Nonparametric estimation of the distribution of gap times for recurrent events
In many longitudinal studies, information is collected on the times of different kinds of events. Some of these studies involve repeated events, where a subject or sample unit may experience a well-defined event several times throughout their history. Such events are called recurrent events. In this...
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| Veröffentlicht in: | Statistical methods & applications 2023-03, Vol.32 (1), p.103-128 |
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| creator | Soutinho, Gustavo Meira-Machado, Luís |
| description | In many longitudinal studies, information is collected on the times of different kinds of events. Some of these studies involve repeated events, where a subject or sample unit may experience a well-defined event several times throughout their history. Such events are called recurrent events. In this paper, we introduce nonparametric methods for estimating the marginal and joint distribution functions for recurrent event data. New estimators are introduced and their extensions to several gap times are also given. Nonparametric inference conditional on current or past covariate measures is also considered. We study by simulation the behavior of the proposed estimators in finite samples, considering two or three gap times. Our proposed methods are applied to the study of (multiple) recurrence times in patients with bladder tumors. Software in the form of an R package, called survivalREC, has been developed, implementing all methods. |
| doi_str_mv | 10.1007/s10260-022-00641-6 |
| format | Article |
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| subjects | Bladder cancer Chemistry and Earth Sciences Computer Science Distribution functions Economics Estimation Estimators Finance Health Sciences Humanities Insurance Law Management Mathematics and Statistics Medicine Nonparametric statistics Original Paper Physics Statistical Theory and Methods Statistics Statistics for Business Statistics for Engineering Statistics for Life Sciences Statistics for Social Sciences |
| title | Nonparametric estimation of the distribution of gap times for recurrent events |
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