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Psychol Methods. 2003 Dec;8(4):497-517.

Power and measures of effect size in analysis of variance with fixed versus random nested factors.

Author information

  • 1Department of Psychology, Ernst Moritz Arndt University, Greifswald, Germany. masiemer@uni-greifswald.de

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). 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.

PMID:
14664685
DOI:
10.1037/1082-989X.8.4.497
[PubMed - indexed for MEDLINE]
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