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A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup

文献类型：期刊论文

作者Sun, Liuquan3,4; Li, Shuwei4; Wang, Lianming2; Song, Xinyuan1
刊名STATISTICAL METHODS IN MEDICAL RESEARCH
出版日期2021-07-01
页码14
关键词Expectation-maximization algorithm maximum likelihood estimation mixture cure model partly interval-censored data proportional hazards model
ISSN号0962-2802
DOI10.1177/09622802211023985
英文摘要Failure time data with a cured subgroup are frequently confronted in various scientific fields and many methods have been proposed for their analysis under right or interval censoring. However, a cure model approach does not seem to exist in the analysis of partly interval-censored data, which consist of both exactly observed and interval-censored observations on the failure time of interest. In this article, we propose a two-component mixture cure model approach for analyzing such type of data. We employ a logistic model to describe the cured probability and a proportional hazards model to model the latent failure time distribution for uncured subjects. We consider maximum likelihood estimation and develop a new expectation-maximization algorithm for its implementation. The asymptotic properties of the resulting estimators are established and the finite sample performance of the proposed method is examined through simulation studies. An application to a set of real data on childhood mortality in Nigeria is provided.
资助项目National Natural Science Foundation of China[11771431] ; National Natural Science Foundation of China[11690015] ; National Natural Science Foundation of China[11901128] ; Key Laboratory of RCSDS, CAS[2008DP173182] ; Natural Science Foundation of Guangdong Province of China[2021A1515010044] ; Science and Technology Program of Guangzhou of China[202102010512] ; Research Grant Council of the Hong Kong Special Administration Region[GRF 14301918] ; Research Grant Council of the Hong Kong Special Administration Region[14302519] ; National Institutes of Health[R01CA218578]
WOS研究方向Health Care Sciences & Services ; Mathematical & Computational Biology ; Medical Informatics ; Mathematics
语种英语
WOS记录号WOS:000680119400001
出版者SAGE PUBLICATIONS LTD
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/59026]  
专题应用数学研究所
通讯作者Li, Shuwei
作者单位1.Chinese Univ Hong Kong, Dept Stat, Hong Kong, Peoples R China
2.Univ South Carolina, Dept Stat, Columbia, SC USA
3.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing, Peoples R China
4.Guangzhou Univ, Sch Econ & Stat, Guangzhou 510006, Peoples R China
推荐引用方式
GB/T 7714		 Sun, Liuquan,Li, Shuwei,Wang, Lianming,et al. A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup[J]. STATISTICAL METHODS IN MEDICAL RESEARCH,2021:14.
APA Sun, Liuquan,Li, Shuwei,Wang, Lianming,&Song, Xinyuan.(2021).A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup.STATISTICAL METHODS IN MEDICAL RESEARCH,14.
MLA Sun, Liuquan,et al."A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup".STATISTICAL METHODS IN MEDICAL RESEARCH (2021):14.

入库方式： OAI收割

来源：数学与系统科学研究院

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