Computing Power and Sample Size for Informational Odds Ratio †

Author： Efird Jimmy T.  

Publisher： MDPI

E-ISSN： 1660-4601|10|10|5239-5243

ISSN： 1660-4601

Source： International Journal of Environmental Research and Public Health, Vol.10, Iss.10, 2013-10, pp. : 5239-5243

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Abstract

The informational odds ratio (IOR) measures the post-exposure odds divided by the pre-exposure odds (i.e., information gained after knowing exposure status). A desirable property of an adjusted ratio estimate is collapsibility, wherein the combined crude ratio will not change after adjusting for a variable that is not a confounder. Adjusted traditional odds ratios (TORs) are not collapsible. In contrast, Mantel-Haenszel adjusted IORs, analogous to relative risks (RRs) generally are collapsible. IORs are a useful measure of disease association in case-referent studies, especially when the disease is common in the exposed and/or unexposed groups. This paper outlines how to compute power and sample size in the simple case of unadjusted IORs.

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