Han Seungbong, Andrei Adin-Cristian, Tsui Kam-Wah
Department of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
BCVI Clinical Trials Unit, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Stat Methods Med Res. 2016 Aug;25(4):1718-35. doi: 10.1177/0962280213498325. Epub 2013 Jul 30.
Doubly censored data often arise in medical studies of disease progression involving two related events for which both an originating and a terminating event are interval-censored. Although regression modeling for such doubly censored data may be complicated, we propose a simple semiparametric regression modeling strategy based on jackknife pseudo-observations obtained using nonparametric estimators of the survival function. Inference is carried out via generalized estimating equations. Simulations studies show that the proposed method produces virtually unbiased covariate effect estimates, even for moderate sample sizes. A prostate cancer study example illustrates the practical advantages of the proposed approach.
双重删失数据经常出现在涉及两个相关事件的疾病进展医学研究中，对于这两个事件，起始事件和终止事件均为区间删失。尽管对此类双重删失数据进行回归建模可能很复杂，但我们基于使用生存函数的非参数估计器获得的刀切伪观测值，提出了一种简单的半参数回归建模策略。通过广义估计方程进行推断。模拟研究表明，即使对于中等样本量，所提出的方法也能产生几乎无偏的协变量效应估计值。一个前列腺癌研究实例说明了所提方法的实际优势。
