ABSTRACT
Because the patient population consists of several regions and patients are nested within their own regions, data observed in multi-regional clinical trials (MRCTs) are structurally hierarchical. In order to reflect such a hierarchical structure, this chapter discusses two-level hierarchical linear models in which the level-1 model is based on patient-level data such as treatment indicator and age, and the level-2 model is based on region-level data such as medical practices. The fixed-effect model and the continuous random effect model are shown to be special cases of hierarchical linear models. Simulation studies are conducted to investigate the empirical type I error rates of three methods for testing the overall treatment effect. The performance of the testing method with sample ratios as weights and the empirical Bayes estimator for between-region variability is better than that of the other two testing methods.
