Improving interpretability: Gamma as an alternative to R-2 as a measure of effect size

Daniel D Reidpath, Mark R Diamond, Gunter Hartel, P Glasziou

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)

Abstract

A traditional measure of effect size associated with tests for difference between two groups is the variance explained by group membership (R-2). If exposure to a disease causes a small but long term deficit in performance, however, R-2 does not capture that cumulating effect. We propose an alternative statistic, gamma, based on the probability of an unexposed person outperforming an exposed person. Although gamma 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 (C) 2000 John WiIey & Sons, Ltd.

Original languageEnglish
Pages (from-to)1295-1302
Number of pages8
JournalStatistics in Medicine
Volume19
Issue number10
DOIs
Publication statusPublished - 30 May 2000
Externally publishedYes

Cite this

Reidpath, Daniel D ; Diamond, Mark R ; Hartel, Gunter ; Glasziou, P. / Improving interpretability : Gamma as an alternative to R-2 as a measure of effect size. In: Statistics in Medicine. 2000 ; Vol. 19, No. 10. pp. 1295-1302.
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Improving interpretability : Gamma as an alternative to R-2 as a measure of effect size. / Reidpath, Daniel D; Diamond, Mark R; Hartel, Gunter; Glasziou, P.

In: Statistics in Medicine, Vol. 19, No. 10, 30.05.2000, p. 1295-1302.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Diamond, Mark R

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