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Multiple Comparisons Using R
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Book Synopsis Multiple Comparisons Using R by : Frank Bretz
Download or read book Multiple Comparisons Using R written by Frank Bretz and published by CRC Press. This book was released on 2016-04-19 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org After giving examples of multiplicity problems, the book covers general concepts and basic multiple comparisons procedures, including the Bonferroni method and Simes’ test. It then shows how to perform parametric multiple comparisons in standard linear models and general parametric models. It also introduces the multcomp package in R, which offers a convenient interface to perform multiple comparisons in a general context. Following this theoretical framework, the book explores applications involving the Dunnett test, Tukey’s all pairwise comparisons, and general multiple contrast tests for standard regression models, mixed-effects models, and parametric survival models. The last chapter reviews other multiple comparison procedures, such as resampling-based procedures, methods for group sequential or adaptive designs, and the combination of multiple comparison procedures with modeling techniques. Controlling multiplicity in experiments ensures better decision making and safeguards against false claims. A self-contained introduction to multiple comparison procedures, this book offers strategies for constructing the procedures and illustrates the framework for multiple hypotheses testing in general parametric models. It is suitable for readers with R experience but limited knowledge of multiple comparison procedures and vice versa. See Dr. Bretz discuss the book.
Download or read book Multiple Comparisons written by Jason Hsu and published by CRC Press. This book was released on 1996-02-01 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Comparisons introduces simultaneous statistical inference and covers the theory and techniques for all-pairwise comparisons, multiple comparisons with the best, and multiple comparisons with a control. The author describes confidence intervals methods and stepwise exposes abuses and misconceptions, and guides readers to the correct method for each problem. Discussions also include the connections with bioequivalence, drug stability, and toxicity studies Real data sets analyzed by computer software packages illustrate the applications presented.
Book Synopsis Doing Meta-Analysis with R by : Mathias Harrer
Download or read book Doing Meta-Analysis with R written by Mathias Harrer and published by CRC Press. This book was released on 2021-09-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
Book Synopsis Multiple Comparison Procedures by : Larry E. Toothaker
Download or read book Multiple Comparison Procedures written by Larry E. Toothaker and published by SAGE. This book was released on 1993 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you conduct research with more than two groups and want to find out if they are significantly different when compared two at a time, then you need Multiple Comparison Procedures. Using examples to illustrate major concepts, this concise volume is your guide to multiple comparisons. Toothaker thoroughly explains such essential issues as planned vs. post-hoc comparisons, stepwise vs. simultaneous test procedures, types of error rate, unequal sample sizes and variances, and interaction tests vs. cell mean tests.
Book Synopsis Learning Statistics with R by : Daniel Navarro
Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Download or read book Multiple Comparisons written by Jason Hsu and published by CRC Press. This book was released on 1996-02-01 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Comparisons introduces simultaneous statistical inference and covers the theory and techniques for all-pairwise comparisons, multiple comparisons with the best, and multiple comparisons with a control. The author describes confidence intervals methods and stepwise exposes abuses and misconceptions, and guides readers to the correct method
Book Synopsis Multiple Comparisons and Multiple Tests by : Peter H. Westfall
Download or read book Multiple Comparisons and Multiple Tests written by Peter H. Westfall and published by SAS Press. This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Does your work require multiple inferences? Are you a statistics teacher looking for a study guide to supplement the usually incomplete or outdated multiple comparisons/multiple testing material in your textbook? This workbook, the companion guide written specifically for use with Multiple Comparisons and Multiple Tests Using the SAS System, provides the supplement you need. Use this workbook and you will find problems and solutions that will enhance your understanding of the material within the main text. The workbook also provides updated information about multiple comparisons procedures, including enhancements for Release 8.1 of the SAS System. The chapters correlate with the chapters of the main text, and the format is clear and easy to use. This book and the companion text are quite useful as supplements for learning multiple comparisons procedures in standard linear models, multivariate analysis, categorical analysis, and regression and nonparametric statistics. Book jacket.
Book Synopsis Multiple Comparison Procedures by : Yosef Hochberg
Download or read book Multiple Comparison Procedures written by Yosef Hochberg and published by . This book was released on 1987-10-05 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a balanced, up-to-date view of multiple comparison procedures, this book refutes the belief held by some statisticians that such procedures have no place in data analysis. With equal emphasis on theory and applications, it establishes the advantages of multiple comparison techniques in reducing error rates and in ensuring the validity of statistical inferences. Provides detailed descriptions of the derivation and implementation of a variety of procedures, paying particular attention to classical approaches and confidence estimation procedures. Also discusses the benefits and drawbacks of other methods. Numerous examples and tables for implementing procedures are included, making this work both practical and informative.
Book Synopsis Multiple Testing Problems in Pharmaceutical Statistics by : Alex Dmitrienko
Download or read book Multiple Testing Problems in Pharmaceutical Statistics written by Alex Dmitrienko and published by CRC Press. This book was released on 2009-12-08 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful Statistical Approaches for Addressing Multiplicity IssuesIncludes practical examples from recent trials Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple c
Book Synopsis Data Analysis and Graphics Using R by : John Maindonald
Download or read book Data Analysis and Graphics Using R written by John Maindonald and published by Cambridge University Press. This book was released on 2010-05-06 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover what you can do with R! Introducing the R system, covering standard regression methods, then tackling more advanced topics, this book guides users through the practical, powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display, and interpretation of data. The many worked examples, from real-world research, are accompanied by commentary on what is done and why. The companion website has code and datasets, allowing readers to reproduce all analyses, along with solutions to selected exercises and updates. Assuming basic statistical knowledge and some experience with data analysis (but not R), the book is ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practising statisticians. It is both for learning and for reference. This third edition expands upon topics such as Bayesian inference for regression, errors in variables, generalized linear mixed models, and random forests.
