Modelling paired categorical outcomes in clinical trials

The goal of this paper is to discuss methods for testing the homogeneity of treatment-induced changes in trials with paired categorical responses. Widely used marginal homogeneity tests ignore the information contained in concordant pairs of observations and become highly underpowered for configurations of parameters encountered in real trials. This paper considers models for paired binary or ordinal outcomes based on both discordant and concordant pairs that provide a natural extension of marginal models. Likelihood-ratio tests associated with these models are developed and are demonstrated to be at least as powerful as or more powerful than marginal homogeneity tests. The proposed models are easy to fit using standard statistical software. Copyright © 2003 John Wiley & Sons, Ltd.