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Abstract

There are several problems concerning the statistical definition of average bioequivalence provided by the U.S. Food and Drug Administration. We proposed a ratio of means based on the original bioavailability measure as the definition for average bioequivalence. Under the log-normal distribution assumption, we proposed a hypothesis testing-based method and a confidence interval-based method to answer the question of whether the ratio of means falls into a predetermined interval. For the hypothesis testing-based method, we decomposed the null two-sided hypothesis of the ratio of means into two one-sided hypotheses. With the intersection–union theorem for asymptotic tests, we constructed two asymptotic size- $α$ tests for the original null hypothesis. The method of variance estimation recovery was adopted to develop the confidence interval-based method. Simulation studies showed that the proposed methods can maintain the empirical type I error rate closely at the nominal level and is as powerful as the two one-sided $t$ -test for testing the ratio of means under different settings. The application of the proposed methods was illustrated through six datasets in real-world examples.

Keywords

Equivalence test bioequivalence two one-sided test geometric mean ratio ratio of means

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Equivalence tests for ratio of means in bioequivalence studies under crossover design

Abstract

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