMed

Zhou, Bing; Li, Ming-Hua; Wang, Wu; Xu, Hao-Wen; Cheng, Yong-De; Wang, Jue

2010-03-01

The authors conducted a study to evaluate the advantages of a 3D volume-rendering technique (VRT) in follow-up digital subtraction (DS) angiography of coil-embolized intracranial aneurysms. One hundred nine patients with 121 intracranial aneurysms underwent endovascular coil embolization and at least 1 follow-up DS angiography session at the authors' institution. Two neuroradiologists independently evaluated the conventional 2D DS angiograms, rotational angiograms, and 3D VRT images obtained at the interventional procedures and DS angiography follow-up. If multiple follow-up sessions were performed, the final follow-up was mainly considered. The authors compared the 3 techniques for their ability to detect aneurysm remnants (including aneurysm neck and sac remnants) and parent artery stenosis based on the angiographic follow-up. The Kruskal-Wallis test was used for group comparisons, and the kappa test was used to measure interobserver agreement. Statistical analyses were performed using commercially available software. There was a high statistical significance among 2D DS angiography, rotational angiography, and 3D VRT results (X(2) = 9.9613, p = 0.0069) when detecting an aneurysm remnant. Further comparisons disclosed a statistical significance between 3D VRT and rotational angiography (X(2) = 4.9754, p = 0.0257); a high statistical significance between 3D VRT and 2D DS angiography (X(2) = 8.9169, p = 0.0028); and no significant difference between rotational angiography and 2D DS angiography (X(2) = 0.5648, p = 0.4523). There was no statistical significance among the 3 techniques when detecting parent artery stenosis (X(2) = 2.5164, p = 0.2842). One case, in which parent artery stenosis was diagnosed by 2D DS angiography and rotational angiography, was excluded by 3D VRT following observations of multiple views. The kappa test showed good agreement between the 2 observers. The 3D VRT is more sensitive in detecting aneurysm remnants than 2D DS angiography and rotational angiography and is helpful for identifying parent artery stenosis. The authors recommend this technique for the angiographic follow-up of patients with coil-embolized aneurysms.

Effect of pH Test-Strip Characteristics on Accuracy of Readings.

PubMed

Metheny, Norma A; Gunn, Emily M; Rubbelke, Cynthia S; Quillen, Terrilynn Fox; Ezekiel, Uthayashanker R; Meert, Kathleen L

2017-06-01

Little is known about characteristics of colorimetric pH test strips that are most likely to be associated with accurate interpretations in clinical situations. To compare the accuracy of 4 pH test strips with varying characteristics (ie, multiple vs single colorimetric squares per calibration, and differing calibration units [1.0 vs 0.5]). A convenience sample of 100 upper-level nursing students with normal color vision was recruited to evaluate the accuracy of the test strips. Six buffer solutions (pH range, 3.0 to 6.0) were used during the testing procedure. Each of the 100 participants performed 20 pH tests in random order, providing a total of 2000 readings. The sensitivity and specificity of each test strip was computed. In addition, the degree to which the test strips under- or overestimated the pH values was analyzed using descriptive statistics. Our criterion for correct readings was an exact match with the pH buffer solution being evaluated. Although none of the test strips evaluated in our study was 100% accurate at all of the measured pH values, those with multiple squares per pH calibration were clearly superior overall to those with a single test square. Test strips with multiple squares per calibration were associated with greater overall accuracy than test strips with a single square per calibration. However, because variable degrees of error were observed in all of the test strips, use of a pH meter is recommended when precise readings are crucial. ©2017 American Association of Critical-Care Nurses.

Neural Correlates of Alerting and Orienting Impairment in Multiple Sclerosis Patients

PubMed Central

Vázquez-Marrufo, Manuel; Galvao-Carmona, Alejandro; González-Rosa, Javier J.; Hidalgo-Muñoz, Antonio R.; Borges, Mónica; Ruiz-Peña, Juan Luis; Izquierdo, Guillermo

2014-01-01

Background A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test. Results After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05). ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05) and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01). With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01) and an ERP parameter (CNV amplitude). Conclusions Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients. PMID:24820333

Neural correlates of alerting and orienting impairment in multiple sclerosis patients.

PubMed

Vázquez-Marrufo, Manuel; Galvao-Carmona, Alejandro; González-Rosa, Javier J; Hidalgo-Muñoz, Antonio R; Borges, Mónica; Ruiz-Peña, Juan Luis; Izquierdo, Guillermo

2014-01-01

A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test. After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05). ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05) and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01). With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01) and an ERP parameter (CNV amplitude). Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients.

Association between osteoporosis and periodontal disease among postmenopausal Indian women.

PubMed

Richa; R, Yashoda; Puranik, Manjunath P; Shrivastava, Amit

2017-08-01

The aim of the present study was to determine the association between osteoporosis and periodontal disease among postmenopausal Indian women. A cross-sectional comparative study was conducted among postmenopausal women aged 45-65 years attending various hospitals in Bangalore, India. The examination was performed using the plaque index, gingival index, modified sulcus bleeding index, and community periodontal index. The women then underwent a bone mineral density (BMD) test using an ultrasonometer. Based on the BMD scores, participants were divided into osteoporotic and non-osteoporotic groups. For the statistical analysis, χ 2 -test, Student's t-test, and multiple regression analysis were applied. The mean plaque, gingival, and bleeding scores were significantly higher among osteoporotic women (1.83 ± 0.47, 1.73 ± 0.49, 1.82 ± 0.52) compared to the non-osteoporotic women (1.31 ± 0.40, 1.09 ± 0.52, 1.25 ± 0.50). The mean number of sextants affected for codes 3 and 4 of the community periodontal index and codes 1, 2, and 3 of loss of attachment were significantly higher among osteoporotic group compared to the non-osteoporotic group. Multiple logistic regression tests confirmed the statistically-significant association between osteoporosis and menopause duration, loss of attachment, bleeding, and gingivitis scores. Skeletal BMD is related to clinical attachment loss, bleeding, and gingivitis, which suggests that there is an association between osteoporosis and periodontal diseases. © 2016 John Wiley & Sons Australia, Ltd.

Effect of slice thickness on brain magnetic resonance image texture analysis

PubMed Central

2010-01-01

Background The accuracy of texture analysis in clinical evaluation of magnetic resonance images depends considerably on imaging arrangements and various image quality parameters. In this paper, we study the effect of slice thickness on brain tissue texture analysis using a statistical approach and classification of T1-weighted images of clinically confirmed multiple sclerosis patients. Methods We averaged the intensities of three consecutive 1-mm slices to simulate 3-mm slices. Two hundred sixty-four texture parameters were calculated for both the original and the averaged slices. Wilcoxon's signed ranks test was used to find differences between the regions of interest representing white matter and multiple sclerosis plaques. Linear and nonlinear discriminant analyses were applied with several separate training and test sets to determine the actual classification accuracy. Results Only moderate differences in distributions of the texture parameter value for 1-mm and simulated 3-mm-thick slices were found. Our study also showed that white matter areas are well separable from multiple sclerosis plaques even if the slice thickness differs between training and test sets. Conclusions Three-millimeter-thick magnetic resonance image slices acquired with a 1.5 T clinical magnetic resonance scanner seem to be sufficient for texture analysis of multiple sclerosis plaques and white matter tissue. PMID:20955567

POWER-ENHANCED MULTIPLE DECISION FUNCTIONS CONTROLLING FAMILY-WISE ERROR AND FALSE DISCOVERY RATES.

PubMed

Peña, Edsel A; Habiger, Joshua D; Wu, Wensong

2011-02-01

Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypotheses testing with weak and strong control of the family-wise error rate (FWER) or the false discovery rate (FDR) are developed and studied. The improvement over existing procedures such as the Šidák procedure for FWER control and the Benjamini-Hochberg (BH) procedure for FDR control is achieved by exploiting possible differences in the powers of the individual tests. Results signal the need to take into account the powers of the individual tests and to have multiple hypotheses decision functions which are not limited to simply using the individual p -values, as is the case, for example, with the Šidák, Bonferroni, or BH procedures. They also enhance understanding of the role of the powers of individual tests, or more precisely the receiver operating characteristic (ROC) functions of decision processes, in the search for better multiple hypotheses testing procedures. A decision-theoretic framework is utilized, and through auxiliary randomizers the procedures could be used with discrete or mixed-type data or with rank-based nonparametric tests. This is in contrast to existing p -value based procedures whose theoretical validity is contingent on each of these p -value statistics being stochastically equal to or greater than a standard uniform variable under the null hypothesis. Proposed procedures are relevant in the analysis of high-dimensional "large M , small n " data sets arising in the natural, physical, medical, economic and social sciences, whose generation and creation is accelerated by advances in high-throughput technology, notably, but not limited to, microarray technology.

Passive detection of vehicle loading

NASA Astrophysics Data System (ADS)

McKay, Troy R.; Salvaggio, Carl; Faulring, Jason W.; Salvaggio, Philip S.; McKeown, Donald M.; Garrett, Alfred J.; Coleman, David H.; Koffman, Larry D.

2012-01-01

The Digital Imaging and Remote Sensing Laboratory (DIRS) at the Rochester Institute of Technology, along with the Savannah River National Laboratory is investigating passive methods to quantify vehicle loading. The research described in this paper investigates multiple vehicle indicators including brake temperature, tire temperature, engine temperature, acceleration and deceleration rates, engine acoustics, suspension response, tire deformation and vibrational response. Our investigation into these variables includes building and implementing a sensing system for data collection as well as multiple full-scale vehicle tests. The sensing system includes; infrared video cameras, triaxial accelerometers, microphones, video cameras and thermocouples. The full scale testing includes both a medium size dump truck and a tractor-trailer truck on closed courses with loads spanning the full range of the vehicle's capacity. Statistical analysis of the collected data is used to determine the effectiveness of each of the indicators for characterizing the weight of a vehicle. The final sensing system will monitor multiple load indicators and combine the results to achieve a more accurate measurement than any of the indicators could provide alone.

Effectiveness of applying progressive muscle relaxation technique on quality of life of patients with multiple sclerosis.

PubMed

Ghafari, Somayeh; Ahmadi, Fazlolah; Nabavi, Masoud; Anoshirvan, Kazemnejad; Memarian, Robabe; Rafatbakhsh, Mohamad

2009-08-01

To identify the effects of applying Progressive Muscle Relaxation Technique on Quality of Life of patients with multiple Sclerosis. In view of the growing caring options in Multiple Sclerosis, improvement of quality of life has become increasingly relevant as a caring intervention. Complementary therapies are widely used by multiple sclerosis patients and Progressive Muscle Relaxation Technique is a form of complementary therapies. Quasi-experimental study. Multiple Sclerosis patients (n = 66) were selected with no probability sampling then assigned to experimental and control groups (33 patients in each group). Means of data collection included: Individual Information Questionnaire, SF-8 Health Survey, Self-reported checklist. PMRT performed for 63 sessions by experimental group during two months but no intervention was done for control group. Statistical analysis was done by SPSS software. Student t-test showed that there was no significant difference between two groups in mean scores of health-related quality of life before the study but this test showed a significant difference between two groups, one and two months after intervention (p < 0.05). anova test with repeated measurements showed that there is a significant difference in mean score of whole and dimensions of health-related quality of life between two groups in three times (p < 0.05). Although this study provides modest support for the effectiveness of Progressive Muscle Relaxation Technique on quality of life of multiple sclerosis patients, further research is required to determine better methods to promote quality of life of patients suffer multiple sclerosis and other chronic disease. Progressive Muscle Relaxation Technique is practically feasible and is associated with increase of life quality of multiple sclerosis patients; so that health professionals need to update their knowledge about complementary therapies.

Effect of intraoperative analgesia on children's pain perception during recovery after painful dental procedures performed under general anaesthesia.

PubMed

El Batawi, H Y

2015-02-01

To investigate the possible effect of intraoperative analgesia, namely diclofenac sodium compared to acetaminophen on post-recovery pain perception in children undergoing painful dental procedures under general anaesthesia. A double-blind randomised clinical trial. A sample of 180 consecutive cases of children undergoing full dental rehabilitation under general anaesthesia in a private hospital in Saudi Arabia during 2013 was divided into three groups (60 children each) according to the analgesic used prior to extubation. Group A, children had diclofenac sodium suppository. Group B, children received acetaminophen suppository and Group C, the control group. Using an authenticated Arabic version of the Wong and Baker faces Pain assessment Scale, patients were asked to choose the face that suits best the pain he/she is suffering. Data were collected and recorded for statistical analysis. Student's t test was used for comparison of sample means. A preliminary F test to compare sample variances was carried out to determine the appropriate t test variant to be used. A "p" value less than 0.05 was considered significant. More than 93% of children had post-operative pain in varying degrees. High statistical significance was observed between children in groups A and B compared to control group C with the later scoring high pain perception. Diclofenac showed higher potency in multiple painful procedures, while the statistical difference was not significant in children with three or less painful dental procedures. Diclophenac sodium is more potent than acetaminophen, especially for multiple pain-provoking or traumatic procedures. A timely use of NSAID analgesia just before extubation helps provide adequate coverage during recovery. Peri-operative analgesia is to be recommended as an essential treatment adjunct for child dental rehabilitation under general anaesthesia.

Single-Item Measurement of Suicidal Behaviors: Validity and Consequences of Misclassification

PubMed Central

Millner, Alexander J.; Lee, Michael D.; Nock, Matthew K.

2015-01-01

Suicide is a leading cause of death worldwide. Although research has made strides in better defining suicidal behaviors, there has been less focus on accurate measurement. Currently, the widespread use of self-report, single-item questions to assess suicide ideation, plans and attempts may contribute to measurement problems and misclassification. We examined the validity of single-item measurement and the potential for statistical errors. Over 1,500 participants completed an online survey containing single-item questions regarding a history of suicidal behaviors, followed by questions with more precise language, multiple response options and narrative responses to examine the validity of single-item questions. We also conducted simulations to test whether common statistical tests are robust against the degree of misclassification produced by the use of single-items. We found that 11.3% of participants that endorsed a single-item suicide attempt measure engaged in behavior that would not meet the standard definition of a suicide attempt. Similarly, 8.8% of those who endorsed a single-item measure of suicide ideation endorsed thoughts that would not meet standard definitions of suicide ideation. Statistical simulations revealed that this level of misclassification substantially decreases statistical power and increases the likelihood of false conclusions from statistical tests. Providing a wider range of response options for each item reduced the misclassification rate by approximately half. Overall, the use of single-item, self-report questions to assess the presence of suicidal behaviors leads to misclassification, increasing the likelihood of statistical decision errors. Improving the measurement of suicidal behaviors is critical to increase understanding and prevention of suicide. PMID:26496707

A Guerilla Guide to Common Problems in ‘Neurostatistics’: Essential Statistical Topics in Neuroscience

PubMed Central

Smith, Paul F.

2017-01-01

Effective inferential statistical analysis is essential for high quality studies in neuroscience. However, recently, neuroscience has been criticised for the poor use of experimental design and statistical analysis. Many of the statistical issues confronting neuroscience are similar to other areas of biology; however, there are some that occur more regularly in neuroscience studies. This review attempts to provide a succinct overview of some of the major issues that arise commonly in the analyses of neuroscience data. These include: the non-normal distribution of the data; inequality of variance between groups; extensive correlation in data for repeated measurements across time or space; excessive multiple testing; inadequate statistical power due to small sample sizes; pseudo-replication; and an over-emphasis on binary conclusions about statistical significance as opposed to effect sizes. Statistical analysis should be viewed as just another neuroscience tool, which is critical to the final outcome of the study. Therefore, it needs to be done well and it is a good idea to be proactive and seek help early, preferably before the study even begins. PMID:29371855

A Guerilla Guide to Common Problems in 'Neurostatistics': Essential Statistical Topics in Neuroscience.

PubMed

Smith, Paul F

2017-01-01

Effective inferential statistical analysis is essential for high quality studies in neuroscience. However, recently, neuroscience has been criticised for the poor use of experimental design and statistical analysis. Many of the statistical issues confronting neuroscience are similar to other areas of biology; however, there are some that occur more regularly in neuroscience studies. This review attempts to provide a succinct overview of some of the major issues that arise commonly in the analyses of neuroscience data. These include: the non-normal distribution of the data; inequality of variance between groups; extensive correlation in data for repeated measurements across time or space; excessive multiple testing; inadequate statistical power due to small sample sizes; pseudo-replication; and an over-emphasis on binary conclusions about statistical significance as opposed to effect sizes. Statistical analysis should be viewed as just another neuroscience tool, which is critical to the final outcome of the study. Therefore, it needs to be done well and it is a good idea to be proactive and seek help early, preferably before the study even begins.

Statistics, Handle with Care: Detecting Multiple Model Components with the Likelihood Ratio Test

NASA Astrophysics Data System (ADS)

Protassov, Rostislav; van Dyk, David A.; Connors, Alanna; Kashyap, Vinay L.; Siemiginowska, Aneta

2002-05-01

The likelihood ratio test (LRT) and the related F-test, popularized in astrophysics by Eadie and coworkers in 1971, Bevington in 1969, Lampton, Margon, & Bowyer, in 1976, Cash in 1979, and Avni in 1978, do not (even asymptotically) adhere to their nominal χ2 and F-distributions in many statistical tests common in astrophysics, thereby casting many marginal line or source detections and nondetections into doubt. Although the above authors illustrate the many legitimate uses of these statistics, in some important cases it can be impossible to compute the correct false positive rate. For example, it has become common practice to use the LRT or the F-test to detect a line in a spectral model or a source above background despite the lack of certain required regularity conditions. (These applications were not originally suggested by Cash or by Bevington.) In these and other settings that involve testing a hypothesis that is on the boundary of the parameter space, contrary to common practice, the nominal χ2 distribution for the LRT or the F-distribution for the F-test should not be used. In this paper, we characterize an important class of problems in which the LRT and the F-test fail and illustrate this nonstandard behavior. We briefly sketch several possible acceptable alternatives, focusing on Bayesian posterior predictive probability values. We present this method in some detail since it is a simple, robust, and intuitive approach. This alternative method is illustrated using the gamma-ray burst of 1997 May 8 (GRB 970508) to investigate the presence of an Fe K emission line during the initial phase of the observation. There are many legitimate uses of the LRT and the F-test in astrophysics, and even when these tests are inappropriate, there remain several statistical alternatives (e.g., judicious use of error bars and Bayes factors). Nevertheless, there are numerous cases of the inappropriate use of the LRT and similar tests in the literature, bringing substantive scientific results into question.

Allelic-based gene-gene interaction associated with quantitative traits.

PubMed

Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

2009-05-01

Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.

Effect of saliva contamination on cementation of orthodontic brackets using different adhesive systems.

PubMed

Robaski, Aliden-Willian; Pamato, Saulo; Tomás-de Oliveira, Marcelo; Pereira, Jefferson-Ricardo

2017-07-01

The enamel condition and the quality of surface are points that need to be considered for achieving optimal efficiency in the treatment with orthodontic brackets. The aim of this study was to assess the immediate bond strength of metallic brackets cemented to dental. Forty human premolars were double-sectioned, placed in PVC matrices and randomly divided into 10 groups (n=8). They received artificial saliva contamination before or after the application of adhesive systems, except for the control groups. The metallic brackets were cemented using two orthodontic cements (Transbond™ Plus Color Change, 3M Unitek e Transbond™ XT Light, 3M Unitek). The specimens were subjected to mechanical shear bond strength testing and classified according to the fracture pattern. The results were analyzed using a two-way ANOVA and Tukey's test for multiple comparisons ( p <0.05). ANOVA analysis showed statistically significant differences between the groups ( p =0.01). The Tukey's multiple comparison test indicated statistically significant difference between G6 and G7 groups ( p <0.05). A high prevalence of adhesive failure in the groups receiving the hydrophobic adhesive system. The saliva contamination prior to the application of a hydrophobic simplified conventional adhesive system was responsible for decreasing the immediate bond strength values of brackets cemented on the dental enamel. Key words: Bonding, orthodontic brackets, shear bond strength, saliva, adhesive systems.

