E-Book, Englisch, 205 Seiten
Bretz / Hothorn / Westfall Multiple Comparisons Using R
1. Auflage 2010
ISBN: 978-1-4200-1090-9
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
E-Book, Englisch, 205 Seiten
            ISBN: 978-1-4200-1090-9 
            Verlag: Taylor & Francis
            
 Format: PDF
    Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
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.
Zielgruppe
Researchers and graduate and advanced undergraduate students in statistics; applied scientists in biology, medicine, pharmaceutical industry, molecular biology, and agriculture.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction 
General Concepts 
Error rates and general concepts 
Construction methods 
Methods based on Bonferroni’s inequality 
Methods based on Simes’ inequality 
Multiple Comparisons in Parametric Models
General linear models 
Extensions to general parametric models
The multcomp package
Applications
Multiple comparisons with a control 
All pairwise comparisons 
Dose response analyses 
Variable selection in regression models 
Simultaneous confidence bands 
Multiple comparisons under heteroscedasticity 
Multiple comparisons in logistic regression models 
Multiple comparisons in survival models 
Multiple comparisons in mixed-effects models
Further Topics 
Resampling-based multiple comparison procedures 
Group sequential and adaptive designs 
Combining multiple comparisons with modeling 
Bibliography 
Index





