An alternative approach to assess exchangeability of a test treatment and the standard treatment with normally distributed response.
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.
Tsong
Yi
Y
Division of Biometric VI, OB, CDER, FDA, Silver Spring, MD 20993-0002, USA. yi.tsong@fda.hhs.gov
Shen
Meiyu
M
D002986:Clinical Trials as Topic / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D018849:Controlled Clinical Trials as Topic / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D016568:Drugs, Generic / Q000493:pharmacokinetics / Q000627:therapeutic use; D006801:Humans; D015233:Models, Statistical; D012107:Research Design / Q000592:standards / Q000706:statistics & numerical data*; D013810:Therapeutic Equivalency
D016568:Drugs, Generic