Multiple Comparisons Using R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multiple Comparisons Using R write by Frank Bretz. This book was released on 2016-04-19. Multiple Comparisons Using R available in PDF, EPUB and Kindle. 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.
Doing Meta-Analysis with R
Doing Meta-Analysis with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Doing Meta-Analysis with R write by Mathias Harrer. This book was released on 2021-09-15. Doing Meta-Analysis with R available in PDF, EPUB and Kindle. 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
Learning Statistics with R
Learning Statistics with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Learning Statistics with R write by Daniel Navarro. This book was released on 2013-01-13. Learning Statistics with R available in PDF, EPUB and Kindle. "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
Multiple Comparisons
Multiple Comparisons - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multiple Comparisons write by Jason Hsu. This book was released on 1996-02-01. Multiple Comparisons available in PDF, EPUB and Kindle. 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.
Multiple Comparisons for Researchers
Multiple Comparisons for Researchers - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multiple Comparisons for Researchers write by Larry E. Toothaker. This book was released on 1991-08-27. Multiple Comparisons for Researchers available in PDF, EPUB and Kindle. Through clear exposition and step-by-step procedures, Toothaker describes all the most important multiple comparison procedures along with relevant concepts, such as error rate, power, robustness and coverage of two-way ANOVA including the controversy on cell mean versus tests on interaction effects. The book also includes samples of multiple comparison programs in SAS and SPSS.
