A comparison of two methods of estimating a common risk difference in a stratified analysis of a multicenter clinical trial

Abstract

In this paper, we compare two methods of estimating the difference between the proportion of adverse events in a test treatment group and the proportion of adverse events in a control treatment group in a multicenter clinical trial. We used simulated data to compare the bias and mean squared error of the weighted least squares estimator to the bias and mean squared error of the Cochran-Mantel-Haenszel estimator. We also computed the coverage probabilities for confidence intervals derived from these estimators. We found that the weighted least squares method was often seriously biased. The coverage probabilities for the Cochran-Mantel-Haenszel estimators were often closer to their nominal values than were the coverage probabilities for the weighted least squares estimators. It also was found that these methods require a larger sample size to maintain coverage probabilities near their nominal values when unequal numbers of persons are assigned to the test and control treatments.