Ghosh Pulak, Rosner Gary L
Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303-3083, U.S.A.
Stat Med. 2007 Mar 15;26(6):1224-36. doi: 10.1002/sim.2620.
Bioequivalence assessment is an issue of great interest. Development of statistical methods for assessing bioequivalence is an important area of research for statisticians. Bioequivalence is usually determined based on the normal distribution. We relax this assumption and develop a semi-parametric mixed model for bioequivalence data. The proposed method is quite flexible and practically meaningful. Our proposed method is based on a mixture normal distribution and a non-parametric Bayesian approach using a Dirichlet process mixture prior. A numerical example illustrates the use of our procedure.
生物等效性评估是一个备受关注的问题。开发用于评估生物等效性的统计方法是统计学家重要的研究领域。生物等效性通常基于正态分布来确定。我们放宽这一假设,为生物等效性数据开发了一个半参数混合模型。所提出的方法相当灵活且具有实际意义。我们提出的方法基于混合正态分布和使用狄利克雷过程混合先验的非参数贝叶斯方法。一个数值例子说明了我们方法的使用。