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Inference of bioequivalence for log‐normal distributed data with unspecified variances
Author(s) -
Xu Siyan,
Hua Steven Y.,
Menton Ronald,
Barker Kerry,
Me Sandeep,
D'Agostino Ralph B.
Publication year - 2014
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.6081
Subject(s) - bioequivalence , statistics , mathematics , inference , statistic , bayesian probability , equivalence (formal languages) , likelihood function , bayesian inference , econometrics , computer science , maximum likelihood , medicine , pharmacokinetics , artificial intelligence , discrete mathematics
Two drugs are bioequivalent if the ratio of a pharmacokinetic (PK) parameter of two products falls within equivalence margins. The distribution of PK parameters is often assumed to be log‐normal, therefore bioequivalence (BE) is usually assessed on the difference of logarithmically transformed PK parameters ( δ ). In the presence of unspecified variances, test procedures such as two one‐sided tests (TOST) use sample estimates for those variances; Bayesian models integrate them out in the posterior distribution. These methods limit our knowledge on the extent that inference about BE is affected by the variability of PK parameters. In this paper, we propose a likelihood approach that retains the unspecified variances in the model and partitions the entire likelihood function into two components: F ‐statistic function for variances and t ‐statistic function for δ . Demonstrated with published real‐life data, the proposed method not only produces results that are same as TOST and comparable with Bayesian method but also helps identify ranges of variances, which could make the determination of BE more achievable. Our findings manifest the advantages of the proposed method in making inference about the extent that BE is affected by the unspecified variances, which cannot be accomplished either by TOST or Bayesian method. Copyright © 2014 John Wiley & Sons, Ltd.