Generalized Cohen’s d for Multiple Means and Polytomous Settings

Cohen's <i>d</i> is the most commonly used estimator to quantify the magnitude of the difference between the means of two subpopulations. When comparing multiple populations simultaneously, Cohen's <i>f</i> can be used for the same purpose. Using their relationship in the dichotomous setting, several general formulas for <i>d</i> are derived that generalize <i>d</i> to the polytomous setting. The traditional simplified estimator <i>d</i> = 2<i>f</i> is studied as a shortcut estimator. It is strongly recommended to use the general formulas instead of the simplified ones when assessing the magnitude of the effect size, especially when the discrepancy of the extreme proportions of cases in the subpopulations exceeds 0.40.

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Publication Details

Journal
Applied Psychological Measurement
Published
2026-01-20
DOI
https://doi.org/10.1177/01466216261416025
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

Generalized Cohen’s d for Multiple Means and Polytomous Settings

Jari Metsämuuronen
Applied Psychological Measurement
Statistical Distribution Estimation and Applications
article

Generalized Cohen’s d for Multiple Means and Polytomous Settings

Jari Metsämuuronen
article en

Abstract

Cohen's <i>d</i> is the most commonly used estimator to quantify the magnitude of the difference between the means of two subpopulations. When comparing multiple populations simultaneously, Cohen's <i>f</i> can be used for the same purpose. Using their relationship in the dichotomous setting, several general formulas for <i>d</i> are derived that generalize <i>d</i> to the polytomous setting. The traditional simplified estimator <i>d</i> = 2<i>f</i> is studied as a shortcut estimator. It is strongly recommended to use the general formulas instead of the simplified ones when assessing the magnitude of the effect size, especially when the discrepancy of the extreme proportions of cases in the subpopulations exceeds 0.40.

Applied Psychological Measurement
University of Turku (FI)
Reduced inequalities
Openalex Percentile: Top 85%
Statistical Distribution Estimation and Applications
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