Multiple Comparisons Using R

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 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 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

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.

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.

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.

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.