Prevalence of consistent condom use with various types of sex partners and associated factors among money boys in Changsha, China.

PubMed

Wang, Lian-Hong; Yan, Jin; Yang, Guo-Li; Long, Shuo; Yu, Yong; Wu, Xi-Lin

2015-04-01

Money boys with inconsistent condom use (less than 100% of the time) are at high risk of infection by human immunodeficiency virus (HIV) or sexually transmitted infection (STI), but relatively little research has examined their risk behaviors. We investigated the prevalence of consistent condom use (100% of the time) and associated factors among money boys. A cross-sectional study using a structured questionnaire was conducted among money boys in Changsha, China, between July 2012 and January 2013. Independent variables included socio-demographic data, substance abuse history, work characteristics, and self-reported HIV and STI history. Dependent variables included the consistent condom use with different types of sex partners. Among the participants, 82.4% used condoms consistently with male clients, 80.2% with male sex partners, and 77.1% with female sex partners in the past 3 months. A multiple stepwise logistic regression model identified four statistically significant factors associated with lower likelihoods of consistent condom use with male clients: age group, substance abuse, lack of an "employment" arrangement, and having no HIV test within the prior 6 months. In a similar model, only one factor associated significantly with lower likelihoods of consistent condom use with male sex partners was identified in multiple stepwise logistic regression analyses: having no HIV test within the prior six months. As for female sex partners, two significant variables were statistically significant in the multiple stepwise logistic regression analysis: having no HIV test within the prior 6 months and having STI history. Interventions which are linked with more realistic and acceptable HIV prevention methods are greatly warranted and should increase risk awareness and the behavior of consistent condom use in both commercial and personal relationship. © 2015 International Society for Sexual Medicine.

Testing for association with multiple traits in generalized estimation equations, with application to neuroimaging data.

PubMed

Zhang, Yiwei; Xu, Zhiyuan; Shen, Xiaotong; Pan, Wei

2014-08-01

There is an increasing need to develop and apply powerful statistical tests to detect multiple traits-single locus associations, as arising from neuroimaging genetics and other studies. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI), in addition to genome-wide single nucleotide polymorphisms (SNPs), thousands of neuroimaging and neuropsychological phenotypes as intermediate phenotypes for Alzheimer's disease, have been collected. Although some classic methods like MANOVA and newly proposed methods may be applied, they have their own limitations. For example, MANOVA cannot be applied to binary and other discrete traits. In addition, the relationships among these methods are not well understood. Importantly, since these tests are not data adaptive, depending on the unknown association patterns among multiple traits and between multiple traits and a locus, these tests may or may not be powerful. In this paper we propose a class of data-adaptive weights and the corresponding weighted tests in the general framework of generalized estimation equations (GEE). A highly adaptive test is proposed to select the most powerful one from this class of the weighted tests so that it can maintain high power across a wide range of situations. Our proposed tests are applicable to various types of traits with or without covariates. Importantly, we also analytically show relationships among some existing and our proposed tests, indicating that many existing tests are special cases of our proposed tests. Extensive simulation studies were conducted to compare and contrast the power properties of various existing and our new methods. Finally, we applied the methods to an ADNI dataset to illustrate the performance of the methods. We conclude with the recommendation for the use of the GEE-based Score test and our proposed adaptive test for their high and complementary performance. Copyright © 2014 Elsevier Inc. All rights reserved.

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

PubMed Central

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-01-01

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008–2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0. PMID:27892471

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies.

PubMed

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-11-28

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

NASA Astrophysics Data System (ADS)

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-11-01

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

Immediate Feedback Assessment Technique in a Chemistry Classroom

NASA Astrophysics Data System (ADS)

Taylor, Kate R.

The Immediate Feedback Assessment Technique, or IFAT, is a new testing system that turns a student's traditional multiple-choice testing into a chance for hands-on learning; and provides teachers with an opportunity to obtain more information about a student's knowledge during testing. In the current study we wanted to know if: When students are given the second-chance afforded by the IFAT system, are they guessing or using prior knowledge when making their second chance choice. Additionally, while there has been some adaptation of this testing system in non-science disciplines, we wanted to study if the IFAT-system would be well- received among faculty in the sciences, more specifically chemistry faculty. By comparing the students rate of success on second-chance afforded by the IFAT-system versus the statistical likelihood of guessing correctly, statistical analysis was used to determine if we observed enough students earning the second-chance points to reject the likelihood that students were randomly guessing. Our data analysis revealed that is statistically highly unlikely that students were only guessing when the IFAT system was utilized. (It is important to note that while we can find that students are getting the answer correct at a much higher rate than random guessing we can never truly know if every student is using thought or not.).

STATISTICAL METHODOLOGY FOR THE SIMULTANEOUS ANALYSIS OF MULTIPLE TYPES OF OUTCOMES IN NONLINEAR THRESHOLD MODELS.

EPA Science Inventory

Multiple outcomes are often measured on each experimental unit in toxicology experiments. These multiple observations typically imply the existence of correlation between endpoints, and a statistical analysis that incorporates it may result in improved inference. When both disc...

Detecting Multiple Model Components with the Likelihood Ratio Test

NASA Astrophysics Data System (ADS)

Protassov, R. S.; van Dyk, D. A.

2000-05-01

The likelihood ratio test (LRT) and F-test popularized in astrophysics by Bevington (Data Reduction and Error Analysis in the Physical Sciences ) and Cash (1977, ApJ 228, 939), do not (even asymptotically) adhere to their nominal χ2 and F distributions in many statistical tests commonly used in astrophysics. The many legitimate uses of the LRT (see, e.g., the examples given in Cash (1977)) notwithstanding, it can be impossible to compute the false positive rate of the LRT or related tests such as the F-test. For example, although Cash (1977) did not suggest the LRT for detecting a line profile in a spectral model, it has become common practice despite the lack of certain required mathematical regularity conditions. Contrary to common practice, the nominal distribution of the LRT statistic should not be used in these situations. In this paper, we characterize an important class of problems where the LRT fails, show the non-standard behavior of the test in this setting, and provide a Bayesian alternative to the LRT, i.e., posterior predictive p-values. We emphasize that there are many legitimate uses of the LRT in astrophysics, and even when the LRT is inappropriate, there remain several statistical alternatives (e.g., judicious use of error bars and Bayes factors). We illustrate this point in our analysis of GRB 970508 that was studied by Piro et al. in ApJ, 514:L73-L77, 1999.

Testing the Predictive Power of Coulomb Stress on Aftershock Sequences

NASA Astrophysics Data System (ADS)

Woessner, J.; Lombardi, A.; Werner, M. J.; Marzocchi, W.

2009-12-01

Empirical and statistical models of clustered seismicity are usually strongly stochastic and perceived to be uninformative in their forecasts, since only marginal distributions are used, such as the Omori-Utsu and Gutenberg-Richter laws. In contrast, so-called physics-based aftershock models, based on seismic rate changes calculated from Coulomb stress changes and rate-and-state friction, make more specific predictions: anisotropic stress shadows and multiplicative rate changes. We test the predictive power of models based on Coulomb stress changes against statistical models, including the popular Short Term Earthquake Probabilities and Epidemic-Type Aftershock Sequences models: We score and compare retrospective forecasts on the aftershock sequences of the 1992 Landers, USA, the 1997 Colfiorito, Italy, and the 2008 Selfoss, Iceland, earthquakes. To quantify predictability, we use likelihood-based metrics that test the consistency of the forecasts with the data, including modified and existing tests used in prospective forecast experiments within the Collaboratory for the Study of Earthquake Predictability (CSEP). Our results indicate that a statistical model performs best. Moreover, two Coulomb model classes seem unable to compete: Models based on deterministic Coulomb stress changes calculated from a given fault-slip model, and those based on fixed receiver faults. One model of Coulomb stress changes does perform well and sometimes outperforms the statistical models, but its predictive information is diluted, because of uncertainties included in the fault-slip model. Our results suggest that models based on Coulomb stress changes need to incorporate stochastic features that represent model and data uncertainty.

[The overall assessment of psychological well - being of patients with multiple sclerosis after the application of physical therapy. Part 2].

PubMed

Kubsik-Gidlewska, Anna; Klimkiewicz, Robert; Klimkiewicz, Paulina; Janczewska, Katarzyna; Jankowska, Agnieszka; Nowakowski, Tomasz; Woldańska-Okońska, Marta

2017-01-01

Multiple sclerosis is a chronic demyelinating disease of the central nervous system, which results a progressive disability. The disease reduces the quality of life of patients, changes the general health perceptions, and also limits performing social roles because of emotional problems. Evaluation of the impact of the methods of rehabilitation to improve the mental health of patients with multiple sclerosis, and also to change individual parameters included in the overall assessment of mental health. The study was conducted in 2010-2014 at the Department of Physical Medicine and Rehabilitation in Lodz. The study included 120 patients with multiple sclerosis. Patients were classified into 4 test groups: in the first was used the laser, in the second - laser and magnetostimulation, in the third - kinesiotherapy, and in the fourth - magnetostimulation. The tests were carried out three times. To evaluate the quality of life was used Quality of Life Questionnaire (MSQOL-54), analyzed the overall assessment of mental health. The improvement in a range of parameters, an overall assessment of the quality of mental health has allowed to get a better overall psychological well-being. ,There was oserved a statistically significant difference at the level of p<0.001 between groups in 4/5 investigated parameters, statistically significant differences weren't obserwed at the evaluation of cognitive functions. The greatest improvement was observed in Group II and Group IV. In the examination it was confirmed an effectiveness of physical treatment, such a the laser radiation and magnetostimulation. Synergism of both methods in their biological activity, allows for evoke of hysteresis fenomenon, resulting in the maintenance of the treatment effects after cessation of rehabilitation. Applying the classical kinesiotherapy only doesn't allow to get long-term effects.

Exact p-values for pairwise comparison of Friedman rank sums, with application to comparing classifiers.

PubMed

Eisinga, Rob; Heskes, Tom; Pelzer, Ben; Te Grotenhuis, Manfred

2017-01-25

The Friedman rank sum test is a widely-used nonparametric method in computational biology. In addition to examining the overall null hypothesis of no significant difference among any of the rank sums, it is typically of interest to conduct pairwise comparison tests. Current approaches to such tests rely on large-sample approximations, due to the numerical complexity of computing the exact distribution. These approximate methods lead to inaccurate estimates in the tail of the distribution, which is most relevant for p-value calculation. We propose an efficient, combinatorial exact approach for calculating the probability mass distribution of the rank sum difference statistic for pairwise comparison of Friedman rank sums, and compare exact results with recommended asymptotic approximations. Whereas the chi-squared approximation performs inferiorly to exact computation overall, others, particularly the normal, perform well, except for the extreme tail. Hence exact calculation offers an improvement when small p-values occur following multiple testing correction. Exact inference also enhances the identification of significant differences whenever the observed values are close to the approximate critical value. We illustrate the proposed method in the context of biological machine learning, were Friedman rank sum difference tests are commonly used for the comparison of classifiers over multiple datasets. We provide a computationally fast method to determine the exact p-value of the absolute rank sum difference of a pair of Friedman rank sums, making asymptotic tests obsolete. Calculation of exact p-values is easy to implement in statistical software and the implementation in R is provided in one of the Additional files and is also available at http://www.ru.nl/publish/pages/726696/friedmanrsd.zip .

Incorporation of operator knowledge for improved HMDS GPR classification

NASA Astrophysics Data System (ADS)

Kennedy, Levi; McClelland, Jessee R.; Walters, Joshua R.

2012-06-01

The Husky Mine Detection System (HMDS) detects and alerts operators to potential threats observed in groundpenetrating RADAR (GPR) data. In the current system architecture, the classifiers have been trained using available data from multiple training sites. Changes in target types, clutter types, and operational conditions may result in statistical differences between the training data and the testing data for the underlying features used by the classifier, potentially resulting in an increased false alarm rate or a lower probability of detection for the system. In the current mode of operation, the automated detection system alerts the human operator when a target-like object is detected. The operator then uses data visualization software, contextual information, and human intuition to decide whether the alarm presented is an actual target or a false alarm. When the statistics of the training data and the testing data are mismatched, the automated detection system can overwhelm the analyst with an excessive number of false alarms. This is evident in the performance of and the data collected from deployed systems. This work demonstrates that analyst feedback can be successfully used to re-train a classifier to account for variable testing data statistics not originally captured in the initial training data.

Estimating False Discovery Proportion Under Arbitrary Covariance Dependence*

PubMed Central

Fan, Jianqing; Han, Xu; Gu, Weijie

2012-01-01

Multiple hypothesis testing is a fundamental problem in high dimensional inference, with wide applications in many scientific fields. In genome-wide association studies, tens of thousands of tests are performed simultaneously to find if any SNPs are associated with some traits and those tests are correlated. When test statistics are correlated, false discovery control becomes very challenging under arbitrary dependence. In the current paper, we propose a novel method based on principal factor approximation, which successfully subtracts the common dependence and weakens significantly the correlation structure, to deal with an arbitrary dependence structure. We derive an approximate expression for false discovery proportion (FDP) in large scale multiple testing when a common threshold is used and provide a consistent estimate of realized FDP. This result has important applications in controlling FDR and FDP. Our estimate of realized FDP compares favorably with Efron (2007)’s approach, as demonstrated in the simulated examples. Our approach is further illustrated by some real data applications. We also propose a dependence-adjusted procedure, which is more powerful than the fixed threshold procedure. PMID:24729644

An entropy-based nonparametric test for the validation of surrogate endpoints.

PubMed

Miao, Xiaopeng; Wang, Yong-Cheng; Gangopadhyay, Ashis

2012-06-30

We present a nonparametric test to validate surrogate endpoints based on measure of divergence and random permutation. This test is a proposal to directly verify the Prentice statistical definition of surrogacy. The test does not impose distributional assumptions on the endpoints, and it is robust to model misspecification. Our simulation study shows that the proposed nonparametric test outperforms the practical test of the Prentice criterion in terms of both robustness of size and power. We also evaluate the performance of three leading methods that attempt to quantify the effect of surrogate endpoints. The proposed method is applied to validate magnetic resonance imaging lesions as the surrogate endpoint for clinical relapses in a multiple sclerosis trial. Copyright © 2012 John Wiley & Sons, Ltd.

Semiquantitative determination of mesophilic, aerobic microorganisms in cocoa products using the Soleris NF-TVC method.

PubMed

Montei, Carolyn; McDougal, Susan; Mozola, Mark; Rice, Jennifer

2014-01-01

The Soleris Non-fermenting Total Viable Count method was previously validated for a wide variety of food products, including cocoa powder. A matrix extension study was conducted to validate the method for use with cocoa butter and cocoa liquor. Test samples included naturally contaminated cocoa liquor and cocoa butter inoculated with natural microbial flora derived from cocoa liquor. A probability of detection statistical model was used to compare Soleris results at multiple test thresholds (dilutions) with aerobic plate counts determined using the AOAC Official Method 966.23 dilution plating method. Results of the two methods were not statistically different at any dilution level in any of the three trials conducted. The Soleris method offers the advantage of results within 24 h, compared to the 48 h required by standard dilution plating methods.

Statistical Anomalies of Bitflips in SRAMs to Discriminate SBUs From MCUs

NASA Astrophysics Data System (ADS)

Clemente, Juan Antonio; Franco, Francisco J.; Villa, Francesca; Baylac, Maud; Rey, Solenne; Mecha, Hortensia; Agapito, Juan A.; Puchner, Helmut; Hubert, Guillaume; Velazco, Raoul

2016-08-01

Recently, the occurrence of multiple events in static tests has been investigated by checking the statistical distribution of the difference between the addresses of the words containing bitflips. That method has been successfully applied to Field Programmable Gate Arrays (FPGAs) and the original authors indicate that it is also valid for SRAMs. This paper presents a modified methodology that is based on checking the XORed addresses with bitflips, rather than on the difference. Irradiation tests on CMOS 130 & 90 nm SRAMs with 14-MeV neutrons have been performed to validate this methodology. Results in high-altitude environments are also presented and cross-checked with theoretical predictions. In addition, this methodology has also been used to detect modifications in the organization of said memories. Theoretical predictions have been validated with actual data provided by the manufacturer.

Bayesian test for colocalisation between pairs of genetic association studies using summary statistics.

PubMed

Giambartolomei, Claudia; Vukcevic, Damjan; Schadt, Eric E; Franke, Lude; Hingorani, Aroon D; Wallace, Chris; Plagnol, Vincent

2014-05-01

Genetic association studies, in particular the genome-wide association study (GWAS) design, have provided a wealth of novel insights into the aetiology of a wide range of human diseases and traits, in particular cardiovascular diseases and lipid biomarkers. The next challenge consists of understanding the molecular basis of these associations. The integration of multiple association datasets, including gene expression datasets, can contribute to this goal. We have developed a novel statistical methodology to assess whether two association signals are consistent with a shared causal variant. An application is the integration of disease scans with expression quantitative trait locus (eQTL) studies, but any pair of GWAS datasets can be integrated in this framework. We demonstrate the value of the approach by re-analysing a gene expression dataset in 966 liver samples with a published meta-analysis of lipid traits including >100,000 individuals of European ancestry. Combining all lipid biomarkers, our re-analysis supported 26 out of 38 reported colocalisation results with eQTLs and identified 14 new colocalisation results, hence highlighting the value of a formal statistical test. In three cases of reported eQTL-lipid pairs (SYPL2, IFT172, TBKBP1) for which our analysis suggests that the eQTL pattern is not consistent with the lipid association, we identify alternative colocalisation results with SORT1, GCKR, and KPNB1, indicating that these genes are more likely to be causal in these genomic intervals. A key feature of the method is the ability to derive the output statistics from single SNP summary statistics, hence making it possible to perform systematic meta-analysis type comparisons across multiple GWAS datasets (implemented online at http://coloc.cs.ucl.ac.uk/coloc/). Our methodology provides information about candidate causal genes in associated intervals and has direct implications for the understanding of complex diseases as well as the design of drugs to target disease pathways.

Repeatability of Cryogenic Multilayer Insulation

NASA Technical Reports Server (NTRS)

Johnson, W. L.; Vanderlaan, M.; Wood, J. J.; Rhys, N. O.; Guo, W.; Van Sciver, S.; Chato, D. J.

2017-01-01

Due to the variety of requirements across aerospace platforms, and one off projects, the repeatability of cryogenic multilayer insulation has never been fully established. The objective of this test program is to provide a more basic understanding of the thermal performance repeatability of MLI systems that are applicable to large scale tanks. There are several different types of repeatability that can be accounted for: these include repeatability between multiple identical blankets, repeatability of installation of the same blanket, and repeatability of a test apparatus. The focus of the work in this report is on the first two types of repeatability. Statistically, repeatability can mean many different things. In simplest form, it refers to the range of performance that a population exhibits and the average of the population. However, as more and more identical components are made (i.e. the population of concern grows), the simple range morphs into a standard deviation from an average performance. Initial repeatability testing on MLI blankets has been completed at Florida State University. Repeatability of five GRC provided coupons with 25 layers was shown to be +/- 8.4 whereas repeatability of repeatedly installing a single coupon was shown to be +/- 8.0. A second group of 10 coupons have been fabricated by Yetispace and tested by Florida State University, through the first 4 tests, the repeatability has been shown to be +/- 16. Based on detailed statistical analysis, the data has been shown to be statistically significant.

