A Semiparametric Additive-multiplicative Rates Model for the Weighted Composite Endpoint of Recurrent and Terminal Events  

作　　者：Yi DENG Qiang XIONG Shu Wei LI 

机构地区：[1]School of Economics and Statistics,Guangzhou University,Guangzhou 510006,P.R.China

出　　处：《Acta Mathematica Sinica,English Series》2024年第4期985-999,共15页数学学报（英文版）

基　　金：the National Natural Science Foundation of China(Grant Nos.11771431,11690015,11926341,11731015,11901128 and 11601097);Key Laboratory of RCSDS,CAS(Grant No.2008DP173182);Natural Science Foundation of Guangdong Province of China(Grant Nos.2018A030310068,2021A1515010044);University Innovation Team Project of Guangdong Province(Grant No.2020WCXTD018);Science and Technology Program of Guangzhou,China(Grant Nos.202102020368,202102010512)。

摘　　要：Recurrent event data are commonly encountered in many scientific fields,including biomedical studies,clinical trials and epidemiological surveys,and many statistical methods have been proposed for their analysis.In this paper,we consider to use a weighted composite endpoint of recurrent and terminal events,which is weighted by the severity of each event,to assess the overall effects of covariates on the two types of events.A flexible additive-multiplicative model incorporating both multiplicative and additive effects on the rate function is proposed to analyze such weighted composite event process,and more importantly,the dependence structure among the recurrent and terminal events is left unspecified.For the estimation,we construct the unbiased estimating equations by virtue of the inverse probability weighting technique,and the resulting estimators are shown to be consistent and asymptotically normal under some mild regularity conditions.We evaluate the finite-sample performance of the proposed method via simulation studies and apply the proposed method to a set of real data arising from a bladder cancer study.

关 键 词：Additive-multiplicative rates model estimating equation recurrent events terminal event weighted composite endpoint 

分 类 号：O212.1[理学—概率论与数理统计]