Bayesian extension of the Weibull AFT shared frailty model with generalized family of distributions for enhanced survival analysis using censored data
© 2024 Informa UK Limited, trading as Taylor & Francis Group.
| Veröffentlicht in: | Journal of applied statistics. - 1991. - 51(2024), 15 vom: 06., Seite 3125-3153 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | Journal of applied statistics |
| Schlagworte: | Journal Article AFT LOOIC STAN Type I half-logistic-G WAIC Weibull distribution censored data shared-frailty type II exponentiated half logistic-G |
| Zusammenfassung: | © 2024 Informa UK Limited, trading as Taylor & Francis Group. In survival analysis, the Accelerated Failure Time (AFT) shared frailty model is a widely used framework for analyzing time-to-event data while accounting for unobserved heterogeneity among individuals. This paper extends the traditional Weibull AFT shared frailty model using half logistic-G family of distributions (Type I, Type II and Type II exponentiated) through Bayesian methods. This approach offers flexibility in capturing covariate influence and handling heavy-tailed frailty distributions. Bayesian inference with MCMC provides parameter estimates and credible intervals. Simulation studies show improved model predictive performance compared to existing models, and real-world applications demonstrate its practical utility. In summary, our Bayesian Weibull AFT shared frailty model with Type I, Type II and Type II exponentiated half logistic-G family distributions enhances time-to-event data analysis, making it a versatile tool for survival analysis in various fields using STAN in R |
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| Beschreibung: | Date Revised 07.11.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
| ISSN: | 0266-4763 |
| DOI: | 10.1080/02664763.2024.2338404 |