etaszquared

Eta-squared, denoted as η², is a measure of effect size used in statistics, particularly within the context of analysis of variance (ANOVA). It quantifies the proportion of total variance in the dependent variable that is attributable to a specific factor or treatment effect. In simpler terms, eta-squared tells you how much of the variation in your outcome is explained by the group you are studying.

The calculation of eta-squared involves dividing the sum of squares for a particular effect by the total sum of squares in the ANOVA model. A value of η² close to 0 indicates that the factor explains very little of the variance, while a value close to 1 suggests that the factor explains a substantial portion of the variance. For instance, if η² = 0.25, it means that 25% of the variation in the dependent variable can be accounted for by the independent variable.

Eta-squared is widely used because it provides an intuitive interpretation of the magnitude of an effect, independent of sample size. This makes it a valuable tool for understanding the practical significance of research findings. However, it is important to note that eta-squared can sometimes be an overestimation of the true population effect size, especially in smaller samples. For this reason, other effect size measures like omega-squared (ω²) are sometimes preferred as they tend to provide a less biased estimate. Despite this, eta-squared remains a commonly reported and easily understood measure of effect size.