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. © Taylor & Francis Group, LLC.
CITATION STYLE
Chen, H., Cohen, P., & Chen, S. (2010). How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. Communications in Statistics: Simulation and Computation, 39(4), 860–864. https://doi.org/10.1080/03610911003650383
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