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Controlling type I error in the reference‐scaled bioequivalence evaluation of highly variable drugs
Author(s) -
Ocaña Jordi,
Muñoz Joel
Publication year - 2019
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.1950
Subject(s) - bioequivalence , type i and type ii errors , statistics , variable (mathematics) , mathematics , sample size determination , statistical power , range (aeronautics) , nominal level , computer science , econometrics , confidence interval , medicine , mathematical analysis , pharmacology , bioavailability , materials science , composite material
Reference‐scaled average bioequivalence (RSABE) approaches for highly variable drugs are based on linearly scaling the bioequivalence limits according to the reference formulation within‐subject variability. RSABE methods have type I error control problems around the value where the limits change from constant to scaled. In all these methods, the probability of type I error has only one absolute maximum at this switching variability value. This allows adjusting the significance level to obtain statistically correct procedures (that is, those in which the probability of type I error remains below the nominal significance level), at the expense of some potential power loss. In this paper, we explore adjustments to the EMA and FDA regulatory RSABE approaches, and to a possible improvement of the original EMA method, designated as HoweEMA. The resulting adjusted methods are completely correct with respect to type I error probability. The power loss is generally small and tends to become irrelevant for moderately large (affordable in real studies) sample sizes.