Parametric accelerated failure time models with random effects and an application to kidney transplant survival
Parametric accelerated failure time models with random effects and an application to kidney transplant survival
Accelerated failure time models with a shared random component are described, and are used to evaluate the effect of explanatory factors and different transplant centres on survival times following kidney transplantation. Different combinations of the distribution of the random effects and baseline hazard function are considered and the fit of such models to the transplant data is critically assessed. A mixture model that combines short- and long-term components of a hazard function is then developed, which provides a more flexible model for the hazard function. The model can incorporate different explanatory variables and random effects in each component. The model is straightforward to fit using standard statistical software, and is shown to be a good fit to the transplant data.
survival analysis, accelerated failure time model, frailty, random effects, Gompertz hazard, transplant survival
3177-3192
Lambert, Philippe
efb90329-4f48-4e3f-a6cf-0a8389759c01
Collett, Dave
7f065fd3-e3b3-487e-9e34-f48490884148
Kimber, Alan
40ba3a19-bbe3-47b6-9a8d-68ebf4cea774
Johnson, Rachel
459cd229-73a0-48a3-88cc-718ec64116f1
2004
Lambert, Philippe
efb90329-4f48-4e3f-a6cf-0a8389759c01
Collett, Dave
7f065fd3-e3b3-487e-9e34-f48490884148
Kimber, Alan
40ba3a19-bbe3-47b6-9a8d-68ebf4cea774
Johnson, Rachel
459cd229-73a0-48a3-88cc-718ec64116f1
Lambert, Philippe, Collett, Dave, Kimber, Alan and Johnson, Rachel
(2004)
Parametric accelerated failure time models with random effects and an application to kidney transplant survival.
Statistics in Medicine, 23 (20), .
(doi:10.1002/sim.1876).
Abstract
Accelerated failure time models with a shared random component are described, and are used to evaluate the effect of explanatory factors and different transplant centres on survival times following kidney transplantation. Different combinations of the distribution of the random effects and baseline hazard function are considered and the fit of such models to the transplant data is critically assessed. A mixture model that combines short- and long-term components of a hazard function is then developed, which provides a more flexible model for the hazard function. The model can incorporate different explanatory variables and random effects in each component. The model is straightforward to fit using standard statistical software, and is shown to be a good fit to the transplant data.
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Published date: 2004
Keywords:
survival analysis, accelerated failure time model, frailty, random effects, Gompertz hazard, transplant survival
Organisations:
Statistics
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Local EPrints ID: 42003
URI: http://eprints.soton.ac.uk/id/eprint/42003
ISSN: 0277-6715
PURE UUID: b57aefaa-01f2-48ad-a18b-3b45ad623703
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Date deposited: 30 Oct 2006
Last modified: 15 Mar 2024 08:42
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Author:
Philippe Lambert
Author:
Dave Collett
Author:
Rachel Johnson
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