Book Synopsis Recent Developments in Multiple Comparison Procedures by : Yoav Benjamini
Download or read book Recent Developments in Multiple Comparison Procedures written by Yoav Benjamini and published by IMS. This book was released on 2004 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pairwise Multiple Comparisons by : Taka-aki Shiraishi
Download or read book Pairwise Multiple Comparisons written by Taka-aki Shiraishi and published by Springer Nature. This book was released on 2019-09-30 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on all-pairwise multiple comparisons of means in multi-sample models, introducing closed testing procedures based on maximum absolute values of some two-sample t-test statistics and on F-test statistics in homoscedastic multi-sample models. It shows that (1) the multi-step procedures are more powerful than single-step procedures and the Ryan/Einot–Gabriel/Welsh tests, and (2) the confidence regions induced by the multi-step procedures are equivalent to simultaneous confidence intervals. Next, it describes the multi-step test procedure in heteroscedastic multi-sample models, which is superior to the single-step Games–Howell procedure. In the context of simple ordered restrictions of means, the authors also discuss closed testing procedures based on maximum values of two-sample one-sided t-test statistics and based on Bartholomew's statistics. Furthermore, the book presents distribution-free procedures and describes simulation studies performed under the null hypothesis and some alternative hypotheses. Although single-step multiple comparison procedures are generally used, the closed testing procedures described are more powerful than the single-step procedures. In order to execute the multiple comparison procedures, the upper 100α percentiles of the complicated distributions are required. Classical integral formulas such as Simpson's rule and the Gaussian rule have been used for the calculation of the integral transform that appears in statistical calculations. However, these formulas are not effective for the complicated distribution. As such, the authors introduce the sinc method, which is optimal in terms of accuracy and computational cost.
Book Synopsis Two-Way Analysis of Variance by : Thomas W. MacFarland
Download or read book Two-Way Analysis of Variance written by Thomas W. MacFarland and published by Springer Science & Business Media. This book was released on 2011-12-09 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes a test between these groups. One test often used by statisticians and researchers in their work is the Two-Way ANOVA, which determines the differences--and possible interactions--when variables are presented from the perspective of two or more categories. When a Two-Way ANOVA is implemented, it enables one to compare and contrast variables resulting from independent or joint actions. This brief provides guidance on how R can be used to facilitate Two-Way ANOVA for data analysis and graphical presentation. Along with instruction on the use of R and R syntax associated with Two-Way ANOVA, this brief will also reinforce the use of descriptive statistics and graphical figures to complement outcomes from parametric Two-Way ANOVA.
Book Synopsis Using R for Introductory Statistics by : John Verzani
Download or read book Using R for Introductory Statistics written by John Verzani and published by CRC Press. This book was released on 2018-10-03 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.
Book Synopsis Design and Analysis of Experiments with R by : John Lawson
Download or read book Design and Analysis of Experiments with R written by John Lawson and published by CRC Press. This book was released on 2014-12-17 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data, shows how to perform the proper analysis of the data,
Book Synopsis Multiple Comparisons and Multiple Tests Using SAS, Second Edition by : Peter H. Westfall
Download or read book Multiple Comparisons and Multiple Tests Using SAS, Second Edition written by Peter H. Westfall and published by SAS Institute. This book was released on 2011 with total page 645 pages. Available in PDF, EPUB and Kindle. Book excerpt: New and extensively updated for SAS 9 and later, this work provides cutting-edge methods, specialized macros, and proven best bet procedures. The book also discusses the pitfalls and advantages of various methods, thereby helping readers to decide which is the most appropriate for their purposes. 644 pp. Pub. 7/11.
Book Synopsis Research Methods Using R by : Daniel H. Baker
Download or read book Research Methods Using R written by Daniel H. Baker and published by Oxford University Press. This book was released on 2022 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing complete coverage of advanced research methods for undergraduates, Daniel H. Baker supports students in their mastery of more advanced research methods and their application in R.This brand new title brings together coverage of a variety of topics for readers with basic statistical knowledge. It begins with material on the fundamental tools - nonlinear curve fitting and function optimization, stochastic methods, and Fourier (frequency) analysis - before leading readers on tomore specialist content - bivariate and multivariate statistics, Bayesian statistics, and machine learning methods. Several chapters also discuss methods that can be used to improve research practises, including power analysis, meta-analysis, reproducible data analysis.Written to build a student's confidence with using R in a step-by-step way, early chapters present the essentials, ensuring that the content is accessible to those that have never programmed before. By giving them a feel for how the software works in practice, students are gradually introduced tosimple examples of techniques before building up to more detailed implementations demonstrated in worked examples.Readers are also presented with opportunities to try analysis techniques for themselves. Practice questions are presented at the end of each chapter with answer guidance supplied in the book, while multiple-choice-questions with instant feedback can be accessed online. The author also providesdatasets online which students can use to practise their new skills.Digital formats and resourcesThis book is available for students and institutions to purchase in a variety of formats, and is supported by online resources.- The e-book offers a mobile experience and convenient access along with functionality, navigation features, and links that offer extra learning support. This book is accompanied by online resources including multiple-choice-questions with instant feedback, example code, and data files allowingstudents to run examples independently.
