aclassoftransformationratemodelsforrecurrenteventdata

	aclassoftransformationratemodelsforrecurrenteventdata
	Zhang Hu 2; Yang Qinglong 2; Qu Lianqiang 1
刊名	sciencechinamathematics
	2016
卷号	59 期号:11 页码:2227
ISSN号	1674-7283
英文摘要	Recurrent 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.
语种	英语
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/45783]
专题	中国科学院数学与系统科学研究院
作者单位	1.中国科学院数学与系统科学研究院 2.中南财经政法大学
推荐引用方式 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.