Reidpath, DanielDiamond, Mark RHartel, GunterGlasziou, Paul2023-04-062023-04-062000-05-12Reidpath, D.D., Diamond, M.R., Hartel, G. and Glasziou, P. (2000) ‘Improving interpretability: γ as an alternative to R2 as a measure of effect size’, Statistics in Medicine, 19(10), pp. 1295–1302. Available at: https://doi.org/10.1002/(SICI)1097-0258(20000530)19:10<1295::AID-SIM493>3.0.CO;2-Z.0277-6715https://eresearch.qmu.ac.uk/handle/20.500.12289/13127https://doi.org/10.1002/(SICI)1097-0258(20000530)19:10%3C1295::AID-SIM493%3E3.0.CO;2-ZDaniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-0420Item is not available in this repository.A traditional measure of effect size associated with tests for difference between two groups is the variance explained by group membership (R2). If exposure to a disease causes a small but long term deficit in performance, however, R2 does not capture that cumulating effect. We propose an alternative statistic, γ, based on the probability of an unexposed person outperforming an exposed person. Although γ is also a point estimate, it more easily conveys what the cumulating effect of a deficit would be. We discuss some of the advantages of this measure. Copyright © 2000 John Wiley & Sons, Ltd.1295–1302enArticle