Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17110
Title: Analysis of multivariate recurrent event data with time-dependent covariates and informative censoring
Authors: Zhao, X 
Liu, L
Liu, Y
Xu, W
Keywords: Frailty
Informative censoring
Marginal model
Multivariate recurrent event data
Pairwise pseudolikelihood
Issue Date: 2012
Publisher: Wiley-VCH
Source: Biometrical journal, 2012, v. 54, no. 5, p. 585-599 How to cite?
Journal: Biometrical journal 
Abstract: Multivariate recurrent event data are usually encountered in many clinical and longitudinal studies in which each study subject may experience multiple recurrent events. For the analysis of such data, most existing approaches have been proposed under the assumption that the censoring times are noninformative, which may not be true especially when the observation of recurrent events is terminated by a failure event. In this article, we consider regression analysis of multivariate recurrent event data with both time-dependent and time-independent covariates where the censoring times and the recurrent event process are allowed to be correlated via a frailty. The proposed joint model is flexible where both the distributions of censoring and frailty variables are left unspecified. We propose a pairwise pseudolikelihood approach and an estimating equation-based approach for estimating coefficients of time-dependent and time-independent covariates, respectively. The large sample properties of the proposed estimates are established, while the finite-sample properties are demonstrated by simulation studies. The proposed methods are applied to the analysis of a set of bivariate recurrent event data from a study of platelet transfusion reactions.
URI: http://hdl.handle.net/10397/17110
ISSN: 0323-3847
EISSN: 1521-4036
DOI: 10.1002/bimj.201100194
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