A Decision Rule Approach to Evaluating Several Independently Conducted Trials Collectively
Qian Li and Mohammad F. Huque, FDA

Usually, in applying for market approval of a new drug, more than one similarly designed clinical trial is conducted to support efficacy claims. How to evaluate these trials collectively and assess the overall type I error of a decision rule can be a challenging statistical issue. In this paper, we propose to use a decision rule approach to evaluate several similarly designed and independently conducted trials collectively, while controlling the overall type I error at a desired level. A concept of overall hypotheses, which is essentially union or intersection combinations of individual trial's hypotheses, is used so that the error can be controlled strongly or weakly at desired levels. We also discuss some important properties of the approach, including the relationship of the overall type I errors among the overall hypotheses and the power characteristics of the approach. A couple of examples are presented to illustrate the application of the approach.