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aclassoftransformationratemodelsforrecurrenteventdata
Zhang Hu1; Yang Qinglong1; Qu Lianqiang2
2016
Source Publicationsciencechinamathematics
ISSN1674-7283
Volume59Issue:11Pages:2227
AbstractRecurrent event data frequently occur in longitudinal studies, and it is often of interest to estimate the effects of covariates on the recurrent event rate. This paper considers a class of semiparametric transformation rate models for recurrent event data, which uses an additive Aalen model as its covariate dependent baseline. The new models are flexible in that they allow for both additive and multiplicative covariate effects, and some covariate effects are allowed to be nonparametric and time-varying. An estimating procedure is proposed for parameter estimation, and the resulting estimators are shown to be consistent and asymptotically normal. Simulation studies and a real data analysis demonstrate that the proposed method performs well and is appropriate for practical use.
Language英语
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/45784
Collection中国科学院数学与系统科学研究院
Affiliation1.中南财经政法大学
2.中国科学院数学与系统科学研究院
Recommended Citation
GB/T 7714
Zhang Hu,Yang Qinglong,Qu Lianqiang. aclassoftransformationratemodelsforrecurrenteventdata[J]. sciencechinamathematics,2016,59(11):2227.
APA Zhang Hu,Yang Qinglong,&Qu Lianqiang.(2016).aclassoftransformationratemodelsforrecurrenteventdata.sciencechinamathematics,59(11),2227.
MLA Zhang Hu,et al."aclassoftransformationratemodelsforrecurrenteventdata".sciencechinamathematics 59.11(2016):2227.
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