Multiple Statistical Inferences

Abstract

Clinical trials often compare the efficacy of several new treatments and often use many efficacy variables. Also, after overall testing for significant differences, additional questions about subgroups differences or about what variables do or do not contribute to the efficacy results. Assessment of such questions introduces the statistical problem of multiple comparison and multiple testing, which increases the risk of false positive statistical results, and thus increases the type-I error risk. In this chapter simple methods are discussed which can help to control this risk.