Computing Power and Sample Size for Informational Odds Ratio

Jimmy T. Efird
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Jimmy T. Efird: Center for Health Disparities Research and Department of Public Health, Brody School of Medicine, Greenville, NC 27858, USA

IJERPH, 2013, vol. 10, issue 10, 1-5

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.

Keywords: informational odds ratios; power; sample size (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2013
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