A1 Refereed original research article in a scientific journal
General formulae for transforming Pearson’s r to the scale of Cohen’s d; 
Authors: Metsämuuronen, Jari
Publisher: SAGE
Publication year: 2026
Journal: Applied Psychological Measurement
ISSN: 0146-6216
eISSN: 1552-3497
DOI: https://doi.org/10.1177/01466216261465015
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Partially Open Access publication channel
Web address : https://doi.org/10.1177/01466216261465015
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/527003893
Self-archived copy's licence: CC BY
Self-archived copy's version: Publisher`s PDF
The traditional thresholds for product-moment correlation (r) usually condensed in terms of “very small,” “small,” “medium,” “large,” “very large,” and “huge” are derived on the scale of d. Properly transforming an estimate of r to the scale of Cohen’s d is important for qualitatively evaluating the magnitude of the r effect size. A proper formula exists for a transformation between r and d in the binary and dichotomous settings, but not in polytomous or continuous settings. The traditional formula for polytomous settings assumes an equal number of cases in the subpopulations and can lead to a radically misleading transformation if the group sizes are severely imbalanced. Two general formulae are derived for transformations applicable to dichotomous, polytomous, and continuous cases, regardless of the imbalance in the group sizes. Real-life examples are given which illustrate the use of the general forms and difference between the general and the traditional forms.
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Funding information in the publication:
The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author declares that no funds, grants, or other support were received during the preparation of this manuscript. The study has been completed as part of the EDUCA Flagship project funded by the Research Council of Finland (#358924, #358947).