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

Science China Mathematics 2015年第6期58卷 1163-1178页

作者： YE Peng SUN LiuQuan ZHAO XingQiu XU Wei Institute of Applied Mathematics Academy of Mathematics and Systems ScienceChinese Academy of Sciences Department of Applied Mathematics The Hong Kong Polytechnic University Shenzhen Research Institute The Hong Kong Polytechnic University Dalla Lana School of Public Health University of Toronto

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.

关键词： additive-multiplicative rates model missing data multivariate recurrent events semiparametricmodel weighted estimating equation

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A Semiparametric additive-multiplicative rates model for the Weighted Composite Endpoint of Recurrent and Terminal Events

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Acta Mathematica Sinica,English Series 2024年第4期40卷 985-999页

作者： Yi DENG Qiang XIONG Shu Wei LI School of Economics and Statistics Guangzhou UniversityGuangzhou 510006P.R.China

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 *** 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 *** 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 *** 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

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