Semiparametric analysis of recurrent events: artificial censoring, truncation, pairwise estimation and inference
The final publication is available at www.springerlink.com at the following DOI: 10.1007/s10985-009-9150-4
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.
Debashis Ghosh. "Semiparametric analysis of recurrent events: artificial censoring, truncation, pairwise estimation and inference" Lifetime Data Analysis (2010).
Available at: http://works.bepress.com/debashis_ghosh/39