Eta-squared is commonly used in 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 eta-squared 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 [Page 423]to be aware of eta-squared's limitations, which include 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 eta-squared statistic, in addition to reporting statistical significance.
This entry focuses on defining, calculating, and interpreting eta-squared values, and will discuss the ...
Looks like you do not have access to this content.