Finite sample corrections for average equivalence testing
Dec 19, 2023·
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0 min read
Younes Boulaguiem
Julie Quartier
Maria Lapteva
Yogeshvar N. Kalia
Maria-Pia Victoria-Feser
Stéphane Guerrier
Dominique-Laurent Couturier

Abstract
Average (bio)equivalence tests check whether two treatments produce responses that fall within the same acceptable range. The standard two one-sided tests (TOST) method is easy to use but often becomes overly conservative, especially for highly variable drugs, leading to very low statistical power. We introduce the $\alpha$
-TOST, a finite-sample correction of TOST that adjusts its significance level to guarantee a true type-I error rate of $\alpha$
. This correction substantially increases power while preserving validity. The procedure is simple to compute, uniformly more powerful than TOST, and performs better than competing methods. A case study on econazole nitrate skin deposition illustrates its practical advantages.
Type
Publication
Statistics in Medicine