Analyzing the general biased data by additive risk model

查看全文 作　　者：LI [1]YanFeng;MA [2]HuiJuan;WANG [1]DeHui;ZHOU [3,4]Yong

机构地区：[1]College of Mathematics, Jilin University;[2]Department of Biostatistics and Bioinformatics, Emory University;[3]School of Statistics and Management, Shanghai University of Finance and Economics;[4]Academy of Mathematics and Systems Science, Chinese Academy of Sciences

出　　处：《Science China Mathematics》索引2017年第60卷第4期,共16页

基　　金：supported by National Institutes of Health of USA (Grant No. R01 HL113548);National Natural Science Foundation of China (Grant Nos. 11271155, 11371168, J1310022, 11571138, 11501241 and 71271128);Science and Technology Research Program of Education Department in Jilin Province for the 12th Five-Year Plan (Grant No. 440020031139);Jilin Province Natural Science Foundation (Grant Nos. 20130101066JC, 20130522102JH and 20150520053JH);the State Key Program of National Natural Science Foundation of China (Grant No. 71331006);National Center for Mathematics and Interdisciplinary Sciences and Shanghai University of Finance and Economics through Project 211 Phase IV and Shanghai Leading Academic Discipline Project A 摘　　要：This paper proposes a unified semiparametric method for the additive risk model under general biased sampling. By using the estimating equation approach, we propose both estimators of the regression parameters and nonparametric function. An advantage is that our approach is still suitable for the lengthbiased data even without the information of the truncation variable. Meanwhile, large sample properties of the proposed estimators are established, including consistency and asymptotic normality. In addition, the finite sample behavior of the proposed methods and the analysis of three groups of real data are given. 关键词：风险模型偏差数模型分析加性大样本性质渐近正态性参数方法参数函数

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Analyzing the general biased data by additive risk model

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