Semiparametric Bayesian Modeling of Multivariate Average Bioequivalence
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Abstract:
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 Cmax. 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 direction of the strength borrowed are determined by the prior correlations. The method developed is illustrated using a real data set.
Subject Area:
Clinical Trials, General Biostatistics, Multivariate Analysis, Statistical Models
Suggested Citation:
Pulak Ghosh Dr. and Mithat Gonen, "Semiparametric Bayesian Modeling of Multivariate Average Bioequivalence" (May 2006). Memorial Sloan-Kettering Cancer Center Department of Epidemiology and Biostatistics Working Paper Series. Working Paper 8.
http://www.bepress.com/mskccbiostat/paper8