A class of weighted estimating equations for additive hazards models with covariates missing at random

作     者：Jin Jin Peng Ye Liuquan Sun Jin Jin;Peng Ye;Liuquan Sun

作者机构：Institute of Applied MathematicsAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical SciencesUniversity of Chinese Academy of SciencesBeijing 100049China School of StatisticsUniversity of International Business and EconomicsBeijing 100029China 

出 版 物：《Science China Mathematics》 (中国科学：数学（英文版）)

年 卷 期：2022年第65卷第3期

页      面：583-602页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 1004[医学-公共卫生与预防医学(可授医学、理学学位)] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 100401[医学-流行病与卫生统计学] 070103[理学-概率论与数理统计] 0701[理学-数学] 10[医学] 

基　　金：supported by National Natural Science Foundation of China(Grant Nos.11771431,11690015,11926341,11601080 and 11671275) Key Laboratory of Random Complex Structures and Data Science,Chinese Academy of Sciences(Grant No.2008DP173182) the Fundamental Research Funds for the Central Universities in University of International Business and Economics(Grant No.CXTD10-09) 

主　　题：additive hazards model censored data kernel smoothing missing at random weighted estimating equation 

摘      要：Missing covariate data arise frequently in biomedical *** this article,we propose a class of weighted estimating equations for the additive hazards regression model when some of the covariates are missing at ***-specific and subject-specific weights are incorporated into the formulation of weighted estimating *** results are established for estimating selection probabilities that cover both parametric and non-parametric modelling *** resulting estimators have closed forms and are shown to be consistent and asymptotically *** studies indicate that the proposed estimators perform well for practical *** application to a mouse leukemia study is illustrated.