Repeatability of Cryogenic Multilayer Insulation

NASA Technical Reports Server (NTRS)

Johnson, W. L.; Vanderlaan, M.; Wood, J. J.; Rhys, N. O.; Guo, W.; Van Sciver, S.; Chato, D. J.

2017-01-01

Due to the variety of requirements across aerospace platforms, and one off projects, the repeatability of cryogenic multilayer insulation has never been fully established. The objective of this test program is to provide a more basic understanding of the thermal performance repeatability of MLI systems that are applicable to large scale tanks. There are several different types of repeatability that can be accounted for: these include repeatability between multiple identical blankets, repeatability of installation of the same blanket, and repeatability of a test apparatus. The focus of the work in this report is on the first two types of repeatability. Statistically, repeatability can mean many different things. In simplest form, it refers to the range of performance that a population exhibits and the average of the population. However, as more and more identical components are made (i.e. the population of concern grows), the simple range morphs into a standard deviation from an average performance. Initial repeatability testing on MLI blankets has been completed at Florida State University. Repeatability of five GRC provided coupons with 25 layers was shown to be +/- 8.4% whereas repeatability of repeatedly installing a single coupon was shown to be +/- 8.0%. A second group of 10 coupons have been fabricated by Yetispace and tested by Florida State University, through the first 4 tests, the repeatability has been shown to be +/- 15-25%. Based on detailed statistical analysis, the data has been shown to be statistically significant.

A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data

PubMed Central

Vinaixa, Maria; Samino, Sara; Saez, Isabel; Duran, Jordi; Guinovart, Joan J.; Yanes, Oscar

2012-01-01

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. PMID:24957762

A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data.

PubMed

Vinaixa, Maria; Samino, Sara; Saez, Isabel; Duran, Jordi; Guinovart, Joan J; Yanes, Oscar

2012-10-18

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.

Statistical analysis of secondary particle distributions in relativistic nucleus-nucleus collisions

NASA Technical Reports Server (NTRS)

Mcguire, Stephen C.

1987-01-01

The use is described of several statistical techniques to characterize structure in the angular distributions of secondary particles from nucleus-nucleus collisions in the energy range 24 to 61 GeV/nucleon. The objective of this work was to determine whether there are correlations between emitted particle intensity and angle that may be used to support the existence of the quark gluon plasma. The techniques include chi-square null hypothesis tests, the method of discrete Fourier transform analysis, and fluctuation analysis. We have also used the method of composite unit vectors to test for azimuthal asymmetry in a data set of 63 JACEE-3 events. Each method is presented in a manner that provides the reader with some practical detail regarding its application. Of those events with relatively high statistics, Fe approaches 0 at 55 GeV/nucleon was found to possess an azimuthal distribution with a highly non-random structure. No evidence of non-statistical fluctuations was found in the pseudo-rapidity distributions of the events studied. It is seen that the most effective application of these methods relies upon the availability of many events or single events that possess very high multiplicities.

Precipitation-snowmelt timing and snowmelt augmentation of large peak flow events, western Cascades, Oregon

Treesearch

Keith Jennings; Julia A. Jones

2015-01-01

This study tested multiple hydrologic mechanisms to explain snowpack dynamics in extreme rain-on-snow floods, which occur widely in the temperate and polar regions. We examined 26, 10 day large storm events over the period 1992–2012 in the H.J. Andrews Experimental Forest in western Oregon, using statistical analyses (regression, ANOVA, and wavelet coherence) of hourly...

Immersive Theater - a Proven Way to Enhance Learning Retention

NASA Astrophysics Data System (ADS)

Reiff, P. H.; Zimmerman, L.; Spillane, S.; Sumners, C.

2014-12-01

The portable immersive theater has gone from our first demonstration at fall AGU 2003 to a product offered by multiple companies in various versions to literally millions of users per year. As part of our NASA funded outreach program, we conducted a test of learning in a portable Discovery Dome as contrasted with learning the same materials (visuals and sound track) on a computer screen. We tested 200 middle school students (primarily underserved minorities). Paired t-tests and an independent t-test were used to compare the amount of learning that students achieved. Interest questionnaires were administered to participants in formal (public school) settings and focus groups were conducted in informal (museum camp and educational festival) settings. Overall results from the informal and formal educational setting indicated that there was a statistically significant increase in test scores after viewing We Choose Space. There was a statistically significant increase in test scores for students who viewed We Choose Space in the portable Discovery Dome (9.75) as well as with the computer (8.88). However, long-term retention of the material tested on the questionnaire indicated that for students who watched We Choose Space in the portable Discovery Dome, there was a statistically significant long-term increase in test scores (10.47), whereas, six weeks after learning on the computer, the improvements over the initial baseline (3.49) were far less and were not statistically significant. The test score improvement six weeks after learning in the dome was essentially the same as the post test immediately after watching the show, demonstrating virtually no loss of gained information in the six week interval. In the formal educational setting, approximately 34% of the respondents indicated that they wanted to learn more about becoming a scientist, while 35% expressed an interest in a career in space science. In the informal setting, 26% indicated that they were interested in pursuing a career in space science.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilbert, Richard O.

The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. The book is logically divided into three parts. Chapters 1, 2, and 3 are introductory chapters. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Somemore » statistical techniques given here are not commonly seen in statistics book. For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17). Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. For example, only brief mention could be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Also, no discussion of methods for assessing risks from environmental pollution could be included.« less

Statistical Analysis of Zebrafish Locomotor Response.

PubMed

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.

Statistical Analysis of Zebrafish Locomotor Response

PubMed Central

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. PMID:26437184

Multiple-Solution Problems in a Statistics Classroom: An Example

ERIC Educational Resources Information Center

Chu, Chi Wing; Chan, Kevin L. T.; Chan, Wai-Sum; Kwong, Koon-Shing

2017-01-01

The mathematics education literature shows that encouraging students to develop multiple solutions for given problems has a positive effect on students' understanding and creativity. In this paper, we present an example of multiple-solution problems in statistics involving a set of non-traditional dice. In particular, we consider the exact…

A comparison of single-cycle versus multiple-cycle proof testing strategies

NASA Technical Reports Server (NTRS)

Hudak, S. J., Jr.; Mcclung, R. C.; Bartlett, M. L.; Fitzgerald, J. H.; Russell, D. A.

1990-01-01

An evaluation of single-cycle and multiple-cycle proof testing (MCPT) strategies for SSME components is described. Data for initial sizes and shapes of actual SSME hardware defects are analyzed statistically. Closed-form estimates of the J-integral for surface flaws are derived with a modified reference stress method. The results of load- and displacement-controlled stable crack growth tests on thin IN-718 plates with deep surface flaws are summarized. A J-resistance curve for the surface-cracked configuration is developed and compared with data from thick compact tension specimens. The potential for further crack growth during large unload/reload cycles is discussed, highlighting conflicting data in the literature. A simple model for ductile crack growth during MCPT based on the J-resistance curve is used to study the potential effects of key variables. The projected changes in the crack size distribution during MCPT depend on the interactions between several key parameters, including the number of proof cycles, the nature of the resistance curve, the initial crack size distribution, the component boundary conditions (load vs. displacement control), and the magnitude of the applied load or displacement. The relative advantages of single-cycle and multiple-cycle proof testing appear to be specific, therefore, to individual component geometry, material, and loading.

Validity of the Instrumented Push and Release Test to Quantify Postural Responses in Persons With Multiple Sclerosis.

PubMed

El-Gohary, Mahmoud; Peterson, Daniel; Gera, Geetanjali; Horak, Fay B; Huisinga, Jessie M

2017-07-01

To test the validity of wearable inertial sensors to provide objective measures of postural stepping responses to the push and release clinical test in people with multiple sclerosis. Cross-sectional study. University medical center balance disorder laboratory. Total sample N=73; persons with multiple sclerosis (PwMS) n=52; healthy controls n=21. Stepping latency, time and number of steps required to reach stability, and initial step length were calculated using 3 inertial measurement units placed on participants' lumbar spine and feet. Correlations between inertial sensor measures and measures obtained from the laboratory-based systems were moderate to strong and statistically significant for all variables: time to release (r=.992), latency (r=.655), time to stability (r=.847), time of first heel strike (r=.665), number of steps (r=.825), and first step length (r=.592). Compared with healthy controls, PwMS demonstrated a longer time to stability and required a larger number of steps to reach stability. The instrumented push and release test is a valid measure of postural responses in PwMS and could be used as a clinical outcome measures for patient care decisions or for clinical trials aimed at improving postural control in PwMS. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Time Scale Optimization and the Hunt for Astronomical Cycles in Deep Time Strata

NASA Astrophysics Data System (ADS)

Meyers, Stephen R.

2016-04-01

A valuable attribute of astrochronology is the direct link between chronometer and climate change, providing a remarkable opportunity to constrain the evolution of the surficial Earth System. Consequently, the hunt for astronomical cycles in strata has spurred the development of a rich conceptual framework for climatic/oceanographic change, and has allowed exploration of the geologic record with unprecedented temporal resolution. Accompanying these successes, however, has been a persistent skepticism about appropriate astrochronologic testing and circular reasoning: how does one reliably test for astronomical cycles in stratigraphic data, especially when time is poorly constrained? From this perspective, it would seem that the merits and promise of astrochronology (e.g., a geologic time scale measured in ≤400 kyr increments) also serves as its Achilles heel, if the confirmation of such short rhythms defies rigorous statistical testing. To address these statistical challenges in astrochronologic testing, a new approach has been developed that (1) explicitly evaluates time scale uncertainty, (2) is resilient to common problems associated with spectrum confidence level assessment and 'multiple testing', and (3) achieves high statistical power under a wide range of conditions (it can identify astronomical cycles when present in data). Designated TimeOpt (for "time scale optimization"; Meyers 2015), the method employs a probabilistic linear regression model framework to investigate amplitude modulation and frequency ratios (bundling) in stratigraphic data, while simultaneously determining the optimal time scale. This presentation will review the TimeOpt method, and demonstrate how the flexible statistical framework can be further extended to evaluate (and optimize upon) complex sedimentation rate models, enhancing the statistical power of the approach, and addressing the challenge of unsteady sedimentation. Meyers, S. R. (2015), The evaluation of eccentricity-related amplitude modulation and bundling in paleoclimate data: An inverse approach for astrochronologic testing and time scale optimization, Paleoceanography, 30, doi:10.1002/ 2015PA002850.

Multiple-labelling immunoEM using different sizes of colloidal gold: alternative approaches to test for differential distribution and colocalization in subcellular structures.

PubMed

Mayhew, Terry M; Lucocq, John M

2011-03-01

Various methods for quantifying cellular immunogold labelling on transmission electron microscope thin sections are currently available. All rely on sound random sampling principles and are applicable to single immunolabelling across compartments within a given cell type or between different experimental groups of cells. Although methods are also available to test for colocalization in double/triple immunogold labelling studies, so far, these have relied on making multiple measurements of gold particle densities in defined areas or of inter-particle nearest neighbour distances. Here, we present alternative two-step approaches to codistribution and colocalization assessment that merely require raw counts of gold particles in distinct cellular compartments. For assessing codistribution over aggregate compartments, initial statistical evaluation involves combining contingency table and chi-squared analyses to provide predicted gold particle distributions. The observed and predicted distributions allow testing of the appropriate null hypothesis, namely, that there is no difference in the distribution patterns of proteins labelled by different sizes of gold particle. In short, the null hypothesis is that of colocalization. The approach for assessing colabelling recognises that, on thin sections, a compartment is made up of a set of sectional images (profiles) of cognate structures. The approach involves identifying two groups of compartmental profiles that are unlabelled and labelled for one gold marker size. The proportions in each group that are also labelled for the second gold marker size are then compared. Statistical analysis now uses a 2 × 2 contingency table combined with the Fisher exact probability test. Having identified double labelling, the profiles can be analysed further in order to identify characteristic features that might account for the double labelling. In each case, the approach is illustrated using synthetic and/or experimental datasets and can be refined to correct observed labelling patterns to specific labelling patterns. These simple and efficient approaches should be of more immediate utility to those interested in codistribution and colocalization in multiple immunogold labelling investigations.

Evaluating Composite Sampling Methods of Bacillus spores at Low Concentrations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hess, Becky M.; Amidan, Brett G.; Anderson, Kevin K.

Restoring facility operations after the 2001 Amerithrax attacks took over three months to complete, highlighting the need to reduce remediation time. The most time intensive tasks were environmental sampling and sample analyses. Composite sampling allows disparate samples to be combined, with only a single analysis needed, making it a promising method to reduce response times. We developed a statistical experimental design to test three different composite sampling methods: 1) single medium single pass composite: a single cellulose sponge samples multiple coupons; 2) single medium multi-pass composite: a single cellulose sponge is used to sample multiple coupons; and 3) multi-medium post-samplemore » composite: a single cellulose sponge samples a single surface, and then multiple sponges are combined during sample extraction. Five spore concentrations of Bacillus atrophaeus Nakamura spores were tested; concentrations ranged from 5 to 100 CFU/coupon (0.00775 to 0.155CFU/cm2, respectively). Study variables included four clean surface materials (stainless steel, vinyl tile, ceramic tile, and painted wallboard) and three grime coated/dirty materials (stainless steel, vinyl tile, and ceramic tile). Analysis of variance for the clean study showed two significant factors: composite method (p-value < 0.0001) and coupon material (p-value = 0.0008). Recovery efficiency (RE) was higher overall using the post-sample composite (PSC) method compared to single medium composite from both clean and grime coated materials. RE with the PSC method for concentrations tested (10 to 100 CFU/coupon) was similar for ceramic tile, painted wall board, and stainless steel for clean materials. RE was lowest for vinyl tile with both composite methods. Statistical tests for the dirty study showed RE was significantly higher for vinyl and stainless steel materials, but significantly lower for ceramic tile. These results suggest post-sample compositing can be used to reduce sample analysis time when responding to a Bacillus anthracis contamination event of clean or dirty surfaces.« less

Random number generators tested on quantum Monte Carlo simulations.

PubMed

Hongo, Kenta; Maezono, Ryo; Miura, Kenichi

2010-08-01

We have tested and compared several (pseudo) random number generators (RNGs) applied to a practical application, ground state energy calculations of molecules using variational and diffusion Monte Carlo metheds. A new multiple recursive generator with 8th-order recursion (MRG8) and the Mersenne twister generator (MT19937) are tested and compared with the RANLUX generator with five luxury levels (RANLUX-[0-4]). Both MRG8 and MT19937 are proven to give the same total energy as that evaluated with RANLUX-4 (highest luxury level) within the statistical error bars with less computational cost to generate the sequence. We also tested the notorious implementation of linear congruential generator (LCG), RANDU, for comparison. (c) 2010 Wiley Periodicals, Inc.

Structured didactic teaching sessions improve medical student neurology clerkship test scores: a pilot study.

PubMed

Menkes, Daniel L; Reed, Mary

2008-01-01

To determine the effectiveness of didactic case-based instruction methodology to improve medical student comprehension of common neurological illnesses and neurological emergencies. Neurology department, academic university. 415 third and fourth year medical students performing a required four week neurology clerkship. Raw test scores on a 1 hour, 50-item clinical vignette based examination and open-ended questions in a post-clerkship feedback session. There was a statistically significant improvement in overall test scores (p<0.001). Didactic teaching sessions have a significant positive impact on neurology student clerkship test score performance and perception of their educational experience. Confirmation of these results across multiple specialties in a multi-center trial is warranted.

Developing a magnetism conceptual survey and assessing gender differences in student understanding of magnetism

NASA Astrophysics Data System (ADS)

Li, Jing; Singh, Chandralekha

2012-02-01

We discuss the development of a research-based conceptual multiple-choice survey of magnetism. We also discuss the use of the survey to investigate gender differences in students' difficulties with concepts related to magnetism. We find that while there was no gender difference on the pre-test. However, female students performed significantly worse than male students when the survey was given as a post-test in traditionally taught calculus-based introductory physics courses with similar results in both the regular and honors versions of the course. In the algebra-based courses, the performance of female and male students has no statistical difference on the pre-test or the post-test.

Benchmarking and performance analysis of the CM-2. [SIMD computer

NASA Technical Reports Server (NTRS)

Myers, David W.; Adams, George B., II

1988-01-01

A suite of benchmarking routines testing communication, basic arithmetic operations, and selected kernel algorithms written in LISP and PARIS was developed for the CM-2. Experiment runs are automated via a software framework that sequences individual tests, allowing for unattended overnight operation. Multiple measurements are made and treated statistically to generate well-characterized results from the noisy values given by cm:time. The results obtained provide a comparison with similar, but less extensive, testing done on a CM-1. Tests were chosen to aid the algorithmist in constructing fast, efficient, and correct code on the CM-2, as well as gain insight into what performance criteria are needed when evaluating parallel processing machines.

A statistical simulation model for field testing of non-target organisms in environmental risk assessment of genetically modified plants.

PubMed

Goedhart, Paul W; van der Voet, Hilko; Baldacchino, Ferdinando; Arpaia, Salvatore

2014-04-01

Genetic modification of plants may result in unintended effects causing potentially adverse effects on the environment. A comparative safety assessment is therefore required by authorities, such as the European Food Safety Authority, in which the genetically modified plant is compared with its conventional counterpart. Part of the environmental risk assessment is a comparative field experiment in which the effect on non-target organisms is compared. Statistical analysis of such trials come in two flavors: difference testing and equivalence testing. It is important to know the statistical properties of these, for example, the power to detect environmental change of a given magnitude, before the start of an experiment. Such prospective power analysis can best be studied by means of a statistical simulation model. This paper describes a general framework for simulating data typically encountered in environmental risk assessment of genetically modified plants. The simulation model, available as Supplementary Material, can be used to generate count data having different statistical distributions possibly with excess-zeros. In addition the model employs completely randomized or randomized block experiments, can be used to simulate single or multiple trials across environments, enables genotype by environment interaction by adding random variety effects, and finally includes repeated measures in time following a constant, linear or quadratic pattern in time possibly with some form of autocorrelation. The model also allows to add a set of reference varieties to the GM plants and its comparator to assess the natural variation which can then be used to set limits of concern for equivalence testing. The different count distributions are described in some detail and some examples of how to use the simulation model to study various aspects, including a prospective power analysis, are provided.

