title: Conditional Monte Carlo randomization tests for regression models.
abstract: We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification.
authors.affiliation: Department of Statistics, George Mason University, 4400 University Drive, MS 4A7, Fairfax, VA 22030, U.S.A.
authors.forename: Parwen
authors.initials: P
authors.lastname: Parhat
authors.forename: William F
authors.initials: WF
authors.lastname: Rosenberger
authors.forename: Guoqing
authors.initials: G
authors.lastname: Diao
mesh_terms: D000465:Algorithms; D056808:Biostatistics; D003198:Computer Simulation; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D015233:Models, Statistical; D009010:Monte Carlo Method; D011897:Random Allocation; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012044:Regression Analysis; D018709:Statistics, Nonparametric; D016019:Survival Analysis
keywords: generalized linear mixed models; generalized linear models; linear rank test; longitudinal data; martingale residuals; time-to-event data