A Bayesian approach to assessing population bioequivalence in a 2 × 2 crossover design

Hyun Sook Oh; Seoung Gon Ko; Man Suk Oh

doi:10.1080/0266476032000117131

A Bayesian approach to assessing population bioequivalence in a 2 × 2 crossover design

Hyun Sook Oh, Seoung Gon Ko, Man Suk Oh

Department of Statistics

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5 Scopus citations

Abstract

A Bayesian testing procedure is proposed for assessment of the bioequivalence in both mean and variance, which ensures population bioequivalence under the normality assumption. We derive the joint posterior distribution of the means and variances in a standard 2× 2 crossover experimental design and propose a Bayesian testing procedure for bioequivalence based on a Markov chain Monte Carlo method. The proposed method is applied to a real data set.

Original language	English
Pages (from-to)	881-891
Number of pages	11
Journal	Journal of Applied Statistics
Volume	30
Issue number	8
DOIs	https://doi.org/10.1080/0266476032000117131
State	Published - Oct 2003

Bibliographical note

Funding Information:
This work was supported by grant No. R04-2001-000-0046-0 from the Korea Science & Engineering Foundation.

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10.1080/0266476032000117131

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abstract = "A Bayesian testing procedure is proposed for assessment of the bioequivalence in both mean and variance, which ensures population bioequivalence under the normality assumption. We derive the joint posterior distribution of the means and variances in a standard 2× 2 crossover experimental design and propose a Bayesian testing procedure for bioequivalence based on a Markov chain Monte Carlo method. The proposed method is applied to a real data set.",

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A Bayesian approach to assessing population bioequivalence in a 2 × 2 crossover design

Abstract

Bibliographical note

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