A statistical simulation model for field testing of non-target organisms in environmental risk assessment of genetically modified plants

PubMed Central

Goedhart, Paul W; van der Voet, Hilko; Baldacchino, Ferdinando; Arpaia, Salvatore

2014-01-01

Genetic modification of plants may result in unintended effects causing potentially adverse effects on the environment. A comparative safety assessment is therefore required by authorities, such as the European Food Safety Authority, in which the genetically modified plant is compared with its conventional counterpart. Part of the environmental risk assessment is a comparative field experiment in which the effect on non-target organisms is compared. Statistical analysis of such trials come in two flavors: difference testing and equivalence testing. It is important to know the statistical properties of these, for example, the power to detect environmental change of a given magnitude, before the start of an experiment. Such prospective power analysis can best be studied by means of a statistical simulation model. This paper describes a general framework for simulating data typically encountered in environmental risk assessment of genetically modified plants. The simulation model, available as Supplementary Material, can be used to generate count data having different statistical distributions possibly with excess-zeros. In addition the model employs completely randomized or randomized block experiments, can be used to simulate single or multiple trials across environments, enables genotype by environment interaction by adding random variety effects, and finally includes repeated measures in time following a constant, linear or quadratic pattern in time possibly with some form of autocorrelation. The model also allows to add a set of reference varieties to the GM plants and its comparator to assess the natural variation which can then be used to set limits of concern for equivalence testing. The different count distributions are described in some detail and some examples of how to use the simulation model to study various aspects, including a prospective power analysis, are provided. PMID:24834325

Lower incisor inclination regarding different reference planes.

PubMed

Zataráin, Brenda; Avila, Josué; Moyaho, Angeles; Carrasco, Rosendo; Velasco, Carmen

2016-09-01

The purpose of this study was to assess the degree of lower incisor inclination with respect to different reference planes. It was an observational, analytical, longitudinal, prospective study conducted on 100 lateral cephalograms which were corrected according to the photograph in natural head position in order to draw the true vertical plane (TVP). The incisor mandibular plane angle (IMPA) was compensated to eliminate the variation of the mandibular plane growth type with the formula "FMApx.- 25 (FMA) + IMPApx. = compensated IMPA (IMPACOM)". As the data followed normal distribution determined by the KolmogorovSmirnov test, parametric tests were used for the statistical analysis, Ttest, ANOVA and Pearson coefficient correlation test. Statistical analysis was performed using a statistical significance of p <0.05. There is correlation between TVP and NB line (NB) (0.8614), Frankfort mandibular incisor angle (FMIA) (0.8894), IMPA (0.6351), Apo line (Apo) (0.609), IMPACOM (0.8895) and McHorris angle (MH) (0.7769). ANOVA showed statistically significant differences between the means for the 7 variables with 95% confidence level, P=0.0001. The multiple range test showed no significant difference among means: APoNB (0.88), IMPAMH (0.36), IMPANB (0.65), FMIAIMPACOM (0.01), FMIATVP (0.18), TVPIMPACOM (0.17). There was correlation among all reference planes. There were statistically significant differences among the means of the planes measured, except for IMPACOM, FMIA and TVP. The IMPA differed significantly from the IMPACOM. The compensated IMPA and the FMIA did not differ significantly from the TVP. The true horizontal plane was mismatched with Frankfort plane in 84% of the sample with a range of 19°. The true vertical plane is adequate for measuring lower incisor inclination. Sociedad Argentina de Investigación Odontológica.

Similitude assessment method for comparing PMHS response data from impact loading across multiple test devices.

PubMed

Dooley, Christopher J; Tenore, Francesco V; Gayzik, F Scott; Merkle, Andrew C

2018-04-27

Biological tissue testing is inherently susceptible to the wide range of variability specimen to specimen. A primary resource for encapsulating this range of variability is the biofidelity response corridor or BRC. In the field of injury biomechanics, BRCs are often used for development and validation of both physical, such as anthropomorphic test devices, and computational models. For the purpose of generating corridors, post-mortem human surrogates were tested across a range of loading conditions relevant to under-body blast events. To sufficiently cover the wide range of input conditions, a relatively small number of tests were performed across a large spread of conditions. The high volume of required testing called for leveraging the capabilities of multiple impact test facilities, all with slight variations in test devices. A method for assessing similitude of responses between test devices was created as a metric for inclusion of a response in the resulting BRC. The goal of this method was to supply a statistically sound, objective method to assess the similitude of an individual response against a set of responses to ensure that the BRC created from the set was affected primarily by biological variability, not anomalies or differences stemming from test devices. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multiple Intelligences Profiles of Children with Attention Deficit and Hyperactivity Disorder in Comparison with Nonattention Deficit and Hyperactivity Disorder.

PubMed

Najafi, Mostafa; Akouchekian, Shahla; Ghaderi, Alireza; Mahaki, Behzad; Rezaei, Mariam

2017-01-01

Attention deficit and hyperactivity disorder (ADHD) is a common psychological problem during childhood. This study aimed to evaluate multiple intelligences profiles of children with ADHD in comparison with non-ADHD. This cross-sectional descriptive analytical study was done on 50 children of 6-13 years old in two groups of with and without ADHD. Children with ADHD were referred to Clinics of Child and Adolescent Psychiatry, Isfahan University of Medical Sciences, in 2014. Samples were selected based on clinical interview (based on Diagnostic and Statistical Manual of Mental Disorders IV and parent-teacher strengths and difficulties questionnaire), which was done by psychiatrist and psychologist. Raven intelligence quotient (IQ) test was used, and the findings were compared to the results of multiple intelligences test. Data analysis was done using a multivariate analysis of covariance using SPSS20 software. Comparing the profiles of multiple intelligence among two groups, there are more kinds of multiple intelligences in control group than ADHD group, a difference which has been more significant in logical, interpersonal, and intrapersonal intelligence ( P < 0.05). There was no significant difference with the other kinds of multiple intelligences in two groups ( P > 0.05). The IQ average score in the control group and ADHD group was 102.42 ± 16.26 and 96.72 ± 16.06, respectively, that reveals the negative effect of ADHD on IQ average value. There was an insignificance relationship between linguistic and naturalist intelligence ( P > 0.05). However, in other kinds of multiple intelligences, direct and significant relationships were observed ( P < 0.05). Since the levels of IQ (Raven test) and MI in control group were more significant than ADHD group, ADHD is likely to be associated with logical-mathematical, interpersonal, and intrapersonal profiles.

A Simple Test of Class-Level Genetic Association Can Reveal Novel Cardiometabolic Trait Loci.

PubMed

Qian, Jing; Nunez, Sara; Reed, Eric; Reilly, Muredach P; Foulkes, Andrea S

2016-01-01

Characterizing the genetic determinants of complex diseases can be further augmented by incorporating knowledge of underlying structure or classifications of the genome, such as newly developed mappings of protein-coding genes, epigenetic marks, enhancer elements and non-coding RNAs. We apply a simple class-level testing framework, termed Genetic Class Association Testing (GenCAT), to identify protein-coding gene association with 14 cardiometabolic (CMD) related traits across 6 publicly available genome wide association (GWA) meta-analysis data resources. GenCAT uses SNP-level meta-analysis test statistics across all SNPs within a class of elements, as well as the size of the class and its unique correlation structure, to determine if the class is statistically meaningful. The novelty of findings is evaluated through investigation of regional signals. A subset of findings are validated using recently updated, larger meta-analysis resources. A simulation study is presented to characterize overall performance with respect to power, control of family-wise error and computational efficiency. All analysis is performed using the GenCAT package, R version 3.2.1. We demonstrate that class-level testing complements the common first stage minP approach that involves individual SNP-level testing followed by post-hoc ascribing of statistically significant SNPs to genes and loci. GenCAT suggests 54 protein-coding genes at 41 distinct loci for the 13 CMD traits investigated in the discovery analysis, that are beyond the discoveries of minP alone. An additional application to biological pathways demonstrates flexibility in defining genetic classes. We conclude that it would be prudent to include class-level testing as standard practice in GWA analysis. GenCAT, for example, can be used as a simple, complementary and efficient strategy for class-level testing that leverages existing data resources, requires only summary level data in the form of test statistics, and adds significant value with respect to its potential for identifying multiple novel and clinically relevant trait associations.

A novel metric that quantifies risk stratification for evaluating diagnostic tests: The example of evaluating cervical-cancer screening tests across populations.

PubMed

Katki, Hormuzd A; Schiffman, Mark

2018-05-01

Our work involves assessing whether new biomarkers might be useful for cervical-cancer screening across populations with different disease prevalences and biomarker distributions. When comparing across populations, we show that standard diagnostic accuracy statistics (predictive values, risk-differences, Youden's index and Area Under the Curve (AUC)) can easily be misinterpreted. We introduce an intuitively simple statistic for a 2 × 2 table, Mean Risk Stratification (MRS): the average change in risk (pre-test vs. post-test) revealed for tested individuals. High MRS implies better risk separation achieved by testing. MRS has 3 key advantages for comparing test performance across populations with different disease prevalences and biomarker distributions. First, MRS demonstrates that conventional predictive values and the risk-difference do not measure risk-stratification because they do not account for test-positivity rates. Second, Youden's index and AUC measure only multiplicative relative gains in risk-stratification: AUC = 0.6 achieves only 20% of maximum risk-stratification (AUC = 0.9 achieves 80%). Third, large relative gains in risk-stratification might not imply large absolute gains if disease is rare, demonstrating a "high-bar" to justify population-based screening for rare diseases such as cancer. We illustrate MRS by our experience comparing the performance of cervical-cancer screening tests in China vs. the USA. The test with the worst AUC = 0.72 in China (visual inspection with acetic acid) provides twice the risk-stratification (i.e. MRS) of the test with best AUC = 0.83 in the USA (human papillomavirus and Pap cotesting) because China has three times more cervical precancer/cancer. MRS could be routinely calculated to better understand the clinical/public-health implications of standard diagnostic accuracy statistics. Published by Elsevier Inc.

Correlations of fatty acid supplementation, aeroallergens, shampoo, and ear cleanser with multiple parameters in pruritic dogs.

PubMed

Nesbitt, Gene H; Freeman, Lisa M; Hannah, Steven S

2004-01-01

Seventy-two pruritic dogs were fed one of four diets controlled for n-6:n-3 fatty acid ratios and total dietary intake of fatty acids. Multiple parameters were evaluated, including clinical and cytological findings, aeroallergen testing, microbial sampling techniques, and effects of an anti-fungal/antibacterial shampoo and ear cleanser. Significant correlations were observed between many clinical parameters, anatomical sampling sites, and microbial counts when data from the diet groups was combined. There were no statistically significant differences between individual diets for any of the clinical parameters. The importance of total clinical management in the control of pruritus was demonstrated.

Slow crack growth in spinel in water

NASA Technical Reports Server (NTRS)

Schwantes, S.; Elber, W.

1983-01-01

Magnesium aluminate spinel was tested in a water environment at room temperature to establish its slow crack-growth behavior. Ring specimens with artificial flaws on the outside surface were loaded hydraulically on the inside surface. The time to failure was measured. Various precracking techniques were evaluated and multiple precracks were used to minimize the scatter in the static fatigue tests. Statistical analysis techniques were developed to determine the strength and crack velocities for a single flaw. Slow crack-growth rupture was observed at stress intensities as low as 70 percent of K sub c. A strengthening effect was observed in specimens that had survived long-time static fatigue tests.

A step-up test procedure to find the minimum effective dose.

PubMed

Wang, Weizhen; Peng, Jianan

2015-01-01

It is of great interest to find the minimum effective dose (MED) in dose-response studies. A sequence of decreasing null hypotheses to find the MED is formulated under the assumption of nondecreasing dose response means. A step-up multiple test procedure that controls the familywise error rate (FWER) is constructed based on the maximum likelihood estimators for the monotone normal means. When the MED is equal to one, the proposed test is uniformly more powerful than Hsu and Berger's test (1999). Also, a simulation study shows a substantial power improvement for the proposed test over four competitors. Three R-codes are provided in Supplemental Materials for this article. Go to the publishers online edition of Journal of Biopharmaceutical Statistics to view the files.

Walking execution is not affected by divided attention in patients with multiple sclerosis with no disability, but there is a motor planning impairment.

PubMed

Nogueira, Leandro Alberto Calazans; Santos, Luciano Teixeira Dos; Sabino, Pollyane Galinari; Alvarenga, Regina Maria Papais; Thuler, Luiz Claudio Santos

2013-08-01

We analysed the cognitive influence on walking in multiple sclerosis (MS) patients, in the absence of clinical disability. A case-control study was conducted with 12 MS patients with no disability and 12 matched healthy controls. Subjects were referred for completion a timed walk test of 10 m and a 3D-kinematic analysis. Participants were instructed to walk at a comfortable speed in a dual-task (arithmetic task) condition, and motor planning was measured by mental chronometry. Scores of walking speed and cadence showed no statistically significant differences between the groups in the three conditions. The dual-task condition showed an increase in the double support duration in both groups. Motor imagery analysis showed statistically significant differences between real and imagined walking in patients. MS patients with no disability did not show any influence of divided attention on walking execution. However, motor planning was overestimated as compared with real walking.

SPICE: exploration and analysis of post-cytometric complex multivariate datasets.

PubMed

Roederer, Mario; Nozzi, Joshua L; Nason, Martha C

2011-02-01

Polychromatic flow cytometry results in complex, multivariate datasets. To date, tools for the aggregate analysis of these datasets across multiple specimens grouped by different categorical variables, such as demographic information, have not been optimized. Often, the exploration of such datasets is accomplished by visualization of patterns with pie charts or bar charts, without easy access to statistical comparisons of measurements that comprise multiple components. Here we report on algorithms and a graphical interface we developed for these purposes. In particular, we discuss thresholding necessary for accurate representation of data in pie charts, the implications for display and comparison of normalized versus unnormalized data, and the effects of averaging when samples with significant background noise are present. Finally, we define a statistic for the nonparametric comparison of complex distributions to test for difference between groups of samples based on multi-component measurements. While originally developed to support the analysis of T cell functional profiles, these techniques are amenable to a broad range of datatypes. Published 2011 Wiley-Liss, Inc.

Sequential Tests of Multiple Hypotheses Controlling Type I and II Familywise Error Rates

PubMed Central

Bartroff, Jay; Song, Jinlin

2014-01-01

This paper addresses the following general scenario: A scientist wishes to perform a battery of experiments, each generating a sequential stream of data, to investigate some phenomenon. The scientist would like to control the overall error rate in order to draw statistically-valid conclusions from each experiment, while being as efficient as possible. The between-stream data may differ in distribution and dimension but also may be highly correlated, even duplicated exactly in some cases. Treating each experiment as a hypothesis test and adopting the familywise error rate (FWER) metric, we give a procedure that sequentially tests each hypothesis while controlling both the type I and II FWERs regardless of the between-stream correlation, and only requires arbitrary sequential test statistics that control the error rates for a given stream in isolation. The proposed procedure, which we call the sequential Holm procedure because of its inspiration from Holm’s (1979) seminal fixed-sample procedure, shows simultaneous savings in expected sample size and less conservative error control relative to fixed sample, sequential Bonferroni, and other recently proposed sequential procedures in a simulation study. PMID:25092948

[Development of critical thinking skill evaluation scale for nursing students].

PubMed

You, So Young; Kim, Nam Cho

2014-04-01

To develop a Critical Thinking Skill Test for Nursing Students. The construct concepts were drawn from a literature review and in-depth interviews with hospital nurses and surveys were conducted among students (n=607) from nursing colleges. The data were collected from September 13 to November 23, 2012 and analyzed using the SAS program, 9.2 version. The KR 20 coefficient for reliability, difficulty index, discrimination index, item-total correlation and known group technique for validity were performed. Four domains and 27 skills were identified and 35 multiple choice items were developed. Thirty multiple choice items which had scores higher than .80 on the content validity index were selected for the pre test. From the analysis of the pre test data, a modified 30 items were selected for the main test. In the main test, the KR 20 coefficient was .70 and Corrected Item-Total Correlations range was .11-.38. There was a statistically significant difference between two academic systems (p=.001). The developed instrument is the first critical thinking skill test reflecting nursing perspectives in hospital settings and is expected to be utilized as a tool which contributes to improvement of the critical thinking ability of nursing students.

Accounting for Multiple Births in Neonatal and Perinatal Trials: Systematic Review and Case Study

PubMed Central

Hibbs, Anna Maria; Black, Dennis; Palermo, Lisa; Cnaan, Avital; Luan, Xianqun; Truog, William E; Walsh, Michele C; Ballard, Roberta A

2010-01-01

Objectives To determine the prevalence in the neonatal literature of statistical approaches accounting for the unique clustering patterns of multiple births. To explore the sensitivity of an actual trial to several analytic approaches to multiples. Methods A systematic review of recent perinatal trials assessed the prevalence of studies accounting for clustering of multiples. The NO CLD trial served as a case study of the sensitivity of the outcome to several statistical strategies. We calculated odds ratios using non-clustered (logistic regression) and clustered (generalized estimating equations, multiple outputation) analyses. Results In the systematic review, most studies did not describe the randomization of twins and did not account for clustering. Of those studies that did, exclusion of multiples and generalized estimating equations were the most common strategies. The NO CLD study included 84 infants with a sibling enrolled in the study. Multiples were more likely than singletons to be white and were born to older mothers (p<0.01). Analyses that accounted for clustering were statistically significant; analyses assuming independence were not. Conclusions The statistical approach to multiples can influence the odds ratio and width of confidence intervals, thereby affecting the interpretation of a study outcome. A minority of perinatal studies address this issue. PMID:19969305

Accounting for multiple births in neonatal and perinatal trials: systematic review and case study.

PubMed

Hibbs, Anna Maria; Black, Dennis; Palermo, Lisa; Cnaan, Avital; Luan, Xianqun; Truog, William E; Walsh, Michele C; Ballard, Roberta A

2010-02-01

To determine the prevalence in the neonatal literature of statistical approaches accounting for the unique clustering patterns of multiple births and to explore the sensitivity of an actual trial to several analytic approaches to multiples. A systematic review of recent perinatal trials assessed the prevalence of studies accounting for clustering of multiples. The Nitric Oxide to Prevent Chronic Lung Disease (NO CLD) trial served as a case study of the sensitivity of the outcome to several statistical strategies. We calculated odds ratios using nonclustered (logistic regression) and clustered (generalized estimating equations, multiple outputation) analyses. In the systematic review, most studies did not describe the random assignment of twins and did not account for clustering. Of those studies that did, exclusion of multiples and generalized estimating equations were the most common strategies. The NO CLD study included 84 infants with a sibling enrolled in the study. Multiples were more likely than singletons to be white and were born to older mothers (P < .01). Analyses that accounted for clustering were statistically significant; analyses assuming independence were not. The statistical approach to multiples can influence the odds ratio and width of confidence intervals, thereby affecting the interpretation of a study outcome. A minority of perinatal studies address this issue. Copyright 2010 Mosby, Inc. All rights reserved.

Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics

USGS Publications Warehouse

Lee, L.; Helsel, D.

2005-01-01

Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these "less thans" is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards. ?? 2005 Elsevier Ltd. All rights reserved.

An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder.

PubMed

Werling, Donna M; Brand, Harrison; An, Joon-Yong; Stone, Matthew R; Zhu, Lingxue; Glessner, Joseph T; Collins, Ryan L; Dong, Shan; Layer, Ryan M; Markenscoff-Papadimitriou, Eirene; Farrell, Andrew; Schwartz, Grace B; Wang, Harold Z; Currall, Benjamin B; Zhao, Xuefang; Dea, Jeanselle; Duhn, Clif; Erdman, Carolyn A; Gilson, Michael C; Yadav, Rachita; Handsaker, Robert E; Kashin, Seva; Klei, Lambertus; Mandell, Jeffrey D; Nowakowski, Tomasz J; Liu, Yuwen; Pochareddy, Sirisha; Smith, Louw; Walker, Michael F; Waterman, Matthew J; He, Xin; Kriegstein, Arnold R; Rubenstein, John L; Sestan, Nenad; McCarroll, Steven A; Neale, Benjamin M; Coon, Hilary; Willsey, A Jeremy; Buxbaum, Joseph D; Daly, Mark J; State, Matthew W; Quinlan, Aaron R; Marth, Gabor T; Roeder, Kathryn; Devlin, Bernie; Talkowski, Michael E; Sanders, Stephan J

2018-05-01

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

Short interpregnancy interval and low birth weight: A role of parity.

