Bias reduction in conditional logistic regression
Copyright policy )Bias reduction in conditional logistic regression
AbstractWe employ a general bias preventive approach developed by Firth (Biometrika1993;80:27–38) to reduce the bias of an estimator of the log‐odds ratio parameter in a matched case–control study by solving a modified score equation. We also propose a method to calculate the standard error of the resultant estimator. A closed‐form expression for the estimator of the log‐odds ratio parameter is derived in the case of a dichotomous exposure variable. Finite sample properties of the estimator are investigated via a simulation study. Finally, we apply the method to analyze a matched case–control data from a low birthweight study. Copyright © 2010 John Wiley & Sons, Ltd.
- The University of Texas System United States
- Michigan State University United States
Logistic Models, Bias, Case-Control Studies, Infant, Newborn, Humans, Computer Simulation, Infant, Low Birth Weight, Effect Modifier, Epidemiologic
Logistic Models, Bias, Case-Control Studies, Infant, Newborn, Humans, Computer Simulation, Infant, Low Birth Weight, Effect Modifier, Epidemiologic
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