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Published on: December 9, 2015
Semiparametric analysis of recurrent events: artificial censoring, truncation, pairwise estimation and inference
1Department of Statistics and Public Health Sciences, Penn State University, 514A Wartik Lab, University Park, PA 16802, USA. ghoshd@psu.edu
Abstract:
The analysis of recurrent failure time data from longitudinal studies can be complicated by the presence of dependent censoring. There has been a substantive literature that has developed based on an artificial censoring device. We explore in this article the connection between this class of methods with truncated data structures. In addition, a new procedure is developed for estimation and inference in a joint model for recurrent events and dependent censoring. Estimation proceeds using a mixed U-statistic based estimating function approach. New resampling-based methods for variance estimation and model checking are also described. The methods are illustrated by application to data from an HIV clinical trial as with a limited simulation study.
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