An additive-multiplicative rates model for multivariate recurrent events with event categories missing at random

作     者：YE Peng SUN LiuQuan ZHAO XingQiu XU Wei 

作者机构：Institute of Applied Mathematics Academy of Mathematics and Systems ScienceChinese Academy of Sciences Department of Applied Mathematics The Hong Kong Polytechnic University Shenzhen Research InstituteThe Hong Kong Polytechnic University Dalla Lana School of Public Health University of Toronto 

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

年 卷 期：2015年第58卷第6期

页      面：1163-1178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] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：supported by National Natural Science Foundation of China(Grant Nos.11231010,11171330 and 11371299) Key Laboratory of Random Complex Structures and Data Science,Chinese Academy of Sciences(Grant No.2008DP173182) Beijing Center for Mathematics and Information Interdisciplinary Sciences,the Research Grant Council of Hong Kong(Grant Nos.504011 and 503513) The Hong Kong Polytechnic University 

主　　题：additive-multiplicative rates model missing data multivariate recurrent events semiparametricmodel weighted estimating equation 

摘      要：Multivariate recurrent event data arises when study subjects may experience more than one type of recurrent events. In some situations, however, although event times are always observed, event categories may be partially missing. In this paper, an additive-multiplicative rates model is proposed for the analysis of multivariate recurrent event data when event categories are missing at random. A weighted estimating equations approach is developed for parameter estimation, and the resulting estimators are shown to be consistent and asymptotically normal. In addition, a model-checking technique is presented to assess the adequacy of the model. Simulation studies are conducted to evaluate the finite sample behavior of the proposed estimators, and an application to a platelet transfusion reaction study is provided.