PubMed

Merklinger-Gruchala, Anna; Jasienska, Grazyna; Kapiszewska, Maria

2015-01-01

Short interpregnancy intervals (IPI) and high parity may be synergistically associated with the risk of unfavorable pregnancy outcomes. This study tests if the effect of short IPI on the odds ratio for low birth weight (LBW, <2,500 g) differs across parity status. The study was carried out on the birth registry sample of almost 40,000 singleton, live-born infants who were delivered between the years 1995 and 2009 to multiparous mothers whose residence at the time of infant's birth was the city of Krakow. Multiple logistic regression analyses were used for testing the effect of IPI on the odds ratio (OR) for LBW, after controlling for employment, educational and marital status, parity, sex of the child, maternal and gestational age. Stratified analyses (according to parity) and tests for interaction were performed. Very short IPI (0-5 months) was associated with an increased OR for LBW, but only among high parity mothers with three or more births (OR = 2.64; 95% CI 1.45-4.80). The test for interaction between very short IPI and parity on the OR for LBW was statistically significant after adjustment for multiple comparisons (P = 0.04). Among low parity mothers (two births) no statistically significant associations were found between IPI and LBW after standardization. Parity may modify the association between short birth spacing and LBW. Women with very short IPI and high parity may have a higher risk of having LBW infants than those with very short IPI but low parity. © 2015 Wiley Periodicals, Inc.

The power to detect linkage in complex disease by means of simple LOD-score analyses.

PubMed Central

Greenberg, D A; Abreu, P; Hodge, S E

1998-01-01

Maximum-likelihood analysis (via LOD score) provides the most powerful method for finding linkage when the mode of inheritance (MOI) is known. However, because one must assume an MOI, the application of LOD-score analysis to complex disease has been questioned. Although it is known that one can legitimately maximize the maximum LOD score with respect to genetic parameters, this approach raises three concerns: (1) multiple testing, (2) effect on power to detect linkage, and (3) adequacy of the approximate MOI for the true MOI. We evaluated the power of LOD scores to detect linkage when the true MOI was complex but a LOD score analysis assumed simple models. We simulated data from 14 different genetic models, including dominant and recessive at high (80%) and low (20%) penetrances, intermediate models, and several additive two-locus models. We calculated LOD scores by assuming two simple models, dominant and recessive, each with 50% penetrance, then took the higher of the two LOD scores as the raw test statistic and corrected for multiple tests. We call this test statistic "MMLS-C." We found that the ELODs for MMLS-C are >=80% of the ELOD under the true model when the ELOD for the true model is >=3. Similarly, the power to reach a given LOD score was usually >=80% that of the true model, when the power under the true model was >=60%. These results underscore that a critical factor in LOD-score analysis is the MOI at the linked locus, not that of the disease or trait per se. Thus, a limited set of simple genetic models in LOD-score analysis can work well in testing for linkage. PMID:9718328

The power to detect linkage in complex disease by means of simple LOD-score analyses.

PubMed

Greenberg, D A; Abreu, P; Hodge, S E

1998-09-01

Maximum-likelihood analysis (via LOD score) provides the most powerful method for finding linkage when the mode of inheritance (MOI) is known. However, because one must assume an MOI, the application of LOD-score analysis to complex disease has been questioned. Although it is known that one can legitimately maximize the maximum LOD score with respect to genetic parameters, this approach raises three concerns: (1) multiple testing, (2) effect on power to detect linkage, and (3) adequacy of the approximate MOI for the true MOI. We evaluated the power of LOD scores to detect linkage when the true MOI was complex but a LOD score analysis assumed simple models. We simulated data from 14 different genetic models, including dominant and recessive at high (80%) and low (20%) penetrances, intermediate models, and several additive two-locus models. We calculated LOD scores by assuming two simple models, dominant and recessive, each with 50% penetrance, then took the higher of the two LOD scores as the raw test statistic and corrected for multiple tests. We call this test statistic "MMLS-C." We found that the ELODs for MMLS-C are >=80% of the ELOD under the true model when the ELOD for the true model is >=3. Similarly, the power to reach a given LOD score was usually >=80% that of the true model, when the power under the true model was >=60%. These results underscore that a critical factor in LOD-score analysis is the MOI at the linked locus, not that of the disease or trait per se. Thus, a limited set of simple genetic models in LOD-score analysis can work well in testing for linkage.

Psychometrics of Multiple Choice Questions with Non-Functioning Distracters: Implications to Medical Education.

PubMed

Deepak, Kishore K; Al-Umran, Khalid Umran; AI-Sheikh, Mona H; Dkoli, B V; Al-Rubaish, Abdullah

2015-01-01

The functionality of distracters in a multiple choice question plays a very important role. We examined the frequency and impact of functioning and non-functioning distracters on psychometric properties of 5-option items in clinical disciplines. We analyzed item statistics of 1115 multiple choice questions from 15 summative assessments of undergraduate medical students and classified the items into five groups by their number of non-functioning distracters. We analyzed the effect of varying degree of non-functionality ranging from 0 to 4, on test reliability, difficulty index, discrimination index and point biserial correlation. The non-functionality of distracters inversely affected the test reliability and quality of items in a predictable manner. The non-functioning distracters made the items easier and lowered the discrimination index significantly. Three non-functional distracters in a 5-option MCQ significantly affected all psychometric properties (p < 0.5). The corrected point biserial correlation revealed that the items with 3 functional options were psychometrically as effective as 5-option items. Our study reveals that a multiple choice question with 3 functional options provides lower most limit of item format that has adequate psychometric property. The test containing items with less number of functioning options have significantly lower reliability. The distracter function analysis and revision of nonfunctioning distracters can serve as important methods to improve the psychometrics and reliability of assessment.

Dynamics and regulation of the southern brook trout (Salvelinus fontinalis) population in an Appalachian stream

Treesearch

Gary D. Grossman; Robert E. Ratajczak; C. Michael Wagner; J. Todd Petty

2010-01-01

1. We used information theoretic statistics [Akaike’s Information Criterion (AIC)] and regression analysis in a multiple hypothesis testing approach to assess the processes capable of explaining long-term demographic variation in a lightly exploited brook trout population in Ball Creek, NC. We sampled a 100-m-long second-order site during both spring and autumn 1991–...

Testing biological liquid samples using modified m-line spectroscopy method

NASA Astrophysics Data System (ADS)

Augusciuk, Elzbieta; Rybiński, Grzegorz

2005-09-01

Non-chemical method of detection of sugar concentration in biological (animal and plant source) liquids has been investigated. Simplified set was build to show the easy way of carrying out the survey and to make easy to gather multiple measurements for error detecting and statistics. Method is suggested as easy and cheap alternative for chemical methods of measuring sugar concentration, but needing a lot effort to be made precise.

Defining window-boundaries for genomic analyses using smoothing spline techniques

DOE PAGES

Beissinger, Timothy M.; Rosa, Guilherme J.M.; Kaeppler, Shawn M.; ...

2015-04-17

High-density genomic data is often analyzed by combining information over windows of adjacent markers. Interpretation of data grouped in windows versus at individual locations may increase statistical power, simplify computation, reduce sampling noise, and reduce the total number of tests performed. However, use of adjacent marker information can result in over- or under-smoothing, undesirable window boundary specifications, or highly correlated test statistics. We introduce a method for defining windows based on statistically guided breakpoints in the data, as a foundation for the analysis of multiple adjacent data points. This method involves first fitting a cubic smoothing spline to the datamore » and then identifying the inflection points of the fitted spline, which serve as the boundaries of adjacent windows. This technique does not require prior knowledge of linkage disequilibrium, and therefore can be applied to data collected from individual or pooled sequencing experiments. Moreover, in contrast to existing methods, an arbitrary choice of window size is not necessary, since these are determined empirically and allowed to vary along the genome.« less

In defence of model-based inference in phylogeography

PubMed Central

Beaumont, Mark A.; Nielsen, Rasmus; Robert, Christian; Hey, Jody; Gaggiotti, Oscar; Knowles, Lacey; Estoup, Arnaud; Panchal, Mahesh; Corander, Jukka; Hickerson, Mike; Sisson, Scott A.; Fagundes, Nelson; Chikhi, Lounès; Beerli, Peter; Vitalis, Renaud; Cornuet, Jean-Marie; Huelsenbeck, John; Foll, Matthieu; Yang, Ziheng; Rousset, Francois; Balding, David; Excoffier, Laurent

2017-01-01

Recent papers have promoted the view that model-based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model-based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model-based inference in population genetics. PMID:29284924

Prolonged instability prior to a regime shift

USGS Publications Warehouse

Spanbauer, Trisha; Allen, Craig R.; Angeler, David G.; Eason, Tarsha; Fritz, Sherilyn C.; Garmestani, Ahjond S.; Nash, Kirsty L.; Stone, Jeffery R.

2014-01-01

Regime shifts are generally defined as the point of ‘abrupt’ change in the state of a system. However, a seemingly abrupt transition can be the product of a system reorganization that has been ongoing much longer than is evident in statistical analysis of a single component of the system. Using both univariate and multivariate statistical methods, we tested a long-term high-resolution paleoecological dataset with a known change in species assemblage for a regime shift. Analysis of this dataset with Fisher Information and multivariate time series modeling showed that there was a∼2000 year period of instability prior to the regime shift. This period of instability and the subsequent regime shift coincide with regional climate change, indicating that the system is undergoing extrinsic forcing. Paleoecological records offer a unique opportunity to test tools for the detection of thresholds and stable-states, and thus to examine the long-term stability of ecosystems over periods of multiple millennia.

Human leukocyte antigens in Gulf War veterans with chronic unexplained multiple symptoms.

PubMed

O'Bryan, Thomas A; Romano, Paula J; Zangwill, Bruce C

2003-12-01

Several articles have suggested that immune dysregulation related to Gulf War deployment may be involved in chronic illnesses with an unclear etiology among Gulf War veterans. To determine whether genetic susceptibility related to the human leukocyte antigen (HLA) system might play a role in development of the veterans' illnesses, we examined the frequency distribution of HLA A, B, DR, and DQ antigens from symptomatic veterans residing in south-central Pennsylvania compared with a local healthy population database. Only HLA-A28 demonstrated statistical significance. A28 was present in 7 (21.9%) of 32 of the veterans and 15 (6.9%) of 217 of the healthy population (p = 0.01, Fisher's exact test). This accounts for a minority of the ill veterans tested and is not statistically significant when corrected for the number of antigens determined. We conclude that specific HLA antigens are not strongly associated with the illnesses of Gulf War veterans.

Equivalence Testing of Complex Particle Size Distribution Profiles Based on Earth Mover's Distance.

PubMed

Hu, Meng; Jiang, Xiaohui; Absar, Mohammad; Choi, Stephanie; Kozak, Darby; Shen, Meiyu; Weng, Yu-Ting; Zhao, Liang; Lionberger, Robert

2018-04-12

Particle size distribution (PSD) is an important property of particulates in drug products. In the evaluation of generic drug products formulated as suspensions, emulsions, and liposomes, the PSD comparisons between a test product and the branded product can provide useful information regarding in vitro and in vivo performance. Historically, the FDA has recommended the population bioequivalence (PBE) statistical approach to compare the PSD descriptors D50 and SPAN from test and reference products to support product equivalence. In this study, the earth mover's distance (EMD) is proposed as a new metric for comparing PSD particularly when the PSD profile exhibits complex distribution (e.g., multiple peaks) that is not accurately described by the D50 and SPAN descriptor. EMD is a statistical metric that measures the discrepancy (distance) between size distribution profiles without a prior assumption of the distribution. PBE is then adopted to perform statistical test to establish equivalence based on the calculated EMD distances. Simulations show that proposed EMD-based approach is effective in comparing test and reference profiles for equivalence testing and is superior compared to commonly used distance measures, e.g., Euclidean and Kolmogorov-Smirnov distances. The proposed approach was demonstrated by evaluating equivalence of cyclosporine ophthalmic emulsion PSDs that were manufactured under different conditions. Our results show that proposed approach can effectively pass an equivalent product (e.g., reference product against itself) and reject an inequivalent product (e.g., reference product against negative control), thus suggesting its usefulness in supporting bioequivalence determination of a test product to the reference product which both possess multimodal PSDs.

Physique and Performance of Young Wheelchair Basketball Players in Relation with Classification

PubMed Central

Zancanaro, Carlo

2015-01-01

The relationships among physical characteristics, performance, and functional ability classification of younger wheelchair basketball players have been barely investigated to date. The purpose of this work was to assess anthropometry, body composition, and performance in sport-specific field tests in a national sample of Italian younger wheelchair basketball players as well as to evaluate the association of these variables with the players’ functional ability classification and game-related statistics. Several anthropometric measurements were obtained for 52 out of 91 eligible players nationwide. Performance was assessed in seven sport-specific field tests (5m sprint, 20m sprint with ball, suicide, maximal pass, pass for accuracy, spot shot and lay-ups) and game-related statistics (free-throw points scored per match, two- and three-point field-goals scored per match, and their sum). Association between variables, and predictivity was assessed by correlation and regression analysis, respectively. Players were grouped into four Classes of increasing functional ability (A-D). One-way ANOVA with Bonferroni’s correction for multiple comparisons was used to assess differences between Classes. Sitting height and functional ability Class especially correlated with performance outcomes, but wheelchair basketball experience and skinfolds did not. Game-related statistics and sport-specific field-test scores all showed significant correlation with each other. Upper arm circumference and/or maximal pass and lay-ups test scores were able to explain 42 to 59% of variance in game-related statistics (P<0.001). A clear difference in performance was only found for functional ability Class A and D. Conclusion: In younger wheelchair basketball players, sitting height positively contributes to performance. The maximal pass and lay-ups test should be carefully considered in younger wheelchair basketball training plans. Functional ability Class reflects to a limited extent the actual differences in performance. PMID:26606681

Integrative set enrichment testing for multiple omics platforms

PubMed Central

2011-01-01

Background Enrichment testing assesses the overall evidence of differential expression behavior of the elements within a defined set. When we have measured many molecular aspects, e.g. gene expression, metabolites, proteins, it is desirable to assess their differential tendencies jointly across platforms using an integrated set enrichment test. In this work we explore the properties of several methods for performing a combined enrichment test using gene expression and metabolomics as the motivating platforms. Results Using two simulation models we explored the properties of several enrichment methods including two novel methods: the logistic regression 2-degree of freedom Wald test and the 2-dimensional permutation p-value for the sum-of-squared statistics test. In relation to their univariate counterparts we find that the joint tests can improve our ability to detect results that are marginal univariately. We also find that joint tests improve the ranking of associated pathways compared to their univariate counterparts. However, there is a risk of Type I error inflation with some methods and self-contained methods lose specificity when the sets are not representative of underlying association. Conclusions In this work we show that consideration of data from multiple platforms, in conjunction with summarization via a priori pathway information, leads to increased power in detection of genomic associations with phenotypes. PMID:22118224

Effect of repeated simulated clinical use and sterilization on the cutting efficiency and flexibility of Hyflex CM nickel-titanium rotary files.

PubMed

Seago, Scott T; Bergeron, Brian E; Kirkpatrick, Timothy C; Roberts, Mark D; Roberts, Howard W; Himel, Van T; Sabey, Kent A

2015-05-01

Recent nickel-titanium manufacturing processes have resulted in an alloy that remains in a twinned martensitic phase at operating temperature. This alloy has been shown to have increased flexibility with added tolerance to cyclic and torsional fatigue. The aim of this study was to assess the effect of repeated simulated clinical use and sterilization on cutting efficiency and flexibility of Hyflex CM rotary files. Cutting efficiency was determined by measuring the load required to maintain a constant feed rate while instrumenting simulated canals. Flexibility was determined by using a 3-point bending test. Files were autoclaved after each use according to the manufacturer's recommendations. Files were tested through 10 simulated clinical uses. For cutting efficiency, mean data were analyzed by using multiple factor analysis of variance and the Dunnett post hoc test (P < .05). For flexibility, mean data were analyzed by using Levene's Test of Equality of Error and a general linear model (P < .05). No statistically significant decrease in cutting efficiency was noted in groups 2, 5, 6, and 7. A statistically significant decrease in cutting efficiency was noted in groups 3, 4, 8, 9, and 10. No statistically significant decrease in flexibility was noted in groups 2, 3, and 7. A statistically significant decrease in flexibility was noted in groups 4, 5, 6, 8, 9, 10, and 11. Repeated simulated clinical use and sterilization showed no effect on cutting efficiency through 1 use and no effect on flexibility through 2 uses. Published by Elsevier Inc.

Statistical Analysis of CFD Solutions from the 6th AIAA CFD Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Derlaga, Joseph M.; Morrison, Joseph H.

2017-01-01

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 uid dynam- ics codes. The solutions were obtained by code developers and users from North America, Europe, Asia, and South America using both common and custom grid sequencees as well as multiple turbulence models for the June 2016 6th AIAA CFD Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic con guration for this workshop was the Common Research Model subsonic transport wing- body previously used for both the 4th and 5th Drag Prediction Workshops. 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.

Speciation and antimicrobial resistance of Enterococci isolated from recreational beaches in Malaysia.

PubMed

Dada, Ayokunle Christopher; Ahmad, Asmat; Usup, Gires; Heng, Lee Yook

2013-02-01

We report the first study on the occurrence of antibiotic-resistant enterococci in coastal bathing waters in Malaysia. One hundred and sixty-five enterococci isolates recovered from two popular recreational beaches in Malaysia were speciated and screened for antibiotic resistance to a total of eight antibiotics. Prevalence of Enterococcus faecalis and Enterococcus faecium was highest in both beaches. E. faecalis/E. faecium ratio was 0.384:1 and 0.375:1, respectively, for isolates from Port Dickson (PD) and Bagan Lalang (BL). Analysis of Fisher's exact test showed that association of prevalence of E. faecalis and E. faecium with considered locations was not statistically significant (p < 0.05). Chi-square test revealed significant differences (χ(2) = 82.630, df = 20, p < 0.001) in the frequency of occurrence of enterococci isolates from the considered sites. Resistance was highest to nalidixic acid (94.84 %) and least for chloramphenicol (8.38 %). One-way ANOVA using Tukey-Kramer multiple comparison test showed that resistance to ampicillin was higher in PD beach isolates than BL isolates and the difference was extremely statistically significant (p < 0.0001). Frequency of occurrence of multiple antibiotic resistance (MAR) isolates were higher for PD beach water (64.29 %) as compared to BL beach water (13.51 %), while MAR indices ranged between 0.198 and 0.48. The results suggest that samples from Port Dickson may contain MAR bacteria and that this could be due to high-risk faecal contamination from sewage discharge pipes that drain into the sea water.

Generalized functional linear models for gene-based case-control association studies.

PubMed

Fan, Ruzong; Wang, Yifan; Mills, James L; Carter, Tonia C; Lobach, Iryna; Wilson, Alexander F; Bailey-Wilson, Joan E; Weeks, Daniel E; Xiong, Momiao

2014-11-01

By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene region are disease related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease datasets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. © 2014 WILEY PERIODICALS, INC.

