Effect Size Eta-Squared for Mixed ANOVA in R
The effect size eta-squared for mixed ANOVA in R can be calculated in two ways: a) partially and b) generally. Additionally, c) the partial eta-squared can be converted into the effect size f.
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A primary reason for reporting the generalized eta-squared is to allow for comparability with other studies where other factors were not present.
For example, if a one-way ANOVA is performed, its eta-squared is comparable to the generalized eta-squared of the between-subjects factor in this mixed ANOVA.
The partial eta-squared, the generalized eta-squared, and f can and should be interpreted in relation to comparable studies. Alternatively, discipline-specific limits can be used, or the general limits from Cohen (1992), p. 157, can be applied. These are 0.1, 0.25, and 0.4 for small, medium, and large effects, respectively.
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💡 Mixed ANOVA in R:
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📚 References:
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Cohen, J. (1992). Quantitative Methods in Psychology: A power primer. Psychological Bulletin, pp. 155-159.
Olejnik, S., & Algina, J. (2003). Generalized eta and omega squared statistics: measures of effect size for some common research designs. Psychological Methods, 8(4), 434.
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Timestamp ⏰
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0:00 Introduction
0:09 Partial eta-squared
0:59 Transformation to effect size f
1:33 Generalized eta-squared
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