Maximum approximate likelihood estimation in accelerated failure time model for interval-censored data.
accelerated failure time model
beta mixture model
current status data
interval censoring
smooth estimation
survival curve
Journal
Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016
Informations de publication
Date de publication:
20 11 2023
20 11 2023
Historique:
revised:
22
06
2023
received:
15
11
2022
accepted:
21
08
2023
medline:
23
10
2023
pubmed:
1
9
2023
entrez:
31
8
2023
Statut:
ppublish
Résumé
The approximate Bernstein polynomial model, a mixture of beta distributions, is applied to obtain maximum likelihood estimates of the regression coefficients, the baseline density and the survival functions in an accelerated failure time model based on interval censored data including current status data. The estimators of the regression coefficients and the underlying baseline density function are shown to be consistent with almost parametric rates of convergence under some conditions for uncensored and/or interval censored data. Simulation shows that the proposed method is better than its competitors. The proposed method is illustrated by fitting the Breast Cosmetic and the HIV infection time data using the accelerated failure time model.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
4886-4896Informations de copyright
© 2023 The Author. Statistics in Medicine published by John Wiley & Sons Ltd.
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