A distribution-free procedure for the statistical analysis of bioequivalence studies

In bioequivalence assessment, the consumer risk of erroneously accepting bioequivalence is of primary concern. In order to control the consumer risk, the decision problem is formulated with bioinequivalence as hypothesis and bioequivalence as alternative. In the parametric approach, a split into two one-sided test problems and application of two-sample t-tests have been suggested. Rejection of both hypotheses at nominal alpha-level is equivalent to the inclusion of the classical (shortest) (1-2 alpha) 100%-confidence interval in the bioequivalence range. This paper demonstrates that the rejection of the two one-sided hypotheses at nominal alpha-level by means of nonparametric Mann-Whitney-Wilcoxon tests is equivalent to the inclusion of the corresponding distribution-free (1-2 alpha) 100%-confidence interval in the bioequivalence range. This distribution-free (nonparametric) approach needs weaker model assumptions and hence presents an alternative to the parametric approach.