R Tutorial Linear mixedeffects models part 2 Repeated measures ANOVA with multiple IVs
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After conducting a repeated measures ANOVA in R it can be helpful to calculate the effect size Eta-Squared (Eta²). In most circumstances it is used for comparison with other studies. • ➡️ Watch next: • Reporting Repeated Measures ANOVA - r... • • However, please keep in mind, that the effect size d for the pairwise comparisons that showed a low enough p-value during post-hoc-testing is more insightfult. I showed the respective calculations in this video: • Effect size for post-hoc-tests of the... • Be aware that the classification of Eta² is reasearch field specific. For the social and behavioral sciences, the paper Cohen, J. (1992), A Power Primer, p. 157 is usually cited. However, Cohen (1992) uses the effect size f, which will require a transofrmation of your Eta-Squared. • Cohen (1988), p. 284 showed the proper formula for the transformation. An effect size should only be reported for a significant effect (aka. low enough p-value). • f is also the common effect size when it comes to doing an apriori sample size calculation, with, for example, G*Power: • Repeated Measures ANOVA - calculate r... • • 📚 Cohen, J. (1992): Quantitative methods in psychology: A power primer. Psychological bulletin, pp. 155-159. • 📚Cohen, J. (1988): Statistical Power Analysis for the Behavioral Sciences. • • ⏰ Timestamps: • ============== • 0:00 Introduction and prerequisites • 0:12 Using anova_test() from rstatix to calculate Eta-squared • 0:31 Classification of Eta-Squared • • If you have any questions or suggestions regarding Effect size Eta-Squared for the repeated measures ANOVA in R please use the comment function. Thumbs up or down to decide if you found the video helpful. • #useR #statorials • • Support channel? 🙌🏼 • =================== • Paypal donation: https://www.paypal.com/paypalme/Bjoer... • Amazon affiliate link: https://amzn.to/49BqP5H
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