论文标题
Pocock和Simon协变量随机化的研究中的测试有效性
Validity of tests for time-to-event endpoints in studies with the Pocock and Simon covariate-adaptive randomization
论文作者
论文摘要
在存在预后的协变量的情况下，关于治疗效果与事件时间终点的推论主要是通过分层对数秩检验或基于COX比例危害模型的分数测试进行的。从理论上讲，在他们的开创性工作中，Ye和Shao（2020）证明了该模型被弄清楚时，在分层随机化的试验中，稳健的得分测试（Wei和Lin，1989）以及未分层的对数秩检验是保守的。但是，除了通过模拟之外，还没有为Pocock和Simon协变量的自适应分配而建立这一事实。在本文中，我们将YE和SHAO的结果扩展到更一般的随机化过程类别，部分在理论上部分通过模拟显示了Pocock和Simon协变量自适应分配属于该类别。我们还通过描述所有层次相等流行的情况，通过描述渐近相关矩阵的渐进性内部失衡的相关结构与最小化的搜索相关结构。我们扩展了Ye和Shao提出的强大测试，以分层随机化以最小化并检查其性能槽模拟。
In the presence of prognostic covariates, inference about the treatment effect with time-to-event endpoints is mostly conducted via the stratified log-rank test or the score test based on the Cox proportional hazards model. In their ground-breaking work Ye and Shao (2020) have demonstrated theoretically that when the model is misspecified, the robust score test (Wei and Lin, 1989) as well as the unstratified log-rank test are conservative in trials with stratified randomization. This fact, however, was not established for the Pocock and Simon covariate-adaptive allocation other than through simulations. In this paper, we expand the results of Ye and Shao to a more general class of randomization procedures and show, in part theoretically, in part through simulations, that the Pocock and Simon covariate-adaptive allocation belongs to this class. We also advance the search for the correlation structure of the normalized within-stratum imbalances with minimization by describing the asymptotic correlation matrix for the case of equal prevalence of all strata. We expand the robust tests proposed by Ye and Shao for stratified randomization to minimization and examine their performance trough simulations.
