Open AccessThis article is
- freely available
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; in revised form: 28 December 2012 / Accepted: 14 January 2013 / Published: 21 October 2013
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
Citations to this Article
Cite This Article
MDPI and ACS Style
Efird, J.T. Computing Power and Sample Size for Informational Odds Ratio. Int. J. Environ. Res. Public Health 2013, 10, 5239-5243.
Efird JT. Computing Power and Sample Size for Informational Odds Ratio. International Journal of Environmental Research and Public Health. 2013; 10(10):5239-5243.
Efird, Jimmy T. 2013. "Computing Power and Sample Size for Informational Odds Ratio." Int. J. Environ. Res. Public Health 10, no. 10: 5239-5243.