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American Journal of Epidemiology Advance Access originally published online on May 15, 2007
American Journal of Epidemiology 2007 166(3):332-339; doi:10.1093/aje/kwm069
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American Journal of Epidemiology © The Author 2007. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

ORIGINAL CONTRIBUTIONS

On the Estimation and Use of Propensity Scores in Case-Control and Case-Cohort Studies

Roger Månsson, Marshall M. Joffe, Wenguang Sun and Sean Hennessy

From the Department of Biostatistics and Epidemiology and Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, PA

Correspondence to Dr. Sean Hennessy, University of Pennsylvania School of Medicine, 803 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021 (e-mail: shenness{at}cceb.med.upenn.edu).

Received for publication February 8, 2006. Accepted for publication January 26, 2007.

The use of propensity scores to adjust for measured confounding factors has become increasingly popular in cohort studies. However, their use in case-control and case-cohort studies has received little attention. The authors present some theory on the estimation and use of propensity scores in case-control and case-cohort studies and present the results of simulation studies that examine whether large-sample expectations are realized in studies of typical size. The application of propensity scores is less straightforward in case-control and case-cohort studies than in cohort studies. The authors' simulations revealed two potentially important issues. First, when using several potential approaches, there is artifactual effect modification of the odds ratio by level of propensity score. The magnitude of this phenomenon decreases as the sample size increases. Second, several potential approaches produce estimated propensity scores that do not converge to the true value as sample size increases and, thus, can fail to adjust fully for measured confounding factors. However, the magnitude of residual confounding appeared modest in our simulations. Researchers considering using propensity scores in case-control or case-cohort studies should consider the potential for artifactual effect modification and their reduced ability to control for potential confounding factors.

bias (epidemiology); case-control studies; cohort studies; confounding factors (epidemiology); epidemiologic methods; models, statistical; propensity score


Abbreviations: IPTW, inverse probability of exposure (or treatment) weighting


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