Recurrent event data often arises in biomedical studies, and individuals within a cluster might not be independent. We propose a semiparametric additive rates model for clustered recurrent event data, wherein the cova...Recurrent event data often arises in biomedical studies, and individuals within a cluster might not be independent. We propose a semiparametric additive rates model for clustered recurrent event data, wherein the covariates are assumed to add to the unspecified baseline rate. For the inference on the model parameters, estimating equation approaches are developed, and both large and finite sample properties of the proposed estimators are established.展开更多
Recurrent events data with a terminal event （e.g. death） often arise in clinical and observational studies. Most of existing models assume multiplicative covariate effects and model the conditional recurrent event r...Recurrent events data with a terminal event （e.g. death） often arise in clinical and observational studies. Most of existing models assume multiplicative covariate effects and model the conditional recurrent event rate given survival. In this article, we propose a general mSditive-multiplicative rates model for recurrent event data in the presence of a terminal event, where the terminal event stop the further occurrence of recurrent events. Based on the estimating equation approach and the inverse probability weighting technique, we propose two procedures for estimating the regression parameters and the baseline mean function. The asymptotic properties of the resulting estimators are established. In addition, some graphical and numerical procedures are presented for model checking. The finite-sample behavior of the proposed methods is examined through simulation studies, and an application to a bladder cancer study is also illustrated.展开更多
基金supported by International Cooperation Projects (2010DFA31790) of Chinese Ministry of Science and Technologythe fund of Central China Normal University for Ph.D students (No. 2009023)+2 种基金supported by the National Natural Science Foundation of China Grants(No. 10731010, 10971015 and 11021161)the National Basic Research Program of China (973 Program) (No.2007CB814902)Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics& Systems Science, Chinese Academy of Sciences (No. 2008DP173182)
文摘Recurrent event data often arises in biomedical studies, and individuals within a cluster might not be independent. We propose a semiparametric additive rates model for clustered recurrent event data, wherein the covariates are assumed to add to the unspecified baseline rate. For the inference on the model parameters, estimating equation approaches are developed, and both large and finite sample properties of the proposed estimators are established.
基金Supported by the National Natural Science Foundation of China(No.11371354)Young Elite Program of Beijing(YETP150)Science and Technology Project of Beijing Municipal Education Commission(KM201411232019)
文摘Recurrent events data with a terminal event （e.g. death） often arise in clinical and observational studies. Most of existing models assume multiplicative covariate effects and model the conditional recurrent event rate given survival. In this article, we propose a general mSditive-multiplicative rates model for recurrent event data in the presence of a terminal event, where the terminal event stop the further occurrence of recurrent events. Based on the estimating equation approach and the inverse probability weighting technique, we propose two procedures for estimating the regression parameters and the baseline mean function. The asymptotic properties of the resulting estimators are established. In addition, some graphical and numerical procedures are presented for model checking. The finite-sample behavior of the proposed methods is examined through simulation studies, and an application to a bladder cancer study is also illustrated.
