Application of component-wise rank method to bivariate bioequivalence case

AbstractOne of the most common analyses in pharmaceutical research is bioequivalence test of two drugs. The FDA has endorsed the usage of Schuirmann's two one-sided hypotheses for the analyses in such studies. Generally, however, several measures on the drugs are taken simultaneously such that the data are multivariate. Nandakumar and McKean generalized Schuirmann's procedure to this multivariate setting. For bivariate data, the results can be summarized in a graphical display. These procedures are least-squares-type procedures and hence, are quite sensitive to mild outliers. To counter this sensitivity, Nandakumar and McKean also developed a simple highly efficient and robust analogue to their multivariate least-squares procedure. The robust results can also be displayed graphically, overlaid with the least-squares graphical results. In this paper, a SAS algorithm is presented, which implements these least-squares and robust multivariate tests for bioequivalence, including their graphical summaries.