Abstract:
:Recurrent event data are commonly encountered in health-related longitudinal studies. In this paper time-to-events models for recurrent event data are studied with non-informative and informative censorings. In statistical literature, the risk set methods have been confirmed to serve as an appropriate and efficient approach for analysing recurrent event data when censoring is non-informative. This approach produces biased results, however, when censoring is informative for the time-to-events outcome data. We compare the risk set methods with alternative non-parametric approaches which are robust subject to informative censoring. In particular, non-parametric procedures for the estimation of the cumulative occurrence rate function (CORF) and the occurrence rate function (ORF) are discussed in detail. Simulation and an analysis of data from the AIDS Link to Intravenous Experiences Cohort Study is presented.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Wang MC,Chiang CTdoi
10.1002/sim.1029subject
Has Abstractpub_date
2002-02-15 00:00:00pages
445-56issue
3eissn
0277-6715issn
1097-0258pii
10.1002/sim.1029journal_volume
21pub_type
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