Perperoglou, Aris and Keramopoullos, Antonis and van Houwelingen, Hans C (2007) Approaches in modelling long‐term survival: an application to breast cancer. Statistics in Medicine, 26 (13). pp. 2666-2685. DOI https://doi.org/10.1002/sim.2729
Perperoglou, Aris and Keramopoullos, Antonis and van Houwelingen, Hans C (2007) Approaches in modelling long‐term survival: an application to breast cancer. Statistics in Medicine, 26 (13). pp. 2666-2685. DOI https://doi.org/10.1002/sim.2729
Perperoglou, Aris and Keramopoullos, Antonis and van Houwelingen, Hans C (2007) Approaches in modelling long‐term survival: an application to breast cancer. Statistics in Medicine, 26 (13). pp. 2666-2685. DOI https://doi.org/10.1002/sim.2729
Abstract
<jats:title>Abstract</jats:title><jats:p>Several modelling techniques have been proposed for non‐proportional hazards. In this work we consider different models which can be classified into three wide categories: models with time‐varying effects of the covariates; frailty models and cure rate models. We present those different extensions of the proportional hazards model on an application of 2433 breast cancer patients with a long follow‐up. We comment on the differences and similarities among the models and evaluate their performance using survival and hazard plots, Brier scores and pseudo‐observations. Copyright © 2006 John Wiley & Sons, Ltd.</jats:p>
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | reduced-rank models; relaxed Burr model; time-dependent effects; pseudo-observations; Brier scores |
| Subjects: | Q Science > QA Mathematics |
| Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
| SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 06 Nov 2012 10:44 |
| Last Modified: | 04 Dec 2024 06:25 |
| URI: | http://repository.essex.ac.uk/id/eprint/3827 |