A0656
Title: Semiparametric analysis of multivariate panel count data with informative observation processes
Authors: Chang Chen - University of Maryland (United States)
Xin He - University of Maryland (United States) [presenting]
Abstract: Multivariate panel count data arise in studies involving several related types of recurrent events in which the study subjects are examined periodically over time. The observation times may vary from subject to subject and carry information about the underlying recurrent event processes of interest. A joint modeling approach is proposed to account for the informative observation processes using bivariate shared frailty models. Estimating equations and an EM algorithm are developed for the parameter estimation, and the resulting estimators are shown to be consistent and asymptotically normal. The proposed methods are evaluated through simulation studies and illustrated with an application to data from a clinical trial of skin cancer.
