Motivated by a breast cancer research program, this paper is concerned with the joint survivor function of multiple event times when their observations are subject to informative censoring caused by a terminating event. We formulate the correlation of the multiple event times together with the time to the terminating event by an Archimedean copula to account for the informative censoring. Adapting the widely used two-stage procedure under a copula model, we propose an easy-to-implement pseudo-likelihood based procedure for estimating the model parameters. The approach yields a new estimator for the marginal distribution of a single event time with semicompeting-risks data. We conduct both asymptotics and simulation studies to examine the proposed approach in consistency, efficiency, and robustness. Data from the breast cancer program are employed to illustrate this research.

中文翻译：

---

存在信息审查的多个事件时间：通过 copula 进行建模和分析。

受乳腺癌研究计划的启发，本文关注多个事件时间的联合幸存者功能，当他们的观察受到终止事件引起的信息审查时。我们通过阿基米德 copula 将多个事件时间与终止事件的时间一起公式化，以解释信息审查。在 copula 模型下适应广泛使用的两阶段程序，我们提出了一种易于实现的基于伪似然的程序来估计模型参数。该方法为具有半竞争风险数据的单个事件时间的边际分布产生了一个新的估计量。我们进行渐近和模拟研究，以检查所提出的方法的一致性、效率和稳健性。