Non-proportional hazards model with a PVF frailty term : application with a melanoma dataset
© 2024 Informa UK Limited, trading as Taylor & Francis Group.
| Publié dans: | Journal of applied statistics. - 1991. - 52(2025), 1 vom: 18., Seite 1-27 |
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| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2025
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| Accès à la collection: | Journal of applied statistics |
| Sujets: | Journal Article 62N02 62N03 Cure rate models generalized time-dependent log-log model maximum likelihood estimation random effects skin cancer |
| Résumé: | © 2024 Informa UK Limited, trading as Taylor & Francis Group. Survival data analysis often uses the Cox proportional hazards (PH) model. This model is widely applied due to its straightforward interpretation of the hazard ratio under the assumption that the hazard rates for two subjects remain constant over time. However, in several randomized clinical trials with long-term survival data comparing two new treatments, it is frequently observed that Kaplan-Meier plots exhibit crossing survival curves. This violation of the PH assumption of the Cox PH model can not be applied to evaluate the treatment's effect on survival. This paper introduces a novel long-term survival model with non-PH that incorporates a frailty term into the hazard function. This model allows us to examine the effect of prognostic factors on survival and quantify the degree of unobservable heterogeneity. The model parameters are estimated using the maximum likelihood estimation procedure, and we evaluate the performance of the proposed models through simulation studies. Additionally, we demonstrate the applicability of our approach by fitting the models to a real skin cancer dataset |
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| Description: | Date Revised 15.05.2025 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
| ISSN: | 0266-4763 |
| DOI: | 10.1080/02664763.2024.2354443 |