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Multiple Comparison Procedures in Linear Models

In: Compstat 2008

Author

Listed:
  • Frank Bretz

    (Novartis Pharma AG, Statistical Methodology, Clinical Information Sciences)

  • Torsten Hothorn

    (Ludwig-Maximilians-Universität München, Institut für Statistik)

  • Peter Westfall

    (Texas Tech University)

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.

Suggested Citation

  • Frank Bretz & Torsten Hothorn & Peter Westfall, 2008. "Multiple Comparison Procedures in Linear Models," Springer Books, in: Paula Brito (ed.), Compstat 2008, pages 423-431, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2084-3_35
    DOI: 10.1007/978-3-7908-2084-3_35
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