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Dynamic semiparametric transformation models for recurrent event data with a terminal event
Jin, Jin1; Song, Xinyuan2; Sun, Liuquan3,4
2022-09-19
Source PublicationSTATISTICS IN MEDICINE
ISSN0277-6715
Pages16
AbstractRecurrent event data with a terminal event commonly arise in many longitudinal follow-up studies. This article proposes a class of dynamic semiparametric transformation models for the marginal mean functions of the recurrent events with a terminal event, where some covariate effects may be time-varying. An estimation procedure is developed for the model parameters, and the asymptotic properties of the resulting estimators are established. In addition, relevant significance tests are suggested for examining whether or not covariate effects vary with time, and a model checking procedure is presented for assessing the adequacy of the proposed models. The finite sample performance of the proposed estimators is examined through simulation studies, and an application to a medical cost study of chronic heart failure patients is provided.
Keyworddynamic regression marginal modeling recurrent events terminal event time-varying coefficients transformation models
DOI10.1002/sim.9577
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[12171463] ; National Natural Science Foundation of China[11771431] ; National Natural Science Foundation of China[11690015] ; Research Grant Council of the Hong Kong Special Administrative Region[14302220]
WOS Research AreaMathematical & Computational Biology ; Public, Environmental & Occupational Health ; Medical Informatics ; Research & Experimental Medicine ; Mathematics
WOS SubjectMathematical & Computational Biology ; Public, Environmental & Occupational Health ; Medical Informatics ; Medicine, Research & Experimental ; Statistics & Probability
WOS IDWOS:000857871700001
PublisherWILEY
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/61008
Collection应用数学研究所
Corresponding AuthorSun, Liuquan
Affiliation1.Univ Sci & Technol Beijing, Sch Math & Phys, Beijing, Peoples R China
2.Chinese Univ Hong Kong, Dept Stat, Hong Kong, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing, Peoples R China
4.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Jin, Jin,Song, Xinyuan,Sun, Liuquan. Dynamic semiparametric transformation models for recurrent event data with a terminal event[J]. STATISTICS IN MEDICINE,2022:16.
APA Jin, Jin,Song, Xinyuan,&Sun, Liuquan.(2022).Dynamic semiparametric transformation models for recurrent event data with a terminal event.STATISTICS IN MEDICINE,16.
MLA Jin, Jin,et al."Dynamic semiparametric transformation models for recurrent event data with a terminal event".STATISTICS IN MEDICINE (2022):16.
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