A mass redistribution algorithm for right-censored and left-truncated time to event data
A mass redistribution algorithm for right-censored and left-truncated time to event data
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DOI：
10.1016/j.jspi.2009.03.007
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发表时间：
2009-09-01
影响因子：
0.9
通讯作者：
Fine, Jason P.
中科院分区：
文献类型：
--
作者：
Zhang, Xu;Zhang, Mei-Jie;Fine, Jason P.
失败时间通常是右删减和左截断的。本文给出了右删失和/或左截断失效时间数据的质量重分布算法。我们证明了该算法给出了生存概率的Kaplan-Meier估计。研究了该算法在竞争风险数据的次分布风险建模中的一个应用。通过对次分布风险进行建模，给出了累积关联函数的乘积极限估计。我们通过归纳法证明了这个乘积极限估计等同于Aalen-Johansen[1978]的左截断形式。基于删失观测的非齐次马氏链的经验转移矩阵。斯堪的纳维亚统计杂志5,141-150]累积关联函数的估计器。爱思唯尔出版公司
Failure times are often right censored and left truncated. In this paper we give a mass redistribution algorithm for right-censored and/or left-truncated failure time data. We show that this algorithm yields the Kaplan-Meier estimator of the survival probability. One application of this algorithm in modeling the subdistribution hazard for competing risks data is studied. We give a product-limit estimator of the Cumulative incidence function via modeling the subdistribution hazard. We show by induction that this product-limit estimator is identical to the left-truncated version of Aalen-Johansen [1978. An empirical transition matrix for nonhomogeneous Markov chains based on censored observations. Scandinavian Journal of Statistics 5, 141-150] estimator for the cumulative incidence function. Published by Elsevier B.V