统计与管理学院2015年学术报告第40期
【主 题】 A semiparametric additive rates model for multivariate recurrent events with missing event categories
【报告人】 孙六全 研究员
中国科学院
【时 间】 2015年9月17日（星期四）15:00－16:00
【地 点】 上海财经大学统计与管理学院大楼1208室
【语 言】 英文
【摘 要】 Multivariate recurrent event data arise in many clinical and observational studies, in which subjects may experience multiple types of recurrent events. In some applications, event times can be always observed, but types for some events may be missing. In this article, a semiparametric additive rates model is proposed for analyzing multivariate recurrent event data when event categories are missing at random. A weighted estimating equation approach is developed to estimate parameters of interest, and the resulting estimators are shown to be consistent and asymptotically normal. In addition, a lack-of-fit test is presented to assess the adequacy of the model. Simulation studies demonstrate that the proposed method performs well for practical settings. An application to a platelet transfusion reaction study is provided.
