Multiple Comparisons Using R

Author : Frank Bretz,Torsten Hothorn,Peter Westfall
Publisher : CRC Press
Page : 205 pages
File Size : 43,9 Mb
Release : 2016-04-19
Category : Mathematics
ISBN : 1420010905

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Multiple Comparisons Using R by Frank Bretz,Torsten Hothorn,Peter Westfall Pdf

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.

Author : Larry E. Toothaker
Publisher : SAGE
Page : 108 pages
File Size : 40,9 Mb
Release : 1993
Category : Mathematics
ISBN : 0803941773

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Multiple Comparison Procedures by Larry E. Toothaker Pdf

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.

Author : Daniel Navarro
Publisher : Lulu.com
Page : 617 pages
File Size : 50,9 Mb
Release : 2013-01-13
Category : Psychology
ISBN : 9781326189723

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Learning Statistics with R by Daniel Navarro Pdf

"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

Author : Jason Hsu
Publisher : CRC Press
Page : 306 pages
File Size : 41,5 Mb
Release : 1996-02-01
Category : Mathematics
ISBN : 0412982811

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Multiple Comparisons by Jason Hsu Pdf

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.

Author : Mathias Harrer,Pim Cuijpers,Toshi A. Furukawa,David D. Ebert
Publisher : CRC Press
Page : 500 pages
File Size : 42,6 Mb
Release : 2021-09-15
Category : Mathematics
ISBN : 9781000435634

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Doing Meta-Analysis with R by Mathias Harrer,Pim Cuijpers,Toshi A. Furukawa,David D. Ebert Pdf

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

Author : Jason Hsu
Publisher : CRC Press
Page : 292 pages
File Size : 47,7 Mb
Release : 1996-02-01
Category : Mathematics
ISBN : 9781482221275

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Multiple Comparisons by Jason Hsu Pdf

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

Author : Peter H. Westfall,Randall D. Tobias
Publisher : SAS Press
Page : 0 pages
File Size : 55,9 Mb
Release : 2000
Category : Computers
ISBN : 1580257593

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Multiple Comparisons and Multiple Tests by Peter H. Westfall,Randall D. Tobias Pdf

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.

Author : John Maindonald,W. John Braun
Publisher : Cambridge University Press
Page : 565 pages
File Size : 47,5 Mb
Release : 2010-05-06
Category : Computers
ISBN : 9781139486675

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Data Analysis and Graphics Using R by John Maindonald,W. John Braun Pdf

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.

Author : Yoav Benjamini,Frank Bretz,Sanat K. Sarkar
Publisher : IMS
Page : 168 pages
File Size : 42,5 Mb
Release : 2004
Category : Mathematics
ISBN : 0940600633

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Recent Developments in Multiple Comparison Procedures by Yoav Benjamini,Frank Bretz,Sanat K. Sarkar Pdf

Author : John Lawson
Publisher : CRC Press
Page : 629 pages
File Size : 51,5 Mb
Release : 2014-12-17
Category : Mathematics
ISBN : 9781498728485

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Design and Analysis of Experiments with R by John Lawson Pdf

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,

Author : Daniel H. Baker
Publisher : Oxford University Press
Page : 353 pages
File Size : 46,8 Mb
Release : 2022
Category : Life sciences
ISBN : 9780192896599

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Research Methods Using R by Daniel H. Baker Pdf

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.

Author : Pablo Inchausti
Publisher : Oxford University Press
Page : 519 pages
File Size : 47,8 Mb
Release : 2022-11-02
Category : Science
ISBN : 9780192675033

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Statistical Modeling With R by Pablo Inchausti Pdf

To date, statistics has tended to be neatly divided into two theoretical approaches or frameworks: frequentist (or classical) and Bayesian. Scientists typically choose the statistical framework to analyse their data depending on the nature and complexity of the problem, and based on their personal views and prior training on probability and uncertainty. Although textbooks and courses should reflect and anticipate this dual reality, they rarely do so. This accessible textbook explains, discusses, and applies both the frequentist and Bayesian theoretical frameworks to fit the different types of statistical models that allow an analysis of the types of data most commonly gathered by life scientists. It presents the material in an informal, approachable, and progressive manner suitable for readers with only a basic knowledge of calculus and statistics. Statistical Modeling with R is aimed at senior undergraduate and graduate students, professional researchers, and practitioners throughout the life sciences, seeking to strengthen their understanding of quantitative methods and to apply them successfully to real world scenarios, whether in the fields of ecology, evolution, environmental studies, or computational biology.

Author : Peter H. Westfall,Randall D. Tobias,Russell D. Wolfinger
Publisher : SAS Institute
Page : 645 pages
File Size : 47,9 Mb
Release : 2011
Category : Computers
ISBN : 9781607648857

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Multiple Comparisons and Multiple Tests Using SAS, Second Edition by Peter H. Westfall,Randall D. Tobias,Russell D. Wolfinger Pdf

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.

Author : Ding-Geng (Din) Chen,Karl E. Peace
Publisher : CRC Press
Page : 384 pages
File Size : 44,8 Mb
Release : 2010-12-14
Category : Mathematics
ISBN : 9781439840214

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Clinical Trial Data Analysis Using R by Ding-Geng (Din) Chen,Karl E. Peace Pdf

Too often in biostatistical research and clinical trials, a knowledge gap exists between developed statistical methods and the applications of these methods. Filling this gap, Clinical Trial Data Analysis Using R provides a thorough presentation of biostatistical analyses of clinical trial data and shows step by step how to implement the statistical methods using R. The book’s practical, detailed approach draws on the authors’ 30 years of real-world experience in biostatistical research and clinical development. Each chapter presents examples of clinical trials based on the authors’ actual experiences in clinical drug development. Various biostatistical methods for analyzing the data are then identified. The authors develop analysis code step by step using appropriate R packages and functions. This approach enables readers to gain an understanding of the analysis methods and R implementation so that they can use R to analyze their own clinical trial data. With step-by-step illustrations of R implementations, this book shows how to easily use R to simulate and analyze data from a clinical trial. It describes numerous up-to-date statistical methods and offers sound guidance on the processes involved in clinical trials.

Author : Sorin Draghici
Publisher : CRC Press
Page : 1036 pages
File Size : 49,6 Mb
Release : 2016-04-19
Category : Computers
ISBN : 9781439809761

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Statistics and Data Analysis for Microarrays Using R and Bioconductor by Sorin Draghici Pdf

Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on,