[Review of statistical procedures for determining the equivalency of two treatments]

Abstract

The absence of a significant difference in a classical efficacy trial testing the null hypothesis of equality between N and S does not allow us to conclude that the treatments are equivalent. Testing the null hypothesis of N not equivalent to S requires: specifying the definition of "equivalence" by choosing delta L, the upper allowable value of the actual difference between two equivalent treatments. The appropriate statistic D which evaluates the difference between N and S, has a non central distribution under the null hypothesis of inequivalence (Ko:[E(D)] greater than or equal to delta L, two-sided test). Under the null hypothesis for a two-sided test, parameters of noncentral distribution have to be estimated, and the critical p-value is obtained using some approximation. Confidence interval of the true difference delta can also provide a decision rule. Specific calculation of the minimum number of subjects is required when designing an equivalence trial.