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

By J. Toby Mordkoff. Advances in Methods and Practices in Psychological Science, 2019

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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 ( η ^ p 2 ), is known to have positive bias. Two less-biased alternatives, partial epsilon squared ( ε ^ p 2 ) and partial omega squared ( ω ^ p 2 ), have both existed for decades, but neither is often employed. Given that researchers appear reluctant to abandon η ^ p 2 , this article provides a simple method for removing bias from this measure, to produce a value referred to as adjusted partial eta squared (adj η ^ p 2 ). Some of the many benefits of adopting this measure are briefly discussed.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d73ab82ce0a597ab9e3c895a86a9339b429c3482