Semiparametric additive frailty hazard model for clustered failure time data

Semiparametric additive frailty hazard model for clustered failure time data
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集群故障时间数据的半参数加性脆弱危险模型

DOI:
10.1002/cjs.11647
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发表时间:
2020-10
期刊:
Canadian Journal of Statistics
影响因子:
--
通讯作者:
Yong Zhou
Yong Zhou
中科院分区:
其他
文献类型:
--
作者:
Peng LIU;Shanshan SONG;Yong Zhou

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本文提出了一个灵活的半参数加性脆弱性风险模型下的集群故障时间数据,其中脆弱性假设有一个加性的影响,对风险函数。当不存在脆弱性时,该模型退化为半参数加性风险模型。我们的方法可以同时处理时变和恒定协变量效应。协变量效应的估计不依赖于脆弱性分布。利用局部线性技术估计时变系数,而通过积分我们可以得到常系数估计的n-相合收敛速度。估计量的另一个优点是它具有封闭形式。我们建立了估计量的大样本性质,并在各种情况下进行模拟研究,以证明其性能。所提出的方法被应用到真实的数据进行说明。
This article proposes a flexible semiparametric additive frailty hazard model under clustered failure time data, where frailty is assumed to have an additive effect on the hazard function. When there is no frailty, this model degenerates into a semiparametric additive hazard model. Our method can deal simultaneously with both time‐varying and constant covariate effects. The estimate of the covariate effects does not rely on the frailty distribution. The time‐varying coefficient is estimated by utilizing the local linear technique, while we can obtain a n ‐consistency convergence rate of the constant‐coefficient estimate by integration. Another advantage of the estimator is that it has a closed form. We establish large sample properties of the estimator and conduct simulation studies under various scenarios to demonstrate its performance. The proposed method is applied to real data for illustration.
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发表时间: 1981-06
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