Joint modeling of generalized scale-change models for recurrent event and failure time data.

IF 1.2 3区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Lifetime Data Analysis Pub Date : 2023-01-01 DOI:10.1007/s10985-022-09573-5
Xiaoyu Wang, Liuquan Sun
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Abstract

Recurrent event and failure time data arise frequently in many clinical and observational studies. In this article, we propose a joint modeling of generalized scale-change models for the recurrent event process and the failure time, and allow the two processes to be correlated through a shared frailty. The proposed joint model is flexible in that it requires neither the Poisson assumption for the recurrent event process nor a parametric assumption on the frailty distribution. Estimating equation approaches are developed for parameter estimation, and the asymptotic properties of the resulting estimators are established. Simulation studies are conducted to evaluate the finite sample performances of the proposed method. An application to a medical cost study of chronic heart failure patients is provided.

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重复事件与失效时间数据的广义尺度变化模型联合建模。
在许多临床和观察性研究中经常出现复发事件和失效时间数据。在本文中,我们提出了一种针对重复事件过程和失效时间的广义尺度变化模型的联合建模,并允许这两个过程通过一个共享的脆弱性相关联。所提出的联合模型既不需要泊松假设,也不需要对脆弱性分布进行参数假设,因而具有灵活性。提出了参数估计的估计方程方法,并给出了估计量的渐近性质。通过仿真研究对该方法的有限样本性能进行了评价。提供了一种在慢性心力衰竭患者医疗费用研究中的应用。
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来源期刊
Lifetime Data Analysis
Lifetime Data Analysis 数学-数学跨学科应用
CiteScore
2.30
自引率
7.70%
发文量
43
审稿时长
3 months
期刊介绍: The objective of Lifetime Data Analysis is to advance and promote statistical science in the various applied fields that deal with lifetime data, including: Actuarial Science – Economics – Engineering Sciences – Environmental Sciences – Management Science – Medicine – Operations Research – Public Health – Social and Behavioral Sciences.
期刊最新文献
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