Generalized Functional Linear Models for Gene-based Case-Control Association Studies

PubMed Central

Mills, James L.; Carter, Tonia C.; Lobach, Iryna; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Weeks, Daniel E.; Xiong, Momiao

2014-01-01

By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene are disease-related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease data sets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. PMID:25203683

Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

PubMed Central

Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

2014-01-01

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

Multiple choice questions can be designed or revised to challenge learners' critical thinking.

PubMed

Tractenberg, Rochelle E; Gushta, Matthew M; Mulroney, Susan E; Weissinger, Peggy A

2013-12-01

Multiple choice (MC) questions from a graduate physiology course were evaluated by cognitive-psychology (but not physiology) experts, and analyzed statistically, in order to test the independence of content expertise and cognitive complexity ratings of MC items. Integration of higher order thinking into MC exams is important, but widely known to be challenging-perhaps especially when content experts must think like novices. Expertise in the domain (content) may actually impede the creation of higher-complexity items. Three cognitive psychology experts independently rated cognitive complexity for 252 multiple-choice physiology items using a six-level cognitive complexity matrix that was synthesized from the literature. Rasch modeling estimated item difficulties. The complexity ratings and difficulty estimates were then analyzed together to determine the relative contributions (and independence) of complexity and difficulty to the likelihood of correct answers on each item. Cognitive complexity was found to be statistically independent of difficulty estimates for 88 % of items. Using the complexity matrix, modifications were identified to increase some item complexities by one level, without affecting the item's difficulty. Cognitive complexity can effectively be rated by non-content experts. The six-level complexity matrix, if applied by faculty peer groups trained in cognitive complexity and without domain-specific expertise, could lead to improvements in the complexity targeted with item writing and revision. Targeting higher order thinking with MC questions can be achieved without changing item difficulties or other test characteristics, but this may be less likely if the content expert is left to assess items within their domain of expertise.

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.

PubMed

He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana

2017-09-07

Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

What do results from coordinate-based meta-analyses tell us?

PubMed

Albajes-Eizagirre, Anton; Radua, Joaquim

2018-08-01

Coordinate-based meta-analyses (CBMA) methods, such as Activation Likelihood Estimation (ALE) and Seed-based d Mapping (SDM), have become an invaluable tool for summarizing the findings of voxel-based neuroimaging studies. However, the progressive sophistication of these methods may have concealed two particularities of their statistical tests. Common univariate voxelwise tests (such as the t/z-tests used in SPM and FSL) detect voxels that activate, or voxels that show differences between groups. Conversely, the tests conducted in CBMA test for "spatial convergence" of findings, i.e., they detect regions where studies report "more peaks than in most regions", regions that activate "more than most regions do", or regions that show "larger differences between groups than most regions do". The first particularity is that these tests rely on two spatial assumptions (voxels are independent and have the same probability to have a "false" peak), whose violation may make their results either conservative or liberal, though fortunately current versions of ALE, SDM and some other methods consider these assumptions. The second particularity is that the use of these tests involves an important paradox: the statistical power to detect a given effect is higher if there are no other effects in the brain, whereas lower in presence of multiple effects. Copyright © 2018 Elsevier Inc. All rights reserved.

How to Assess the Existence of Competing Strategies in Cognitive Tasks: A Primer on the Fixed-Point Property

PubMed Central

van Maanen, Leendert; de Jong, Ritske; van Rijn, Hedderik

2014-01-01

When multiple strategies can be used to solve a type of problem, the observed response time distributions are often mixtures of multiple underlying base distributions each representing one of these strategies. For the case of two possible strategies, the observed response time distributions obey the fixed-point property. That is, there exists one reaction time that has the same probability of being observed irrespective of the actual mixture proportion of each strategy. In this paper we discuss how to compute this fixed-point, and how to statistically assess the probability that indeed the observed response times are generated by two competing strategies. Accompanying this paper is a free R package that can be used to compute and test the presence or absence of the fixed-point property in response time data, allowing for easy to use tests of strategic behavior. PMID:25170893

Dispositional optimism and sleep quality: a test of mediating pathways

PubMed Central

Cribbet, Matthew; Kent de Grey, Robert G.; Cronan, Sierra; Trettevik, Ryan; Smith, Timothy W.

2016-01-01

Dispositional optimism has been related to beneficial influences on physical health outcomes. However, its links to global sleep quality and the psychological mediators responsible for such associations are less studied. This study thus examined if trait optimism predicted global sleep quality, and if measures of subjective well-being were statistical mediators of such links. A community sample of 175 participants (93 men, 82 women) completed measures of trait optimism, depression, and life satisfaction. Global sleep quality was assessed using the Pittsburgh Sleep Quality Index. Results indicated that trait optimism was a strong predictor of better PSQI global sleep quality. Moreover, this association was mediated by depression and life satisfaction in both single and multiple mediator models. These results highlight the importance of optimism for the restorative process of sleep, as well as the utility of multiple mediator models in testing distinct psychological pathways. PMID:27592128

Dispositional optimism and sleep quality: a test of mediating pathways.

PubMed

Uchino, Bert N; Cribbet, Matthew; de Grey, Robert G Kent; Cronan, Sierra; Trettevik, Ryan; Smith, Timothy W

2017-04-01

Dispositional optimism has been related to beneficial influences on physical health outcomes. However, its links to global sleep quality and the psychological mediators responsible for such associations are less studied. This study thus examined if trait optimism predicted global sleep quality, and if measures of subjective well-being were statistical mediators of such links. A community sample of 175 participants (93 men, 82 women) completed measures of trait optimism, depression, and life satisfaction. Global sleep quality was assessed using the Pittsburgh Sleep Quality Index. Results indicated that trait optimism was a strong predictor of better PSQI global sleep quality. Moreover, this association was mediated by depression and life satisfaction in both single and multiple mediator models. These results highlight the importance of optimism for the restorative process of sleep, as well as the utility of multiple mediator models in testing distinct psychological pathways.

Drug safety data mining with a tree-based scan statistic.

PubMed

Kulldorff, Martin; Dashevsky, Inna; Avery, Taliser R; Chan, Arnold K; Davis, Robert L; Graham, David; Platt, Richard; Andrade, Susan E; Boudreau, Denise; Gunter, Margaret J; Herrinton, Lisa J; Pawloski, Pamala A; Raebel, Marsha A; Roblin, Douglas; Brown, Jeffrey S

2013-05-01

In post-marketing drug safety surveillance, data mining can potentially detect rare but serious adverse events. Assessing an entire collection of drug-event pairs is traditionally performed on a predefined level of granularity. It is unknown a priori whether a drug causes a very specific or a set of related adverse events, such as mitral valve disorders, all valve disorders, or different types of heart disease. This methodological paper evaluates the tree-based scan statistic data mining method to enhance drug safety surveillance. We use a three-million-member electronic health records database from the HMO Research Network. Using the tree-based scan statistic, we assess the safety of selected antifungal and diabetes drugs, simultaneously evaluating overlapping diagnosis groups at different granularity levels, adjusting for multiple testing. Expected and observed adverse event counts were adjusted for age, sex, and health plan, producing a log likelihood ratio test statistic. Out of 732 evaluated disease groupings, 24 were statistically significant, divided among 10 non-overlapping disease categories. Five of the 10 signals are known adverse effects, four are likely due to confounding by indication, while one may warrant further investigation. The tree-based scan statistic can be successfully applied as a data mining tool in drug safety surveillance using observational data. The total number of statistical signals was modest and does not imply a causal relationship. Rather, data mining results should be used to generate candidate drug-event pairs for rigorous epidemiological studies to evaluate the individual and comparative safety profiles of drugs. Copyright © 2013 John Wiley & Sons, Ltd.

Family-Based Rare Variant Association Analysis: A Fast and Efficient Method of Multivariate Phenotype Association Analysis.

PubMed

Wang, Longfei; Lee, Sungyoung; Gim, Jungsoo; Qiao, Dandi; Cho, Michael; Elston, Robert C; Silverman, Edwin K; Won, Sungho

2016-09-01

Family-based designs have been repeatedly shown to be powerful in detecting the significant rare variants associated with human diseases. Furthermore, human diseases are often defined by the outcomes of multiple phenotypes, and thus we expect multivariate family-based analyses may be very efficient in detecting associations with rare variants. However, few statistical methods implementing this strategy have been developed for family-based designs. In this report, we describe one such implementation: the multivariate family-based rare variant association tool (mFARVAT). mFARVAT is a quasi-likelihood-based score test for rare variant association analysis with multiple phenotypes, and tests both homogeneous and heterogeneous effects of each variant on multiple phenotypes. Simulation results show that the proposed method is generally robust and efficient for various disease models, and we identify some promising candidate genes associated with chronic obstructive pulmonary disease. The software of mFARVAT is freely available at http://healthstat.snu.ac.kr/software/mfarvat/, implemented in C++ and supported on Linux and MS Windows. © 2016 WILEY PERIODICALS, INC.

A Simple Illustration for the Need of Multiple Comparison Procedures

ERIC Educational Resources Information Center

Carter, Rickey E.

2010-01-01

Statistical adjustments to accommodate multiple comparisons are routinely covered in introductory statistical courses. The fundamental rationale for such adjustments, however, may not be readily understood. This article presents a simple illustration to help remedy this.

Global Sensitivity Analysis of Environmental Systems via Multiple Indices based on Statistical Moments of Model Outputs

NASA Astrophysics Data System (ADS)

Guadagnini, A.; Riva, M.; Dell'Oca, A.

2017-12-01

We propose to ground sensitivity of uncertain parameters of environmental models on a set of indices based on the main (statistical) moments, i.e., mean, variance, skewness and kurtosis, of the probability density function (pdf) of a target model output. This enables us to perform Global Sensitivity Analysis (GSA) of a model in terms of multiple statistical moments and yields a quantification of the impact of model parameters on features driving the shape of the pdf of model output. Our GSA approach includes the possibility of being coupled with the construction of a reduced complexity model that allows approximating the full model response at a reduced computational cost. We demonstrate our approach through a variety of test cases. These include a commonly used analytical benchmark, a simplified model representing pumping in a coastal aquifer, a laboratory-scale tracer experiment, and the migration of fracturing fluid through a naturally fractured reservoir (source) to reach an overlying formation (target). Our strategy allows discriminating the relative importance of model parameters to the four statistical moments considered. We also provide an appraisal of the error associated with the evaluation of our sensitivity metrics by replacing the original system model through the selected surrogate model. Our results suggest that one might need to construct a surrogate model with increasing level of accuracy depending on the statistical moment considered in the GSA. The methodological framework we propose can assist the development of analysis techniques targeted to model calibration, design of experiment, uncertainty quantification and risk assessment.

Survival analysis in hematologic malignancies: recommendations for clinicians

PubMed Central

Delgado, Julio; Pereira, Arturo; Villamor, Neus; López-Guillermo, Armando; Rozman, Ciril

2014-01-01

The widespread availability of statistical packages has undoubtedly helped hematologists worldwide in the analysis of their data, but has also led to the inappropriate use of statistical methods. In this article, we review some basic concepts of survival analysis and also make recommendations about how and when to perform each particular test using SPSS, Stata and R. In particular, we describe a simple way of defining cut-off points for continuous variables and the appropriate and inappropriate uses of the Kaplan-Meier method and Cox proportional hazard regression models. We also provide practical advice on how to check the proportional hazards assumption and briefly review the role of relative survival and multiple imputation. PMID:25176982

False-positive results in pharmacoepidemiology and pharmacovigilance.

PubMed

Bezin, Julien; Bosco-Levy, Pauline; Pariente, Antoine

2017-09-01

False-positive constitute an important issue in scientific research. In the domain of drug evaluation, it affects all phases of drug development and assessment, from the very early preclinical studies to the late post-marketing evaluations. The core concern associated with this false-positive is the lack of replicability of the results. Aside from fraud or misconducts, false-positive is often envisioned from the statistical angle, which considers them as a price to pay for type I error in statistical testing, and its inflation in the context of multiple testing. If envisioning this problematic in the context of pharmacoepidemiology and pharmacovigilance however, that both evaluate drugs in an observational settings, information brought by statistical testing and the significance of such should only be considered as additional to the estimates provided and their confidence interval, in a context where differences have to be a clinically meaningful upon everything, and the results appear robust to the biases likely to have affected the studies. In the following article, we consequently illustrate these biases and their consequences in generating false-positive results, through studies and associations between drug use and health outcomes that have been widely disputed. Copyright © 2017 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.

Threat detection of liquid explosives and precursors from their x-ray scattering pattern using energy dispersive detector technology

NASA Astrophysics Data System (ADS)

Kehres, Jan; Lyksborg, Mark; Olsen, Ulrik L.

2017-09-01

Energy dispersive X-ray diffraction (EDXRD) can be applied for identification of liquid threats in luggage scanning in security applications. To define the instrumental design, the framework for data reduction and analysis and test the performance of the threat detection in various scenarios, a flexible laboratory EDXRD test setup was build. A data set of overall 570 EDXRD spectra has been acquired for training and testing of threat identification algorithms. The EDXRD data was acquired with limited count statistics and at multiple detector angles and merged after correction and normalization. Initial testing of the threat detection algorithms with this data set indicate the feasibility of detection levels of > 95 % true positive with < 6 % false positive alarms.

Statistical Stationarity of Sediment Interbed Thicknesses in a Basalt Aquifer, Idaho National Laboratory, Eastern Snake River Plain, Idaho

USGS Publications Warehouse

Stroup, Caleb N.; Welhan, John A.; Davis, Linda C.

2008-01-01

The statistical stationarity of distributions of sedimentary interbed thicknesses within the southwestern part of the Idaho National Laboratory (INL) was evaluated within the stratigraphic framework of Quaternary sediments and basalts at the INL site, eastern Snake River Plain, Idaho. The thicknesses of 122 sedimentary interbeds observed in 11 coreholes were documented from lithologic logs and independently inferred from natural-gamma logs. Lithologic information was grouped into composite time-stratigraphic units based on correlations with existing composite-unit stratigraphy near these holes. The assignment of lithologic units to an existing chronostratigraphy on the basis of nearby composite stratigraphic units may introduce error where correlations with nearby holes are ambiguous or the distance between holes is great, but we consider this the best technique for grouping stratigraphic information in this geologic environment at this time. Nonparametric tests of similarity were used to evaluate temporal and spatial stationarity in the distributions of sediment thickness. The following statistical tests were applied to the data: (1) the Kolmogorov-Smirnov (K-S) two-sample test to compare distribution shape, (2) the Mann-Whitney (M-W) test for similarity of two medians, (3) the Kruskal-Wallis (K-W) test for similarity of multiple medians, and (4) Levene's (L) test for the similarity of two variances. Results of these analyses corroborate previous work that concluded the thickness distributions of Quaternary sedimentary interbeds are locally stationary in space and time. The data set used in this study was relatively small, so the results presented should be considered preliminary, pending incorporation of data from more coreholes. Statistical tests also demonstrated that natural-gamma logs consistently fail to detect interbeds less than about 2-3 ft thick, although these interbeds are observable in lithologic logs. This should be taken into consideration when modeling aquifer lithology or hydraulic properties based on lithology.

[Normalisation and validation of the Brief Neuropsychological Battery as the reference neuropsychological test in multiple sclerosis].

PubMed

Duque, P; Ibanez, J; Del Barco, A; Sepulcre, J; de Ramon, E; Fernandez-Fernandez, O

2012-03-01

INTRODUCTION. The current batteries such as the Brief Repeatable Battery of Neuropsychological Tests (BRB-N) for evaluating cognitive decline in patients with multiple sclerosis are complex and time-consuming. AIM. To obtain normative values and validate a new battery. SUBJECTS AND METHODS. Four neuropsychological tests were finally included (episodic memory, the Symbol-Digit Modalities Test, a category fluency test, and the Paced Auditory Serial Addition Test). Normative values (overall and by age group) were derived by administering the battery to healthy subjects (5th percentile was the limit of normal). External validity was explored by comparison with the BRB-N. The new battery was also administered to a subsample after 4 weeks to assess reproducibility. RESULTS. To provide normative data, 1036 healthy subjects were recruited. The mean completion time was 18.5 ± 5.2 minutes. For the 229 subjects who were administered the new battery and the BRB-N, no statistically significant differences were found except for mean completion time (19 ± 4 vs 25 ± 5 minutes). In the reproducibility study, there were no significant differences except in the memory tests. CONCLUSION. The scores on the new battery and the BRB-N were strongly correlated although the shorter completion time and ease of administration could make the new battery preferable in clinical practice.

Graphical method for comparative statistical study of vaccine potency tests.

PubMed

Pay, T W; Hingley, P J

1984-03-01

Producers and consumers are interested in some of the intrinsic characteristics of vaccine potency assays for the comparative evaluation of suitable experimental design. A graphical method is developed which represents the precision of test results, the sensitivity of such results to changes in dosage, and the relevance of the results in the way they reflect the protection afforded in the host species. The graphs can be constructed from Producer's scores and Consumer's scores on each of the scales of test score, antigen dose and probability of protection against disease. A method for calculating these scores is suggested and illustrated for single and multiple component vaccines, for tests which do or do not employ a standard reference preparation, and for tests which employ quantitative or quantal systems of scoring.

Single aortic clamping in coronary artery bypass surgery reduces cerebral embolism and improves neurocognitive outcomes.

PubMed

Gasparovic, Hrvoje; Borojevic, Marko; Malojcic, Branko; Gasparovic, Kristina; Biocina, Bojan

2013-10-01

Aortic manipulation releases embolic material, thereby enhancing the probability of adverse neurologic outcomes following coronary artery bypass grafting (CABG). We prospectively evaluated 59 patients undergoing CABG. Patients in the single (SC, n = 37) and multiple clamp (MC, n = 22) groups were comparable in relation to age and operative risk (p > 0.05). Neurocognitive evaluation consisted of the Auditory Verbal Learning Test (AVLT), Color Trails Test A, the Grooved Pegboard test and the Mini-Mental State Examination. Data acquisition was performed preoperatively, early postoperatively and at the 4-month follow-up. Intraoperative transcranial Doppler (TCD) monitoring was used to quantify the embolic load in relation to different aortic clamping strategies. Preoperative neurocognitive results were similar between the groups (p > 0.05). The incidence of postoperative delirium was greater in the MC group but this failed to reach statistical significance (23% vs 8%, p = 0.14). SC patients had fewer embolization signals (270 ± 181 vs 465 ± 160, p < 0.0001). Early postoperative neurocognitive results were depressed in comparison to preoperative values in both groups (p < 0.05 for multiple comparisons). The magnitude of this cognitive depression was greater in the MC group (p < 0.05 for multiple comparisons). Preoperative levels of neurocognition were restored at follow-up in the SC group in all tests except the AVLT. A trend towards improvements in neurocognitive performances at follow-up was also observed in the MC group. Residual attention, motor skill and memory deficits were, however, documented with multiple tests. In conclusion, the embolic burden was significantly lower in the SC group. This TCD imaging outcome translated into fewer early cognition deficits and superior late restoration of function.

Clinical Pharmacology Quality Assurance (CPQA) Program: Models for Longitudinal Analysis of Antiretroviral (ARV) Proficiency Testing for International Laboratories

PubMed Central

DiFrancesco, Robin; Rosenkranz, Susan L.; Taylor, Charlene R.; Pande, Poonam G.; Siminski, Suzanne M.; Jenny, Richard W.; Morse, Gene D.

