Randomization model methods for evaluating treatment efficacy in multicenter clinical trials.

This paper studies randomization model methods for analyzing data from a multicenter study comparing the effectiveness of two treatments. The Mantel-Haenszel mean score statistic, which can be used for continuous or ordered categorical response variables, is shown to be a useful nonparametric alternative to standard linear model methods for testing the significance of the average treatment difference. In an extensive simulation study, the mean score test performs nearly as well as the optimal linear model methods when the normal-theory assumptions are satisfied. A related estimator of the average treatment difference is also studied. This estimator, which is a weighted average of the center-specific mean differences, is analogous to the commonly used Mantel-Haenszel estimator of the average odds ratio in stratified 2 x 2 contingency tables. The proposed estimator is equivalent to the fixed-effects analysis of variance estimator from the main effects model, and valid estimation of its variance is feasible under very general assumptions.