Testing secondary hypotheses following sequential clinical trials

Abstract

Sequential monitoring in a clinical trial poses difficulty in hypotheses testing on secondary endpoints after the trial is terminated. The conventional likelihood-based testing procedure that ignores the sequential monitoring inflates Type I error and undermines power. In this article, we show that the power of the conventional testing procedure can be substantially improved while the Type I error is controlled. The method is illustrated with a real clinical trial.