Open AccessMedicineMathematicsComputer Science

Henian Chen, P. Cohen, Sophie Chen

2010.3.31COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION

DOI: 10.1080/03610911003650383

Résumé tlooto

A new method for interpreting the size of the OR by relating it to differences in a normal standard deviate is proposed, which indicates that OR = 1.68, 3.47, and 6.71 are equivalent to Cohen's d = 0.2, 0.5, and 0.8 when OR > 5.8.

Résumé

The odds ratio (OR) is probably the most widely used index of effect size in epidemiological studies. The difficulty of interpreting the OR has troubled many clinical researchers and epidemiologists for a long time. We propose a new method for interpreting the size of the OR by relating it to differences in a normal standard deviate. Our calculations indicate that OR = 1.68, 3.47, and 6.71 are equivalent to Cohen's d = 0.2 (small), 0.5 (medium), and 0.8 (large), respectively, when disease rate is 1% in the nonexposed group; Cohen's d < 0.2 when OR <1.5, and Cohen's d > 0.8 when OR > 5.

Format de citation

CHEN, Henian; COHEN, P.; CHEN, Sophie. How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2010, 39: 860–864.