A Bayesian proportional hazards mixture cure model for interval-censored data.

IF 1.2 3区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Lifetime Data Analysis Pub Date : 2024-04-01 Epub Date: 2023-11-28 DOI:10.1007/s10985-023-09613-8
Chun Pan, Bo Cai, Xuemei Sui
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引用次数: 0

Abstract

The proportional hazards mixture cure model is a popular analysis method for survival data where a subgroup of patients are cured. When the data are interval-censored, the estimation of this model is challenging due to its complex data structure. In this article, we propose a computationally efficient semiparametric Bayesian approach, facilitated by spline approximation and Poisson data augmentation, for model estimation and inference with interval-censored data and a cure rate. The spline approximation and Poisson data augmentation greatly simplify the MCMC algorithm and enhance the convergence of the MCMC chains. The empirical properties of the proposed method are examined through extensive simulation studies and also compared with the R package "GORCure". The use of the proposed method is illustrated through analyzing a data set from the Aerobics Center Longitudinal Study.

Abstract Image

区间截尾数据的贝叶斯比例风险混合校正模型。
比例风险混合治愈模型是一种流行的生存数据分析方法,其中一个亚组患者被治愈。当数据是区间截尾时,由于其复杂的数据结构,该模型的估计具有挑战性。在本文中,我们提出了一种计算效率高的半参数贝叶斯方法,通过样条近似和泊松数据增强来促进模型估计和推理,并且具有区间截尾数据和修复率。样条逼近和泊松数据扩充极大地简化了MCMC算法,提高了MCMC链的收敛性。通过广泛的模拟研究检验了所提出方法的经验性质,并与R包“GORCure”进行了比较。通过对健美操中心纵向研究数据集的分析,说明了该方法的应用。
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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.
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