After conducting a mixed 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.
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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: [ Ссылка ]


📚 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:
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0:00 Introduction and prerequisites
0:06 Using anova_test() from rstatix to calculate Eta-squared
0:30 More than one Eta-Squared
0:57 Transformation of Eta-Squared to f
1:24 Classifying the effect size f


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