2013-01-01

Among National Institutes of Health (NIH) HIV Research Networks conducting multicenter trials, samples from protocols that span several years are analyzed at multiple clinical pharmacology laboratories (CPLs) for multiple antiretrovirals (ARV). Drug assay data are, in turn, entered into study-specific datasets that are used for pharmacokinetic analyses, merged to conduct cross-protocol pharmacokinetic analysis and integrated with pharmacogenomics research to investigate pharmacokinetic-pharmacogenetic associations. The CPLs participate in a semi-annual proficiency testing (PT) program implemented by the Clinical Pharmacology Quality Assurance (CPQA) program. Using results from multiple PT rounds, longitudinal analyses of recovery are reflective of accuracy and precision within/across laboratories. The objectives of this longitudinal analysis of PT across multiple CPLs were to develop and test statistical models that longitudinally: (1)assess the precision and accuracy of concentrations reported by individual CPLs; (2)determine factors associated with round-specific and long-term assay accuracy, precision and bias using a new regression model. A measure of absolute recovery is explored as a simultaneous measure of accuracy and precision. Overall, the analysis outcomes assured 97% accuracy (±20% of the final target concentration of all (21)drug concentration results reported for clinical trial samples by multiple CPLs).Using the CLIA acceptance of meeting criteria for ≥2/3 consecutive rounds, all ten laboratories that participated in three or more rounds per analyte maintained CLIA proficiency. Significant associations were present between magnitude of error and CPL (Kruskal Wallis [KW]p<0.001), and ARV (KW p<0.001). PMID:24052065

Clinical pharmacology quality assurance program: models for longitudinal analysis of antiretroviral proficiency testing for international laboratories.

PubMed

DiFrancesco, Robin; Rosenkranz, Susan L; Taylor, Charlene R; Pande, Poonam G; Siminski, Suzanne M; Jenny, Richard W; Morse, Gene D

2013-10-01

Among National Institutes of Health HIV Research Networks conducting multicenter trials, samples from protocols that span several years are analyzed at multiple clinical pharmacology laboratories (CPLs) for multiple antiretrovirals. Drug assay data are, in turn, entered into study-specific data sets that are used for pharmacokinetic analyses, merged to conduct cross-protocol pharmacokinetic analysis, and integrated with pharmacogenomics research to investigate pharmacokinetic-pharmacogenetic associations. The CPLs participate in a semiannual proficiency testing (PT) program implemented by the Clinical Pharmacology Quality Assurance program. Using results from multiple PT rounds, longitudinal analyses of recovery are reflective of accuracy and precision within/across laboratories. The objectives of this longitudinal analysis of PT across multiple CPLs were to develop and test statistical models that longitudinally: (1) assess the precision and accuracy of concentrations reported by individual CPLs and (2) determine factors associated with round-specific and long-term assay accuracy, precision, and bias using a new regression model. A measure of absolute recovery is explored as a simultaneous measure of accuracy and precision. Overall, the analysis outcomes assured 97% accuracy (±20% of the final target concentration of all (21) drug concentration results reported for clinical trial samples by multiple CPLs). Using the Clinical Laboratory Improvement Act acceptance of meeting criteria for ≥2/3 consecutive rounds, all 10 laboratories that participated in 3 or more rounds per analyte maintained Clinical Laboratory Improvement Act proficiency. Significant associations were present between magnitude of error and CPL (Kruskal-Wallis P < 0.001) and antiretroviral (Kruskal-Wallis P < 0.001).

Interlaboratory comparability, bias, and precision for four laboratories measuring constituents in precipitation, November 1982-August 1983

USGS Publications Warehouse

Brooks, M.H.; Schroder, L.J.; Malo, B.A.

1985-01-01

Four laboratories were evaluated in their analysis of identical natural and simulated precipitation water samples. Interlaboratory comparability was evaluated using analysis of variance coupled with Duncan 's multiple range test, and linear-regression models describing the relations between individual laboratory analytical results for natural precipitation samples. Results of the statistical analyses indicate that certain pairs of laboratories produce different results when analyzing identical samples. Analyte bias for each laboratory was examined using analysis of variance coupled with Duncan 's multiple range test on data produced by the laboratories from the analysis of identical simulated precipitation samples. Bias for a given analyte produced by a single laboratory has been indicated when the laboratory mean for that analyte is shown to be significantly different from the mean for the most-probable analyte concentrations in the simulated precipitation samples. Ion-chromatographic methods for the determination of chloride, nitrate, and sulfate have been compared with the colorimetric methods that were also in use during the study period. Comparisons were made using analysis of variance coupled with Duncan 's multiple range test for means produced by the two methods. Analyte precision for each laboratory has been estimated by calculating a pooled variance for each analyte. Analyte estimated precisions have been compared using F-tests and differences in analyte precisions for laboratory pairs have been reported. (USGS)

Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies

PubMed Central

Liu, Xiaolei; Huang, Meng; Fan, Bin; Buckler, Edward S.; Zhang, Zhiwu

2016-01-01

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises true positives. The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. To completely eliminate the confounding, we divided MLMM into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM) and use them iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting problem in FEM, the associated markers are estimated in REM by using them to define kinship. The P values of testing markers and the associated markers are unified at each iteration. We named the new method as Fixed and random model Circulating Probability Unification (FarmCPU). Both real and simulated data analyses demonstrated that FarmCPU improves statistical power compared to current methods. Additional benefits include an efficient computing time that is linear to both number of individuals and number of markers. Now, a dataset with half million individuals and half million markers can be analyzed within three days. PMID:26828793

Environmental Health Practice: Statistically Based Performance Measurement

PubMed Central

Enander, Richard T.; Gagnon, Ronald N.; Hanumara, R. Choudary; Park, Eugene; Armstrong, Thomas; Gute, David M.

2007-01-01

Objectives. State environmental and health protection agencies have traditionally relied on a facility-by-facility inspection-enforcement paradigm to achieve compliance with government regulations. We evaluated the effectiveness of a new approach that uses a self-certification random sampling design. Methods. Comprehensive environmental and occupational health data from a 3-year statewide industry self-certification initiative were collected from representative automotive refinishing facilities located in Rhode Island. Statistical comparisons between baseline and postintervention data facilitated a quantitative evaluation of statewide performance. Results. The analysis of field data collected from 82 randomly selected automotive refinishing facilities showed statistically significant improvements (P<.05, Fisher exact test) in 4 major performance categories: occupational health and safety, air pollution control, hazardous waste management, and wastewater discharge. Statistical significance was also shown when a modified Bonferroni adjustment for multiple comparisons was performed. Conclusions. Our findings suggest that the new self-certification approach to environmental and worker protection is effective and can be used as an adjunct to further enhance state and federal enforcement programs. PMID:17267709

Which form of assessment provides the best information about student performance in chemistry examinations?

NASA Astrophysics Data System (ADS)

Hudson, Ross D.; Treagust, David F.

2013-04-01

Background . This study developed from observations of apparent achievement differences between male and female chemistry performances in a state university entrance examination. Male students performed more strongly than female students, especially in higher scores. Apart from the gender of the students, two other important factors that might influence student performance were format of questions (short-answer or multiple-choice) and type of questions (recall or application). Purpose The research question addressed in this study was: Is there a relationship between performance in state university entrance examinations in chemistry and school chemistry examinations and student gender, format of questions - multiple-choice or short-answer, and conceptual level - recall or application? Sample The two sources of data were: (1) secondary analyses of five consecutive years' data published by the examining authority of chemistry examinations, and (2) tests conducted with 192 students which provided information about all aspects of the three variables (question format, question type and gender) under consideration. Design and methods Both sources of data were analysed using ANOVA to compare means for the variables under consideration and the statistical significance of any differences. The data from the tests were also analysed using Rasch analysis to determine differences in gender performance. Results When overall mean data are considered, both male and female students performed better on multiple-choice questions and recall questions than on short-answer questions and application questions, respectively. When overall mean data are considered, male students outperformed female students in both the university entrance and school tests, particularly in the higher scores. When data were analysed with Rasch, there was no statistically significant difference in performance between males and females of equal ability. Conclusions Both male and female students generally perform better on multiple-choice questions than they do on short-answer questions. However, when the questions are matched in terms of difficulty (using Rasch analysis), the differences in performance between multiple-choice and short-answer are quite small. Rasch analysis showed that there was little difference in performance between males and females of equal ability. This study shows that a simple face-value score analysis of relative student performance - in this case, in chemistry - can be deceptive unless the actual abilities of the students concerned, as measured by a tool such as Rasch, are taken into consideration before reaching any conclusion.

Stability of Spinal Bone Lesions in Patients With Multiple Myeloma After Radiotherapy-A Retrospective Analysis of 130 Cases.

PubMed

Lang, Kristin; König, Laila; Bruckner, Thomas; Förster, Robert; Sprave, Tanja; Schlampp, Ingmar; Bostel, Tilman; Welte, Stefan; Nicolay, Nils H; Debus, Jürgen; Rief, Harald

2017-12-01

The objective of the present retrospective analysis was the response evaluation regarding bone density and stability of patients with osteolytic spinal bone lesions due to multiple myeloma after palliative radiotherapy (RT). Patients with multiple myeloma who had undergone spinal RT from March 2003 to May 2016 were analyzed before and 3 and 6 months after RT. Assessment of spinal stability and bone density was performed using the internationally recognized Taneichi scoring system and measurement of bone density using computed tomography imaging-based Hounsfield units. For statistical analysis, we used the Bowker test, McNemar test, and κ statistics to detect possible asymmetries in the distribution of the Taneichi score over time. We used the Student t test for comparison of the density values (Hounsfield units) before and after treatment. Toxicity was evaluated using the Common Terminology Criteria for Adverse Events, version 4.0. Additionally, overall survival was calculated using the Kaplan-Meier method. We evaluated 130 patients (69% male; 31% female) with multiple myeloma and a median age of 58 years. The median follow-up period was 41 months. Before treatment, 51% of the lesions were classified as unstable. At 3 and 6 months after RT, this rate had decreased to 41% (P = .0047) and 24% (P = .2393), respectively. The computed tomography measurements showed a significant increase in bone density at 3 and 6 months after RT. Acute RT-related grade 1 and 2 complications were detected in 34% of patients. Late side effects (grade 1-2) were detected in 23% of the patients. No severe grade 3 or 4 acute or late toxicities were identified. The median overall survival was 19.7 months for all patients and 6.6 months for patients with a Karnofsky performance score of ≤ 70%. To the best of our knowledge, ours is the first report to analyze the bone density and stability in patients with multiple myeloma after RT using a validated scoring system and computed tomography imaging. Palliative RT is an effective method resulting in a significant increase in bone density for local response and stability without severe RT-related toxicity. Furthermore, recalcification could already be detected at 3 months after treatment. Copyright © 2017 Elsevier Inc. All rights reserved.

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies

PubMed Central

Zhang, Shujun

2018-01-01

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study. PMID:29377896

The capacity limitations of orientation summary statistics

PubMed Central

Attarha, Mouna; Moore, Cathleen M.

2015-01-01

The simultaneous–sequential method was used to test the processing capacity of establishing mean orientation summaries. Four clusters of oriented Gabor patches were presented in the peripheral visual field. One of the clusters had a mean orientation that was tilted either left or right while the mean orientations of the other three clusters were roughly vertical. All four clusters were presented at the same time in the simultaneous condition whereas the clusters appeared in temporal subsets of two in the sequential condition. Performance was lower when the means of all four clusters had to be processed concurrently than when only two had to be processed in the same amount of time. The advantage for establishing fewer summaries at a given time indicates that the processing of mean orientation engages limited-capacity processes (Experiment 1). This limitation cannot be attributed to crowding, low target-distractor discriminability, or a limited-capacity comparison process (Experiments 2 and 3). In contrast to the limitations of establishing multiple summary representations, establishing a single summary representation unfolds without interference (Experiment 4). When interpreted in the context of recent work on the capacity of summary statistics, these findings encourage reevaluation of the view that early visual perception consists of summary statistic representations that unfold independently across multiple areas of the visual field. PMID:25810160

Neural Correlates of Morphology Acquisition through a Statistical Learning Paradigm.

PubMed

Sandoval, Michelle; Patterson, Dianne; Dai, Huanping; Vance, Christopher J; Plante, Elena

2017-01-01

The neural basis of statistical learning as it occurs over time was explored with stimuli drawn from a natural language (Russian nouns). The input reflected the "rules" for marking categories of gendered nouns, without making participants explicitly aware of the nature of what they were to learn. Participants were scanned while listening to a series of gender-marked nouns during four sequential scans, and were tested for their learning immediately after each scan. Although participants were not told the nature of the learning task, they exhibited learning after their initial exposure to the stimuli. Independent component analysis of the brain data revealed five task-related sub-networks. Unlike prior statistical learning studies of word segmentation, this morphological learning task robustly activated the inferior frontal gyrus during the learning period. This region was represented in multiple independent components, suggesting it functions as a network hub for this type of learning. Moreover, the results suggest that subnetworks activated by statistical learning are driven by the nature of the input, rather than reflecting a general statistical learning system.

Neural Correlates of Morphology Acquisition through a Statistical Learning Paradigm

PubMed Central

Sandoval, Michelle; Patterson, Dianne; Dai, Huanping; Vance, Christopher J.; Plante, Elena

2017-01-01

The neural basis of statistical learning as it occurs over time was explored with stimuli drawn from a natural language (Russian nouns). The input reflected the “rules” for marking categories of gendered nouns, without making participants explicitly aware of the nature of what they were to learn. Participants were scanned while listening to a series of gender-marked nouns during four sequential scans, and were tested for their learning immediately after each scan. Although participants were not told the nature of the learning task, they exhibited learning after their initial exposure to the stimuli. Independent component analysis of the brain data revealed five task-related sub-networks. Unlike prior statistical learning studies of word segmentation, this morphological learning task robustly activated the inferior frontal gyrus during the learning period. This region was represented in multiple independent components, suggesting it functions as a network hub for this type of learning. Moreover, the results suggest that subnetworks activated by statistical learning are driven by the nature of the input, rather than reflecting a general statistical learning system. PMID:28798703

Statistical and Machine Learning forecasting methods: Concerns and ways forward

PubMed Central

Makridakis, Spyros; Assimakopoulos, Vassilios

2018-01-01

Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions. PMID:29584784

Multiple commodities in statistical microeconomics: Model and market

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.; Yu, Miao; Du, Xin

2016-11-01

A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

A Study of relationship between frailty and physical performance in elderly women.

PubMed

Jeoung, Bog Ja; Lee, Yang Chool

2015-08-01

Frailty is a disorder of multiple inter-related physiological systems. It is unclear whether the level of physical performance factors can serve as markers of frailty and a sign. The purpose of this study was to examine the relationship between frailty and physical performance in elderly women. One hundred fourteen elderly women participated in this study, their aged was from 65 to 80. We were measured 6-min walk test, grip-strength, 30-sec arm curl test, 30-sec chair stand test, 8 foot Up- and Go, Back scratch, chair sit and reach, unipedal stance, BMI, and the frailty with questionnaire. The collected data were analyzed by descriptive statistics, frequencies, correlation analysis, ANOVA, and simple liner regression using the IBM 21. SPSS program. In results, statistic tests showed that there were significant differences between frailty and 6-min walk test, 30-sec arm curl test, 30-sec chair stand test, grip-strength, Back scratch, and BMI. However, we did not find significant differences between frailty and 8 foot Up- and Go, unipedal stance. When the subjects were divided into five groups according to physical performance level, subjects with high 6-min walk, 30-sec arm curl test, chair sit and reach test, and high grip strength had low score frailty. Physical performance factors were strongly associated with decreased frailty, suggesting that physical performance improvements play an important role in preventing or reducing the frailty.

New methods of testing nonlinear hypothesis using iterative NLLS estimator

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper discusses the method of testing nonlinear hypothesis using iterative Nonlinear Least Squares (NLLS) estimator. Takeshi Amemiya [1] explained this method. However in the present research paper, a modified Wald test statistic due to Engle, Robert [6] is proposed to test the nonlinear hypothesis using iterative NLLS estimator. An alternative method for testing nonlinear hypothesis using iterative NLLS estimator based on nonlinear hypothesis using iterative NLLS estimator based on nonlinear studentized residuals has been proposed. In this research article an innovative method of testing nonlinear hypothesis using iterative restricted NLLS estimator is derived. Pesaran and Deaton [10] explained the methods of testing nonlinear hypothesis. This paper uses asymptotic properties of nonlinear least squares estimator proposed by Jenrich [8]. The main purpose of this paper is to provide very innovative methods of testing nonlinear hypothesis using iterative NLLS estimator, iterative NLLS estimator based on nonlinear studentized residuals and iterative restricted NLLS estimator. Eakambaram et al. [12] discussed least absolute deviation estimations versus nonlinear regression model with heteroscedastic errors and also they studied the problem of heteroscedasticity with reference to nonlinear regression models with suitable illustration. William Grene [13] examined the interaction effect in nonlinear models disused by Ai and Norton [14] and suggested ways to examine the effects that do not involve statistical testing. Peter [15] provided guidelines for identifying composite hypothesis and addressing the probability of false rejection for multiple hypotheses.

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence.

PubMed

Liu, Gang; Mukherjee, Bhramar; Lee, Seunggeun; Lee, Alice W; Wu, Anna H; Bandera, Elisa V; Jensen, Allan; Rossing, Mary Anne; Moysich, Kirsten B; Chang-Claude, Jenny; Doherty, Jennifer A; Gentry-Maharaj, Aleksandra; Kiemeney, Lambertus; Gayther, Simon A; Modugno, Francesmary; Massuger, Leon; Goode, Ellen L; Fridley, Brooke L; Terry, Kathryn L; Cramer, Daniel W; Ramus, Susan J; Anton-Culver, Hoda; Ziogas, Argyrios; Tyrer, Jonathan P; Schildkraut, Joellen M; Kjaer, Susanne K; Webb, Penelope M; Ness, Roberta B; Menon, Usha; Berchuck, Andrew; Pharoah, Paul D; Risch, Harvey; Pearce, Celeste Leigh

2018-02-01

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Combined statistical analyses for long-term stability data with multiple storage conditions: a simulation study.

PubMed

Almalik, Osama; Nijhuis, Michiel B; van den Heuvel, Edwin R

2014-01-01

Shelf-life estimation usually requires that at least three registration batches are tested for stability at multiple storage conditions. The shelf-life estimates are often obtained by linear regression analysis per storage condition, an approach implicitly suggested by ICH guideline Q1E. A linear regression analysis combining all data from multiple storage conditions was recently proposed in the literature when variances are homogeneous across storage conditions. The combined analysis is expected to perform better than the separate analysis per storage condition, since pooling data would lead to an improved estimate of the variation and higher numbers of degrees of freedom, but this is not evident for shelf-life estimation. Indeed, the two approaches treat the observed initial batch results, the intercepts in the model, and poolability of batches differently, which may eliminate or reduce the expected advantage of the combined approach with respect to the separate approach. Therefore, a simulation study was performed to compare the distribution of simulated shelf-life estimates on several characteristics between the two approaches and to quantify the difference in shelf-life estimates. In general, the combined statistical analysis does estimate the true shelf life more consistently and precisely than the analysis per storage condition, but it did not outperform the separate analysis in all circumstances.

