A Simple Method for Removing Bias From a Popular Measure of Standardized Effect Size: Adjusted Partial Eta Squared

Abstract

Accurate estimates of population effect size are critical to empirical science, for both reporting experimental results and conducting a priori power analyses. Unfortunately, the current most-popular measure of standardized effect size, partial eta squared ([Formula: see text]), is known to have positive bias. Two less-biased alternatives, partial epsilon squared ([Formula: see text]) and partial omega squared ([Formula: see text]), have both existed for decades, but neither is often employed. Given that researchers appear reluctant to abandon [Formula: see text], this article provides a simple method for removing bias from this measure, to produce a value referred to as adjusted partial eta squared (adj [Formula: see text]). Some of the many benefits of adopting this measure are briefly discussed.