Murray S
Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, Michigan 48109-2029, USA.
Biometrics. 2000 Dec;56(4):984-90. doi: 10.1111/j.0006-341x.2000.0984.x.
This research gives methods for nonparametric sequential monitoring of paired censored survival data in the two-sample problem using paired weighted log-rank statistics with adjustments for dependence in survival and censoring outcomes. The joint asymptotic closed-form distribution of these sequentially monitored statistics has a dependent increments structure. Simulations validating operating characteristics of the proposed methods highlight power and size consequences of ignoring even mildly correlated data. A motivating example is presented via the Early Treatment Diabetic Retinopathy Study.
本研究给出了在两样本问题中对配对删失生存数据进行非参数序贯监测的方法，该方法使用配对加权对数秩统计量，并对生存和删失结果中的相关性进行了调整。这些序贯监测统计量的联合渐近封闭形式分布具有相依增量结构。验证所提方法操作特征的模拟突出了忽略即使是轻度相关数据的功效和规模后果。通过早期治疗糖尿病视网膜病变研究给出了一个激励性示例。
