title: Tests for inter-subject and total variabilities under crossover designs.
abstract: 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.
authors.affiliation: University of Wisconsin-Madison, Madison, Wisconsin, USA. ylee@statplusinc.com
authors.forename: Yonghee
authors.initials: Y
authors.lastname: Lee
authors.forename: Jun
authors.initials: J
authors.lastname: Shao
authors.forename: Shein-Chung
authors.initials: SC
authors.lastname: Chow
authors.forename: Hansheng
authors.initials: H
authors.lastname: Wang
mesh_terms: D000704:Analysis of Variance; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D018592:Cross-Over Studies; D023381:Endpoint Determination; D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D012107:Research Design; D018401:Sample Size