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具有非参数协变量函数的复发事件和终末事件的联合模型。

A joint model of recurrent events and a terminal event with a nonparametric covariate function.

机构信息

Division of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, USA.

出版信息

Stat Med. 2011 Sep 30;30(22):2683-95. doi: 10.1002/sim.4297. Epub 2011 Jul 12.

Abstract

We extend the shared frailty model of recurrent events and a dependent terminal event to allow for a nonparametric covariate function. We include a Gaussian random effect (frailty) in the intensity functions of both the recurrent and terminal events to capture correlation between the two processes. We employ the penalized cubic spline method to describe the nonparametric covariate function in the recurrent events model. We use Laplace approximation to evaluate the marginal penalized partial likelihood without a closed form. We also propose the variance estimates for regression coefficients. Numerical analysis results show that the proposed estimates perform well for both the nonparametric and parametric components. We apply this method to analyze the hospitalization rate of patients with heart failure in the presence of death.

摘要

我们将复发事件和相关终末事件的共享脆弱性模型扩展到允许非参数协变量函数。我们在复发事件和终末事件的强度函数中包含一个高斯随机效应(脆弱性),以捕捉两个过程之间的相关性。我们使用惩罚三次样条方法来描述复发事件模型中的非参数协变量函数。我们使用拉普拉斯逼近来评估没有闭式解的边缘惩罚部分似然。我们还提出了回归系数的方差估计。数值分析结果表明,所提出的估计对于非参数和参数分量都表现良好。我们将该方法应用于分析心力衰竭患者在死亡存在的情况下的住院率。

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