Recommended effect size statistics for repeated measures designs |
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Authors: | Email author" target="_blank">Roger?BakemanEmail author |
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Institution: | Department of Psychology, Georgia State University, Atlanta, Georgia 30302-5010, USA. bakeman@gsu.edu |
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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 (ηG2; Olejnik & Algina, 2003). Here, we present this method, explain that ηG2 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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