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Bayesian modeling of multivariate average bioequivalence
Author(s) -
Ghosh Pulak,
Gönen Mithat
Publication year - 2007
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3160
Subject(s) - bioequivalence , univariate , multivariate statistics , bayesian probability , econometrics , statistics , inference , bayesian inference , mathematics , computer science , medicine , artificial intelligence , pharmacokinetics
Bioequivalence trials are usually conducted to compare two or more formulations of a drug. Simultaneous assessment of bioequivalence on multiple endpoints is called multivariate bioequivalence. Despite the fact that some tests for multivariate bioequivalence are suggested, current practice usually involves univariate bioequivalence assessments ignoring the correlations between the endpoints such as AUC and C max . In this paper we develop a semiparametric Bayesian test for bioequivalence under multiple endpoints. Specifically, we show how the correlation between the endpoints can be incorporated in the analysis and how this correlation affects the inference. Resulting estimates and posterior probabilities ‘borrow strength’ from one another where the amount and the direction of the strength borrowed are determined by the prior correlations. The method developed is illustrated using a real data set. Copyright © 2007 John Wiley & Sons, Ltd.