title: Inference for blocked randomization under a selection bias model.
abstract: We provide an asymptotic test to analyze randomized clinical trials that may be subject to selection bias. For normally distributed responses, and under permuted block randomization, we derive a likelihood ratio test of the treatment effect under a selection bias model. A likelihood ratio test of the presence of selection bias arises from the same formulation. We prove that the test is asymptotically chi-square on one degree of freedom. These results correlate well with the likelihood ratio test of Ivanova et al. (2005, Statistics in Medicine 24, 1537-1546) for binary responses, for which they established by simulation that the asymptotic distribution is chi-square. Simulations also show that the test is robust to departures from normality and under another randomization procedure. We illustrate the test by reanalyzing a clinical trial on retinal detachment.
authors.affiliation: Department of Medical Statistics, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany.
authors.forename: Lieven N
authors.initials: LN
authors.lastname: Kennes
authors.affiliation: Department of Medical Statistics, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany.|Department of Statistics, George Mason University, 4400 University Drive, MS 4A7, Fairfax, Virginia 22030, U.S.A.
authors.forename: William F
authors.initials: WF
authors.lastname: Rosenberger
authors.affiliation: Department of Medical Statistics, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany.
authors.forename: Ralf-Dieter
authors.initials: RD
authors.lastname: Hilgers
mesh_terms: D001699:Biometry / Q000379:methods; D016009:Chi-Square Distribution; D003198:Computer Simulation; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012163:Retinal Detachment / Q000601:surgery; D012591:Scleral Buckling; D015983:Selection Bias; D014821:Vitrectomy
keywords: Confidence intervals; Likelihood ratio test; Permuted block design; Restricted randomization