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Estimation of the joint survival function for successive duration times

机译:连续持续时间的关节生存功能估计

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In incident cohort studies, survival data often include subjects who have experienced an initiate event but have not experienced a subsequent event at the calendar time of recruitment. During the follow-up periods, subjects may undergo a series of successive events. Since the second/third duration process becomes observable only if the first/second event has occurred, the data are subject to left-truncation and dependent censoring. In this article, using the inverse-probability-weighted (IPW) approach, we propose nonparametric estimators for the estimation of the joint survival function of three successive duration times. The asymptotic properties of the proposed estimators are established. The simple bootstrap methods are used to estimate standard deviations and construct interval estimators. A simulation study is conducted to investigate the finite sample properties of the proposed estimators.
机译:在事件队列研究中,生存数据通常包括在招募期间经历过初始事件但未经历过后续事件的受试者。在随访期间,受试者可能经历一系列连续事件。由于仅在发生第一事件/第二事件时第二/第三持续时间过程才可观察到,因此数据将进行左截断和相关检查。在本文中,我们使用逆概率加权(IPW)方法,提出了三个连续持续时间的联合生存函数的非参数估计量。提出了估计量的渐近性质。简单的自举方法用于估计标准偏差并构造间隔估计器。进行了仿真研究,以研究所提出估计量的有限样本性质。

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