Eta-squared (η2) is commonly used in analysis of variance (ANOVA) and t-test designs as an index of the proportion of variance attributed to one or more effects. The statistic is useful in describing how variables are behaving within the researcher’s sample. In addition, because η2 is a measure of effect size, researchers are able to compare effects of grouping variables or treatment conditions across related studies. Despite these advantages, researchers need to be aware of the limitations of η2, which includes an overestimation of population effects and its sensitivity to design features that influence its relevance and interpretability. Nonetheless, many social scientists advocate for the reporting of the η2 statistic, in addition to reporting statistical significance.

This entry focuses on defining, calculating, and interpreting η2 ...

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