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American Journal of Epidemiology Advance Access published online on December 20, 2006
American Journal of Epidemiology, doi:10.1093/aje/kwk052
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American Journal of Epidemiology Copyright © 2006 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

ORIGINAL CONTRIBUTIONS

Relaxing the Rule of Ten Events per Variable in Logistic and Cox Regression

Eric Vittinghoff and Charles E. McCulloch

From the Department of Epidemiology and Biostatistics, University of California, San Francisco, CA

Correspondence to Eric Vittinghoff, Box 0560, Department of Epidemiology and Biostatistics, University of California, 185 Berry Street, Suite 5700, San Francisco, CA 94107 (e-mail: eric{at}biostat.ucsf.edu).

The rule of thumb that logistic and Cox models should be used with a minimum of 10 outcome events per predictor variable (EPV), based on two simulation studies, may be too conservative. The authors conducted a large simulation study of other influences on confidence interval coverage, type I error, relative bias, and other model performance measures. They found a range of circumstances in which coverage and bias were within acceptable levels despite less than 10 EPV, as well as other factors that were as influential as or more influential than EPV. They conclude that this rule can be relaxed, in particular for sensitivity analyses undertaken to demonstrate adequate control of confounding.

bias (epidemiology); coverage probability; event history analysis; model adequacy; type I error; variable selection

Abbreviations: EPV, events per predictor variable


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