Multiple Comparison Procedures in Linear Models

Frank Bretz (), Torsten Hothorn () and Peter Westfall ()
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Frank Bretz: Novartis Pharma AG, Statistical Methodology, Clinical Information Sciences
Torsten Hothorn: Ludwig-Maximilians-Universität München, Institut für Statistik
Peter Westfall: Texas Tech University

A chapter in COMPSTAT 2008, 2008, pp 423-431 from Springer

Abstract: Abstract Multiplicity is a difficult and ubiquitous problem. The problem of evaluating multiple experimental questions occurs in many areas of applications, such as, for example, in clinical trials assessing more than one outcome variable, or in agricultural field experiments comparing several irrigation systems. If multiple null hypotheses are tested simultaneously, the probability of declaring effects when none exists increases beyond the nominal type I error level used for the individual comparisons. In this paper we review multiple comparison procedures in the linear model framework. We use the multcomp package from $\mathsf{R}$ to illustrate the methods with a linear regression example.

Keywords: multiplicity; multiple testing; multivariate t; multcomp; $\mathsf{R}$ (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2084-3_35

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DOI: 10.1007/978-3-7908-2084-3_35

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