title: Weighted re-randomization tests for minimization with unbalanced allocation.
abstract: Re-randomization test has been considered as a robust alternative to the traditional population model-based methods for analyzing randomized clinical trials. This is especially so when the clinical trials are randomized according to minimization, which is a popular covariate-adaptive randomization method for ensuring balance among prognostic factors. Among various re-randomization tests, fixed-entry-order re-randomization is advocated as an effective strategy when a temporal trend is suspected. Yet when the minimization is applied to trials with unequal allocation, fixed-entry-order re-randomization test is biased and thus compromised in power. We find that the bias is due to non-uniform re-allocation probabilities incurred by the re-randomization in this case. We therefore propose a weighted fixed-entry-order re-randomization test to overcome the bias. The performance of the new test was investigated in simulation studies that mimic the settings of a real clinical trial. The weighted re-randomization test was found to work well in the scenarios investigated including the presence of a strong temporal trend.
authors.affiliation: Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN 46285, USA. han_baoguang@lilly.com
authors.forename: Baoguang
authors.initials: B
authors.lastname: Han
authors.forename: Menggang
authors.initials: M
authors.lastname: Yu
authors.forename: Damian
authors.initials: D
authors.lastname: McEntegart
mesh_terms: D015982:Bias; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D011336:Probability; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012107:Research Design
keywords: covariate-adaptive randomization; minimization; re-randomization test; temporal trend