论文标题
在最小化方法下，协变量随机化的层不平衡的一致协方差估计
Consistent Covariance estimation for stratum imbalances under minimization method for covariate-adaptive randomization
论文作者
论文摘要
Pocock和Simon的最小化方法是临床试验中协变量自适应随机化的流行方法。在最小化方法下收集的数据的有效统计推论需要了解层内不平衡的限制协方差矩阵，其存在直到最近才建立。在这项工作中，我们为此限制提出了一个基于引导的估计器，并尤其是Le Cam的第三次引理，尤其是建立了其一致性。作为应用程序，我们在模拟研究中考虑了对现有的鲁棒测试的调整，该测试对拟议估计量的生存数据进行了生存数据的治疗效果。它表明调整后的测试达到了接近名义水平的尺寸，并且与其他设计不同，在最小化方法下，无需调整的稳健测试可能会有渐近的大小通胀问题。
Pocock and Simon's minimization method is a popular approach for covariate-adaptive randomization in clinical trials. Valid statistical inference with data collected under the minimization method requires the knowledge of the limiting covariance matrix of within-stratum imbalances, whose existence is only recently established. In this work, we propose a bootstrap-based estimator for this limit and establish its consistency, in particular, by Le Cam's third lemma. As an application, we consider in simulation studies adjustments to existing robust tests for treatment effects with survival data by the proposed estimator. It shows that the adjusted tests achieve a size close to the nominal level, and unlike other designs, the robust tests without adjustment may have an asymptotic size inflation issue under the minimization method.
