Abstract
In order to assess the equivalence of two treatments, clinical trials are designed to test against the null hypothesis that the difference (or ratio) of two means (proportions) is either smaller than a pre-specified lower equivalence limit or larger than a pre-specified upper equivalence limit. For example, in generic drug evaluation, such approach is defined as average bioequivalence. However, average equivalence type test is often criticized as lack of the ability to assess the exchangeability of the two treatments. In this article, we restate the statistical hypotheses in the form of stochastic inequalities. The stochastic statement can then be generalized to define the probability of exchangeability (i.e., coverage percentage) of the two treatments. The approach will be illustrated with a numeric example.
ACKNOWLEDGMENTS
This article is completed as part of the regulatory science research project RSR06-01. The project is funded by Center for Drug Evaluation and Research. The authors want to acknowledge the referee for valuable comments and pointing out the earlier research works of Esinhart and Chinchilli, and Liu and Chow.
Notes
∗This paper does not represent the official position of U.S. Food and Drug Administration.