Constructing more powerful exact tests of equivalence from binary matched pairs

Abstract

In randomized clinical trials, it is often necessary to demonstrate that a new medical treatment does not substantially differ from a standard reference treatment. Formal testing of such 'equivalence hypotheses' is typically done by combining two one-sided tests (TOST). A quite different strand of research has demonstrated that replacing nuisance parameters with a null estimate produces P-values that are close to exact (Lloyd 2008a) and that maximizing over the residual dependence on the nuisance parameter produces P-values that are exact and optimal within a class (Röhmel & Mansmann 1999; Lloyd 2008a). The three procedures - TOST, estimation and maximization of a nuisance parameter - can ea..