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Computing Power and Sample Size for Informational Odds Ratio

Author

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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)

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.

Suggested Citation

  • Jimmy T. Efird, 2013. "Computing Power and Sample Size for Informational Odds Ratio," IJERPH, MDPI, vol. 10(10), pages 1-5, October.
    • Handle: RePEc:gam:jijerp:v:10:y:2013:i:10:p:5239-5243:d:29700
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