A proportional hazards regression model for the subdistribution with right-censored and left-truncated competing risks data.
A proportional hazards regression model for the subdistribution with right-censored and left-truncated competing risks data.
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DOI：
10.1002/sim.4264
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发表时间：
2011-07-20
影响因子：
2
通讯作者：
Fine, Jason
中科院分区：
文献类型：
--
作者：
Zhang, Xu;Zhang, Mei-Jie;Fine, Jason
对于竞争风险失效时间数据，通常需要评估协变量对累积发生概率的影响。Fine和Gray提出了一个比例风险回归模型，直接模拟竞争风险的子分布。他们基于截尾权重的逆概率，开发了右截尾竞争风险数据的估计程序。在生物医学研究中，有时会出现右删失左截断的竞争风险数据。本文研究了右删失左截断数据下竞争风险子分布的比例风险回归模型。我们采用一种新的加权技术来估计模型中的参数。我们推导出了所提出的估计量的大样本性质。为了说明新方法的应用，我们分析了儿童急性白血病的失败时间数据。在这个例子中，接受骨髓移植的儿童的失败时间被截断。
With competing risks failure time data, one often needs to assess the covariate effects on the cumulative incidence probabilities. Fine and Gray proposed a proportional hazards regression model to directly model the subdistribution of a competing risk. They developed the estimating procedure for right-censored competing risks data, based on the inverse probability of censoring weighting. Right-censored and left-truncated competing risks data sometimes occur in biomedical researches. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with right-censored and left-truncated data. We adopt a new weighting technique to estimate the parameters in this model. We have derived the large sample properties of the proposed estimators. To illustrate the application of the new method, we analyze the failure time data for children with acute leukemia. In this example, the failure times for children who had bone marrow transplants were left truncated.
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