Liu J P, Weng C S
Berlex Laboratories, Inc., Wayne, NJ 07470.
Stat Med. 1991 Sep;10(9):1375-89. doi: 10.1002/sim.4780100906.
This paper considers the problem of detecting outlying data in bioavailability/bioequivalence studies. We define outlying subjects as those whose responses in bioavailability to all formulations differ from the rest of the subjects. We also define an outlying observation as the response in bioavailability of a subject to a particular formulation which is grossly different from the average bioavailability of that formulation calculated from all subjects. We propose two test procedures. The first, based on two-sample Hotelling T2, is to detect possible outlying subjects. The second, based on residuals from formulation means, is to identify possible outlying observations within subjects. Both procedures take into account the covariance structure of the responses to formulations, dependence of test statistics, and multiplicity of test procedures. We apply the Monte Carlo or bootstrap simulation to evaluate the sampling distributions of test statistics. An example from a 3-way crossover bioequivalence study illustrates the two procedures.
本文探讨生物利用度/生物等效性研究中的异常数据检测问题。我们将异常受试者定义为那些在生物利用度方面对所有制剂的反应与其他受试者不同的人。我们还将异常观测定义为受试者对特定制剂的生物利用度反应,该反应与根据所有受试者计算出的该制剂平均生物利用度有显著差异。我们提出了两种检验程序。第一种基于双样本霍特林T2检验,用于检测可能的异常受试者。第二种基于制剂均值的残差,用于识别受试者内可能的异常观测。两种程序都考虑了对制剂反应的协方差结构、检验统计量的依赖性以及检验程序的多重性。我们应用蒙特卡罗或自助模拟来评估检验统计量的抽样分布。一个三路交叉生物等效性研究的例子说明了这两种程序。