Power and Measures of Effect Size in Analysis of Variance with Fixed Versus Random Nested Factors

Matthias Siemer, Jutta Joormann

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

Ignoring a nested factor can influence the validity of statistical decisions about treatment effectiveness. Previous discussions have centered on consequences of ignoring nested factors versus treating them as random factors on Type I errors and measures of effect size (B. E. Wampold & R. C. Serlin, 2000). The authors (a) discuss circumstances under which the treatment of nested provider effects as fixed as opposed to random is appropriate; (b) present 2 formulas for the correct estimation of effect sizes when nested factors are fixed; (c) present the results of Monte Carlo simulations of the consequences of treating providers as fixed versus random on effect size estimates, Type I error rates, and power; and (d) discuss implications of mistaken considerations of provider effects for the study of differential treatment effects in psychotherapy research.

Original languageEnglish (US)
Pages (from-to)497-517
Number of pages21
JournalPsychological Methods
Volume8
Issue number4
DOIs
StatePublished - Dec 1 2003

ASJC Scopus subject areas

  • Psychology (miscellaneous)

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