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 (eta2G; Olejnik & Algina, 2003). Here, we present this method, explain that eta2G 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.
Keywords
ComparabilityStatisticsStatisticVariance (accounting)Repeated measures designEconometricsAdvice (programming)Computer scienceMathematics
MeSH Terms
Behavioral SciencesHumansModelsPsychological
Affiliated Institutions
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Publication Info
- Year
- 2005
- Type
- article
- Volume
- 37
- Issue
- 3
- Pages
- 379-384
- Citations
- 1762
- Access
- Closed
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Cite This
Roger Bakeman
(2005).
Recommended effect size statistics for repeated measures designs.
Behavior Research Methods
, 37
(3)
, 379-384.
https://doi.org/10.3758/bf03192707
Identifiers
- DOI
- 10.3758/bf03192707
- PMID
- 16405133