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Recommended effect size statistics for repeated measures designs

  • Published: August 2005
  • Volume 37, pages 379–384, (2005)
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Recommended effect size statistics for repeated measures designs
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  • Roger Bakeman1 
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Abstract

Investigators, who are increasingly implored to present and discuss effect size statistics, might comply more often if they understood more clearly what is required. When investigators wish to report effect sizes derived from analyses of variance that include repeated measures, past advice has been problematic. Only recently has a generally useful effect size statistic been proposed for such designs: generalized eta squared (η 2G ; Olejnik & Algina, 2003). Here, we present this method, explain that η 2G is preferred to eta squared and partial eta squared because it provides comparability across between-subjects and within-subjects designs, show that it can easily be computed from information provided by standard statistical packages, and recommend that investigators provide it routinely in their research reports when appropriate.

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Authors and Affiliations

  1. Department of Psychology, Georgia State University, P.O. Box 5010, 30302-5010, Atlanta, GA

    Roger Bakeman

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  1. Roger Bakeman
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Correspondence to Roger Bakeman.

Additional information

My appreciation to my colleague, Christopher Henrich, and to two anonymous reviewers who provided useful and valuable feedback on earlier versions of this article.

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Bakeman, R. Recommended effect size statistics for repeated measures designs. Behavior Research Methods 37, 379–384 (2005). https://doi.org/10.3758/BF03192707

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  • Received: 13 October 2004

  • Accepted: 25 March 2005

  • Issue Date: August 2005

  • DOI: https://doi.org/10.3758/BF03192707

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Keywords

  • Repeat Measure Design
  • Lowercase Letter
  • Repeated Measure Factor
  • Effect Size Measure
  • Standard Statistical Package
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