Validation of the MCNP6 electron-photon transport algorithm: multiple-scattering of 13- and 20-MeV electrons in thin foils

NASA Astrophysics Data System (ADS)

Dixon, David A.; Hughes, H. Grady

2017-09-01

This paper presents a validation test comparing angular distributions from an electron multiple-scattering experiment with those generated using the MCNP6 Monte Carlo code system. In this experiment, a 13- and 20-MeV electron pencil beam is deflected by thin foils with atomic numbers from 4 to 79. To determine the angular distribution, the fluence is measured down range of the scattering foil at various radii orthogonal to the beam line. The characteristic angle (the angle for which the max of the distribution is reduced by 1/e) is then determined from the angular distribution and compared with experiment. Multiple scattering foils tested herein include beryllium, carbon, aluminum, copper, and gold. For the default electron-photon transport settings, the calculated characteristic angle was statistically distinguishable from measurement and generally broader than the measured distributions. The average relative difference ranged from 5.8% to 12.2% over all of the foils, source energies, and physics settings tested. This validation illuminated a deficiency in the computation of the underlying angular distributions that is well understood. As a result, code enhancements were made to stabilize the angular distributions in the presence of very small substeps. However, the enhancement only marginally improved results indicating that additional algorithmic details should be studied.

kruX: matrix-based non-parametric eQTL discovery.

PubMed

Qi, Jianlong; Asl, Hassan Foroughi; Björkegren, Johan; Michoel, Tom

2014-01-14

The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com.

Experimental design matters for statistical analysis: how to handle blocking.

PubMed

Jensen, Signe M; Schaarschmidt, Frank; Onofri, Andrea; Ritz, Christian

2018-03-01

Nowadays, evaluation of the effects of pesticides often relies on experimental designs that involve multiple concentrations of the pesticide of interest or multiple pesticides at specific comparable concentrations and, possibly, secondary factors of interest. Unfortunately, the experimental design is often more or less neglected when analysing data. Two data examples were analysed using different modelling strategies. First, in a randomized complete block design, mean heights of maize treated with a herbicide and one of several adjuvants were compared. Second, translocation of an insecticide applied to maize as a seed treatment was evaluated using incomplete data from an unbalanced design with several layers of hierarchical sampling. Extensive simulations were carried out to further substantiate the effects of different modelling strategies. It was shown that results from suboptimal approaches (two-sample t-tests and ordinary ANOVA assuming independent observations) may be both quantitatively and qualitatively different from the results obtained using an appropriate linear mixed model. The simulations demonstrated that the different approaches may lead to differences in coverage percentages of confidence intervals and type 1 error rates, confirming that misleading conclusions can easily happen when an inappropriate statistical approach is chosen. To ensure that experimental data are summarized appropriately, avoiding misleading conclusions, the experimental design should duly be reflected in the choice of statistical approaches and models. We recommend that author guidelines should explicitly point out that authors need to indicate how the statistical analysis reflects the experimental design. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

How easily can omission of patients, or selection amongst poorly-reproducible measurements, create artificial correlations? Methods for detection and implications for observational research design in cardiology.

PubMed

Francis, Darrel P

2013-07-15

When reported correlation coefficients seem too high to be true, does investigative verification of source data provide suitable reassurance? This study tests how easily omission of patients or selection amongst irreproducible measurements generate fictitious strong correlations, without data fabrication. Two forms of manipulation are applied to a pair of normally-distributed, uncorrelated variables: first, exclusion of patients least favourable to a hypothesised association and, second, making multiple poorly-reproducible measurements per patient and choosing the most supportive. Excluding patients raises correlations powerfully, from 0.0 ± 0.11 (no patients omitted) to 0.40 ± 0.11 (one-fifth omitted), 0.59 ± 0.08 (one-third omitted) and 0.78 ± 0.05 (half omitted). Study size offers no protection: omitting just one-fifth of 75 patients (i.e. publishing 60) makes 92% of correlations statistically significant. Worse, simply selecting the most favourable amongst several measurements raises correlations from 0.0 ± 0.12 (single measurement of each variable) to 0.73 ± 0.06 (best of 2), and 0.90 ± 0.03 (best of 4). 100% of correlation coefficients become statistically significant. Scatterplots may reveal a telltale "shave sign" or "bite sign". Simple statistical tests are presented for these suspicious signatures in single or multiple studies. Correlations are vulnerable to data manipulation. Cardiology is especially vulnerable to patient deletion (because cardiologists ourselves might completely control enrolment and measurement), and selection of "best" measurements (because alternative heartbeats are numerous, and some modalities poorly reproducible). Source data verification cannot detect these but tests might highlight suspicious data and--aggregating across studies--unreliable laboratories or research fields. Cardiological correlation research needs adequately-informed planning and guarantees of integrity, with teeth. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Changes in sexual behaviour and practice and HIV prevalence indicators among young people aged 15–24 years in Zambia: An in-depth analysis of the 2001–2002 and 2007 Zambia Demographic and Health Surveys

PubMed Central

Kembo, Joshua

2014-01-01

HIV and AIDS still pose a major public health problem to most countries in sub-Saharan Africa, Zambia included. The objective of the paper is to determine changes in selected sexual behaviour and practice and HIV prevalence indicators between 2001–2002 and 2007. We used the Demographic and Health Survey Indicators Database for the computation of the selected indicators. We further used STATA 10.0 to compute significance tests to test for statistical difference in the indicators. The results indicate some changes in sexual behaviour, as indicated by an increase in abstinence, use of condoms and the decrease in multiple partnerships. The overall percentage of abstinence among never-married young men and women aged 15–24 years in Zambia increased significantly by 15.2% (p = .000) and 5.9% (p = .001) respectively, between 2001–2002 and 2007. A statistically significant increase of 6.6% (p = .029) was observed in the percentage of young women who reported having used a condom during the last time they had had premarital sex. A statistically significant decrease of 11.0% (p = .000) and 1.4% (p = .000) was observed among young men and women, respectively, who reported having multiple partners in the preceding 12 months. The factorial decomposition using multivariate analysis reveals that the indicators which contributed to the statistically significant 2.6% decline in HIV prevalence among young women aged 15–24 years in Zambia include proportion reporting condom use during premarital sex (+6.6%), abstinence (+5.9%), sex before age 15 (– 4.5%), premarital sex (– 2.6%), sex before age 18 (– 2.4%) and proportion reporting multiple partnerships (– 1.4%). Remarkable strides have been achieved towards promoting responsible sexual behaviour and practice among young people in Zambia. Further research focusing on factors that predispose young women in Zambia to higher risk of infection from HIV is required. The results from this paper should be useful in the design of programmes to control the spread of HIV and AIDS, particularly among young people in Zambia and other sub-Saharan countries. PMID:24702245

Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies.

PubMed

Nettleton, Jennifer A; McKeown, Nicola M; Kanoni, Stavroula; Lemaitre, Rozenn N; Hivert, Marie-France; Ngwa, Julius; van Rooij, Frank J A; Sonestedt, Emily; Wojczynski, Mary K; Ye, Zheng; Tanaka, Tosh; Garcia, Melissa; Anderson, Jennifer S; Follis, Jack L; Djousse, Luc; Mukamal, Kenneth; Papoutsakis, Constantina; Mozaffarian, Dariush; Zillikens, M Carola; Bandinelli, Stefania; Bennett, Amanda J; Borecki, Ingrid B; Feitosa, Mary F; Ferrucci, Luigi; Forouhi, Nita G; Groves, Christopher J; Hallmans, Goran; Harris, Tamara; Hofman, Albert; Houston, Denise K; Hu, Frank B; Johansson, Ingegerd; Kritchevsky, Stephen B; Langenberg, Claudia; Launer, Lenore; Liu, Yongmei; Loos, Ruth J; Nalls, Michael; Orho-Melander, Marju; Renstrom, Frida; Rice, Kenneth; Riserus, Ulf; Rolandsson, Olov; Rotter, Jerome I; Saylor, Georgia; Sijbrands, Eric J G; Sjogren, Per; Smith, Albert; Steingrímsdóttir, Laufey; Uitterlinden, André G; Wareham, Nicholas J; Prokopenko, Inga; Pankow, James S; van Duijn, Cornelia M; Florez, Jose C; Witteman, Jacqueline C M; Dupuis, Josée; Dedoussis, George V; Ordovas, Jose M; Ingelsson, Erik; Cupples, L Adrienne; Siscovick, David S; Franks, Paul W; Meigs, James B

2010-12-01

Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin. Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant. Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele. Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

Seismic activity prediction using computational intelligence techniques in northern Pakistan

NASA Astrophysics Data System (ADS)

Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

2017-10-01

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

A Wave Chaotic Study of Quantum Graphs with Microwave Networks

NASA Astrophysics Data System (ADS)

Fu, Ziyuan

Quantum graphs provide a setting to test the hypothesis that all ray-chaotic systems show universal wave chaotic properties. I study the quantum graphs with a wave chaotic approach. Here, an experimental setup consisting of a microwave coaxial cable network is used to simulate quantum graphs. Some basic features and the distributions of impedance statistics are analyzed from experimental data on an ensemble of tetrahedral networks. The random coupling model (RCM) is applied in an attempt to uncover the universal statistical properties of the system. Deviations from RCM predictions have been observed in that the statistics of diagonal and off-diagonal impedance elements are different. Waves trapped due to multiple reflections on bonds between nodes in the graph most likely cause the deviations from universal behavior in the finite-size realization of a quantum graph. In addition, I have done some investigations on the Random Coupling Model, which are useful for further research.

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

PubMed

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Psychology, Science, and Knowledge Construction: Broadening Perspectives from the Replication Crisis.

PubMed

Shrout, Patrick E; Rodgers, Joseph L

2018-01-04

Psychology advances knowledge by testing statistical hypotheses using empirical observations and data. The expectation is that most statistically significant findings can be replicated in new data and in new laboratories, but in practice many findings have replicated less often than expected, leading to claims of a replication crisis. We review recent methodological literature on questionable research practices, meta-analysis, and power analysis to explain the apparently high rates of failure to replicate. Psychologists can improve research practices to advance knowledge in ways that improve replicability. We recommend that researchers adopt open science conventions of preregi-stration and full disclosure and that replication efforts be based on multiple studies rather than on a single replication attempt. We call for more sophisticated power analyses, careful consideration of the various influences on effect sizes, and more complete disclosure of nonsignificant as well as statistically significant findings.

Optimal allocation of testing resources for statistical simulations

NASA Astrophysics Data System (ADS)

Quintana, Carolina; Millwater, Harry R.; Singh, Gulshan; Golden, Patrick

2015-07-01

Statistical estimates from simulation involve uncertainty caused by the variability in the input random variables due to limited data. Allocating resources to obtain more experimental data of the input variables to better characterize their probability distributions can reduce the variance of statistical estimates. The methodology proposed determines the optimal number of additional experiments required to minimize the variance of the output moments given single or multiple constraints. The method uses multivariate t-distribution and Wishart distribution to generate realizations of the population mean and covariance of the input variables, respectively, given an amount of available data. This method handles independent and correlated random variables. A particle swarm method is used for the optimization. The optimal number of additional experiments per variable depends on the number and variance of the initial data, the influence of the variable in the output function and the cost of each additional experiment. The methodology is demonstrated using a fretting fatigue example.

Tests for linkage and association in nuclear families.

PubMed Central

Martin, E R; Kaplan, N L; Weir, B S

1997-01-01

The transmission/disequilibrium test (TDT) originally was introduced to test for linkage between a genetic marker and a disease-susceptibility locus, in the presence of association. Recently, the TDT has been used to test for association in the presence of linkage. The motivation for this is that linkage analysis typically identifies large candidate regions, and further refinement is necessary before a search for the disease gene is begun, on the molecular level. Evidence of association and linkage may indicate which markers in the region are closest to a disease locus. As a test of linkage, transmissions from heterozygous parents to all of their affected children can be included in the TDT; however, the TDT is a valid chi2 test of association only if transmissions to unrelated affected children are used in the analysis. If the sample contains independent nuclear families with multiple affected children, then one procedure that has been used to test for association is to select randomly a single affected child from each sibship and to apply the TDT to those data. As an alternative, we propose two statistics that use data from all of the affected children. The statistics give valid chi2 tests of the null hypothesis of no association or no linkage and generally are more powerful than the TDT with a single, randomly chosen, affected child from each family. PMID:9311750

Ranking Bias in Association Studies

PubMed Central

Jeffries, Neal O.

2009-01-01

Background It is widely appreciated that genomewide association studies often yield overestimates of the association of a marker with disease when attention focuses upon the marker showing the strongest relationship. For example, in a case-control setting the largest (in absolute value) estimated odds ratio has been found to typically overstate the association as measured in a second, independent set of data. The most common reason given for this observation is that the choice of the most extreme test statistic is often conditional upon first observing a significant p value associated with the marker. A second, less appreciated reason is described here. Under common circumstances it is the multiple testing of many markers and subsequent focus upon those with most extreme test statistics (i.e. highly ranked results) that leads to bias in the estimated effect sizes. Conclusions This bias, termed ranking bias, is separate from that arising from conditioning on a significant p value and may often be a more important factor in generating bias. An analytic description of this bias, simulations demonstrating its extent, and identification of some factors leading to its exacerbation are presented. PMID:19172085

Multi-pulse multi-delay (MPMD) multiple access modulation for UWB

DOEpatents

Dowla, Farid U.; Nekoogar, Faranak

2007-03-20

A new modulation scheme in UWB communications is introduced. This modulation technique utilizes multiple orthogonal transmitted-reference pulses for UWB channelization. The proposed UWB receiver samples the second order statistical function at both zero and non-zero lags and matches the samples to stored second order statistical functions, thus sampling and matching the shape of second order statistical functions rather than just the shape of the received pulses.

Multiple-solution problems in a statistics classroom: an example

NASA Astrophysics Data System (ADS)

Chu, Chi Wing; Chan, Kevin L. T.; Chan, Wai-Sum; Kwong, Koon-Shing

2017-11-01

The mathematics education literature shows that encouraging students to develop multiple solutions for given problems has a positive effect on students' understanding and creativity. In this paper, we present an example of multiple-solution problems in statistics involving a set of non-traditional dice. In particular, we consider the exact probability mass distribution for the sum of face values. Four different ways of solving the problem are discussed. The solutions span various basic concepts in different mathematical disciplines (sample space in probability theory, the probability generating function in statistics, integer partition in basic combinatorics and individual risk model in actuarial science) and thus promotes upper undergraduate students' awareness of knowledge connections between their courses. All solutions of the example are implemented using the R statistical software package.

Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-07-01

This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

Using public control genotype data to increase power and decrease cost of case-control genetic association studies.

PubMed

Ho, Lindsey A; Lange, Ethan M

2010-12-01

Genome-wide association (GWA) studies are a powerful approach for identifying novel genetic risk factors associated with human disease. A GWA study typically requires the inclusion of thousands of samples to have sufficient statistical power to detect single nucleotide polymorphisms that are associated with only modest increases in risk of disease given the heavy burden of a multiple test correction that is necessary to maintain valid statistical tests. Low statistical power and the high financial cost of performing a GWA study remains prohibitive for many scientific investigators anxious to perform such a study using their own samples. A number of remedies have been suggested to increase statistical power and decrease cost, including the utilization of free publicly available genotype data and multi-stage genotyping designs. Herein, we compare the statistical power and relative costs of alternative association study designs that use cases and screened controls to study designs that are based only on, or additionally include, free public control genotype data. We describe a novel replication-based two-stage study design, which uses free public control genotype data in the first stage and follow-up genotype data on case-matched controls in the second stage that preserves many of the advantages inherent when using only an epidemiologically matched set of controls. Specifically, we show that our proposed two-stage design can substantially increase statistical power and decrease cost of performing a GWA study while controlling the type-I error rate that can be inflated when using public controls due to differences in ancestry and batch genotype effects.

Immunochip Analyses of Epistasis in Rheumatoid Arthritis Confirm Multiple Interactions within MHC and Suggest Novel Non-MHC Epistatic Signals.

PubMed

Wei, Wen-Hua; Loh, Chia-Yin; Worthington, Jane; Eyre, Stephen

2016-05-01

Studying statistical gene-gene interactions (epistasis) has been limited by the difficulties in performance, both statistically and computationally, in large enough sample numbers to gain sufficient power. Three large Immunochip datasets from cohort samples recruited in the United Kingdom, United States, and Sweden with European ancestry were used to examine epistasis in rheumatoid arthritis (RA). A full pairwise search was conducted in the UK cohort using a high-throughput tool and the resultant significant epistatic signals were tested for replication in the United States and Swedish cohorts. A forward selection approach was applied to remove redundant signals, while conditioning on the preidentified additive effects. We detected abundant genome-wide significant (p < 1.0e-13) epistatic signals, all within the MHC region. These signals were reduced substantially, but a proportion remained significant (p < 1.0e-03) in conditional tests. We identified 11 independent epistatic interactions across the entire MHC, each explaining on average 0.12% of the phenotypic variance, nearly all replicated in both replication cohorts. We also identified non-MHC epistatic interactions between RA susceptible loci LOC100506023 and IRF5 with Immunochip-wide significance (p < 1.1e-08) and between 2 neighboring single-nucleotide polymorphism near PTPN22 that were in low linkage disequilibrium with independent interaction (p < 1.0e-05). Both non-MHC epistatic interactions were statistically replicated with a similar interaction pattern in the US cohort only. There are multiple but relatively weak interactions independent of the additive effects in RA and a larger sample number is required to confidently assign additional non-MHC epistasis.

Mammalian Toxicity of Munition Compounds. Phase II. Effects of Multiple Doses. Part III. 2,6-Dinitrotoluene

DTIC Science & Technology

1976-07-01

Histopathology , Statistical Analysis, and Normal Values ..... ...... ........... 131 I Ii A.mmALIAN TOXICITY OF MUNITION COMPOUNDS PHASE II: Effects of...chemistry tests and histopathology , and the normal values are given in Appendix I. The concentrations of Ca 2+, Mg2 +, Na+ and K+ in serum were determined...mice fed 2,6-DNT included focal epicarditis or myocarditis, focal cystitis, chronic murine pneumonia or bronchopneumonia, metritis and focal myositis

Method and system for knowledge discovery using non-linear statistical analysis and a 1st and 2nd tier computer program

DOEpatents

Hively, Lee M [Philadelphia, TN

2011-07-12

The invention relates to a method and apparatus for simultaneously processing different sources of test data into informational data and then processing different categories of informational data into knowledge-based data. The knowledge-based data can then be communicated between nodes in a system of multiple computers according to rules for a type of complex, hierarchical computer system modeled on a human brain.

Automating approximate Bayesian computation by local linear regression.

PubMed

Thornton, Kevin R

2009-07-07

In several biological contexts, parameter inference often relies on computationally-intensive techniques. "Approximate Bayesian Computation", or ABC, methods based on summary statistics have become increasingly popular. A particular flavor of ABC based on using a linear regression to approximate the posterior distribution of the parameters, conditional on the summary statistics, is computationally appealing, yet no standalone tool exists to automate the procedure. Here, I describe a program to implement the method. The software package ABCreg implements the local linear-regression approach to ABC. The advantages are: 1. The code is standalone, and fully-documented. 2. The program will automatically process multiple data sets, and create unique output files for each (which may be processed immediately in R), facilitating the testing of inference procedures on simulated data, or the analysis of multiple data sets. 3. The program implements two different transformation methods for the regression step. 4. Analysis options are controlled on the command line by the user, and the program is designed to output warnings for cases where the regression fails. 5. The program does not depend on any particular simulation machinery (coalescent, forward-time, etc.), and therefore is a general tool for processing the results from any simulation. 6. The code is open-source, and modular.Examples of applying the software to empirical data from Drosophila melanogaster, and testing the procedure on simulated data, are shown. In practice, the ABCreg simplifies implementing ABC based on local-linear regression.