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Title:

Dependence modeling for recurrent event times subject to right‐censoring with D‐vine copulas

Document type:
Zeitschriftenaufsatz
Author(s):
Barthel, Nicole; Geerdens, Candida; Czado, Claudia; Janssen, Paul
Abstract:
In many time‐to‐event studies, the event of interest is recurrent. Here, the data for each sample unit correspond to a series of gap times between the subsequent events. Given a limited follow‐up period, the last gap time might be right‐censored. In contrast to classical analysis, gap times and censoring times cannot be assumed independent, i.e., the sequential nature of the data induces dependent censoring. Also, the number of recurrences typically varies among sample units leading to unbalance...     »
Keywords:
Dependence modeling; D-vine copulas; Gap time data; Induced dependent right-censoring; Maximum likelihood estimation; Recurrent event time data; Survival analysis; Unbalanced data
Dewey Decimal Classification:
510 Mathematik
Journal title:
Biometrics
Year:
2019
Journal volume:
75
Year / month:
2019-06
Quarter:
2. Quartal
Month:
Jun
Journal issue:
2
Pages contribution:
439-451
Language:
en
Fulltext / DOI:
doi:10.1111/biom.13014
Publisher:
Wiley
E-ISSN:
0006-341X1541-0420
Notes:
First published online: 14 December 2018
Status:
Verlagsversion / published
Date of publication:
03.04.2019
TUM Institution:
Professur für Angewandte Mathematische Statistik
Format:
Text
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