KMS Of Academy of mathematics and systems sciences, CAS
| Analysis of proportional mean residual life model with latent variables | |
He, Haijin1; Cai, Jingheng2; Song, Xinyuan3,4; Sun, Liuquan5
| |
| 2017-02-01 | |
| Source Publication | STATISTICS IN MEDICINE
 |
| ISSN | 0277-6715 |
| Volume | 36Issue:5Pages:813-826 |
| Abstract | End-stage renal disease (ESRD) is one of the most serious diabetes complications. Numerous studies have been devoted to revealing the risk factors of the onset time of ESRD. In this article, we propose a proportional mean residual life (MRL) model with latent variables to assess the effects of observed and latent risk factors on the MRL function of ESRD in a cohort of Chinese type 2 diabetic patients. The proposed model generalizes the conventional proportional MRL model to accommodate the latent risk factor that cannot be measured by a single observed variable. We employ a factor analysis model to characterize the latent risk factors via multiple observed variables. We develop a borrow-strength estimation procedure, which incorporates the expectation-maximization algorithm and an extended estimating equation approach. The asymptotic properties of the proposed estimators are established. Simulation shows that the performance of the proposed methodology is satisfactory. The application to the study of type 2 diabetes reveals insights into the prevention of ESRD. Copyright (C) 2016 John Wiley & Sons, Ltd. |
| Keyword | borrow-strength estimation extended estimating equations factor analysis latent variables mean residual life function proportional model |
| DOI | 10.1002/sim.7174 |
| Language | 英语 |
| Funding Project | Research Grant Council of the Hong Kong Special Administration Region[14601115] ; Research Grant Council of the Hong Kong Special Administration Region[14305014] ; Chinese University of Hong Kong ; National Natural Science Foundation of China[11471277] ; National Natural Science Foundation of China[11231010] ; National Natural Science Foundation of China[11171330] ; Key Laboratory of RCSDS, CAS[2008DP173182] |
| WOS Research Area | Mathematical & Computational Biology ; Public, Environmental & Occupational Health ; Medical Informatics ; Research & Experimental Medicine ; Mathematics |
| WOS Subject | Mathematical & Computational Biology ; Public, Environmental & Occupational Health ; Medical Informatics ; Medicine, Research & Experimental ; Statistics & Probability |
| WOS ID | WOS:000393303200007 |
| Publisher | WILEY-BLACKWELL |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/24689 |
| Collection | 应用数学研究所 |
| Corresponding Author | Song, Xinyuan |
| Affiliation | 1.Shenzhen Univ, Coll Math & Comp Sci, Shenzhen, Peoples R China 2.Sun Yat Sen Univ, Dept Stat, Guangzhou, Guangdong, Peoples R China 3.Chinese Univ Hong Kong, Shenzhen Res Inst, Hong Kong, Hong Kong, Peoples R China 4.Chinese Univ Hong Kong, Dept Stat, Hong Kong, Hong Kong, Peoples R China 5.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing, Peoples R China |
| Recommended Citation GB/T 7714 | He, Haijin,Cai, Jingheng,Song, Xinyuan,et al. Analysis of proportional mean residual life model with latent variables[J]. STATISTICS IN MEDICINE,2017,36(5):813-826. |
| APA | He, Haijin,Cai, Jingheng,Song, Xinyuan,&Sun, Liuquan.(2017).Analysis of proportional mean residual life model with latent variables.STATISTICS IN MEDICINE,36(5),813-826. |
| MLA | He, Haijin,et al."Analysis of proportional mean residual life model with latent variables".STATISTICS IN MEDICINE 36.5(2017):813-826. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment