Effects of covariates on alternating recurrent events in accelerated failure time models.
AFT models
alternating recurrent events
hazard function
rhDNase
Journal
The international journal of biostatistics
ISSN: 1557-4679
Titre abrégé: Int J Biostat
Pays: Germany
ID NLM: 101313850
Informations de publication
Date de publication:
12 11 2020
12 11 2020
Historique:
received:
04
05
2019
accepted:
22
10
2020
pubmed:
12
11
2020
medline:
6
1
2022
entrez:
11
11
2020
Statut:
epublish
Résumé
In this article, we model alternately occurring recurrent events and study the effects of covariates on each of the survival times. This is done through the accelerated failure time models, where we use lagged event times to capture the dependence over both the cycles and the two events. However, since the errors of the two regression models are likely to be correlated, we assume a bivariate error distribution. Since most event time distributions do not readily extend to bivariate forms, we take recourse to copula functions to build up the bivariate distributions from the marginals. The model parameters are then estimated using the maximum likelihood method and the properties of the estimators studied. A data on respiratory disease is used to illustrate the technique. A simulation study is also conducted to check for consistency.
Identifiants
pubmed: 33174863
doi: 10.1515/ijb-2019-0099
pii: ijb-2019-0099
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
295-315Informations de copyright
© 2020 Walter de Gruyter GmbH, Berlin/Boston.
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