Lee Yonghee, Shao Jun, Chow Shein-Chung, Wang Hansheng
University of Wisconsin-Madison, Madison, Wisconsin, USA.
J Biopharm Stat. 2002 Nov;12(4):503-34. doi: 10.1081/BIP-120016233.
In this paper, we consider statistical tests for inter-subject and total variabilities between treatments under crossover designs. Since estimators of variance components for inter-subject variability and total variability in crossover design are not independent, the usual F-test cannot be applied. Alternatively, we propose a test based on the concept of the extension of the modified large sample method to compare inter-subject variability and total variability between treatments under a 2 x 2 m replicated crossover design. An asymptotic power of the proposed test is derived. A sensitivity analysis is performed based on the asymptotic power to determine how the power changes with respect to various parameters such as inter-subject correlation and intra-class correlation. Also the two methods for sample size calculation for testing total variability under 2 x 4 crossover design are discussed. The method based on the Fisher-Cornish inversion shows better performance than the method based on the normal approximation. Several simulation studies were conducted to investigate the finite sample performance of the proposed test. Our simulation results show that the proposed test can control type I error satisfactorily.
在本文中,我们考虑交叉设计下处理间受试者间变异性和总变异性的统计检验。由于交叉设计中受试者间变异性和总变异性的方差分量估计量不独立,因此通常的F检验无法应用。取而代之的是,我们提出了一种基于将修正的大样本方法扩展的概念的检验,以比较2×2 m重复交叉设计下处理间的受试者间变异性和总变异性。推导了所提出检验的渐近功效。基于渐近功效进行敏感性分析,以确定功效如何随受试者间相关性和组内相关性等各种参数变化。此外,还讨论了2×4交叉设计下检验总变异性的两种样本量计算方法。基于Fisher-Cornish反演的方法比基于正态近似的方法表现更好。进行了几项模拟研究以调查所提出检验的有限样本性能。我们的模拟结果表明,所提出的检验能够令人满意地控制I型错误。