Advances in Methods and Practices in Psychological Science, Volume 2, Issue 3, Page 228-232, September 2019.

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 ([math]), is known to have positive bias. Two less-biased alternatives, partial epsilon squared ([math]) and partial omega squared ([math]), have both existed for decades, but neither is often employed. Given that researchers appear reluctant to abandon [math], this article provides a simple method for removing bias from this measure, to produce a value referred to as adjusted partial eta squared (adj [math]). Some of the many benefits of adopting this measure are briefly discussed.