Modeling of Recurrent Event Data

Thomas M. Menino Convention & Exhibition Center 

Recurrent events are frequently observed in biomedical studies, and often they consist of more than one type of events of interests. Marginal analysis of each type of recurrent event is useful but cannot address questions on the relationship between different types of recurrent events. In this work, we study a dynamic association model. Our estimating equations are constructed based on the stochastic processes embedded with bivariate recurrent events data. The proposed estimation can be implemented by an efficient and stable algorithm. Our proposals are illustrated via simulation studies and an application to a real dataset.

recurrent event data

dynamic association 

Biometrics Section