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Int. J. Environ. Res. Public Health 2013, 10(10), 5239-5243; doi:10.3390/ijerph10105239
Communication

Computing Power and Sample Size for Informational Odds Ratio

Center for Health Disparities Research and Department of Public Health, Brody School of Medicine, Greenville, NC 27858, USA
This paper is an extended version of paper presented at the Ninth International Symposium on Recent Advances in Environmental Health Research, Jackson, MS, USA; 16–19 September 2012.
Received: 16 November 2012 / Revised: 28 December 2012 / Accepted: 14 January 2013 / Published: 21 October 2013
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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.
Keywords: informational odds ratios; power; sample size informational odds ratios; power; sample size
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Efird, J.T. Computing Power and Sample Size for Informational Odds Ratio. Int. J. Environ. Res. Public Health 2013, 10, 5239-5243.

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