The University of Southampton
University of Southampton Institutional Repository

Parametric accelerated failure time models with random effects and an application to kidney transplant survival

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), pp. 3177-3192. (doi:10.1002/sim.1876).

Record type: Article


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.

Full text not available from this repository.

More information

Published date: 2004
Keywords: survival analysis, accelerated failure time model, frailty, random effects, Gompertz hazard, transplant survival
Organisations: Statistics


Local EPrints ID: 42003
ISSN: 0277-6715
PURE UUID: b57aefaa-01f2-48ad-a18b-3b45ad623703

Catalogue record

Date deposited: 30 Oct 2006
Last modified: 17 Jul 2017 15:25

Export record



Author: Philippe Lambert
Author: Dave Collett
Author: Alan Kimber
Author: Rachel Johnson

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.