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

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Lambert, Philippe [UCL] Collett, Dave Kimber, Alan Johnson, Rachel

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.

Document type Article de périodique (Journal article) – Journal Article, Research Support, Non-U.S. Gov't
Publication date 2004
Journal information "Statistics in medicine" - Vol. 23, no. 20, p. 3177-92 (2004)
Peer reviewed yes
issn 0277-6715
Publication status Publié
Affiliation UCL
MESH Subject Adult ; Female ; Graft Survival ; Humans ; Kidney Transplantation ; Male ; Middle Aged ; Models, Biological ; Models, Statistical
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Bibliographic reference Lambert, Philippe ; Collett, Dave ; Kimber, Alan ; Johnson, Rachel. Parametric accelerated failure time models with random effects and an application to kidney transplant survival.. In: Statistics in medicine, Vol. 23, no. 20, p. 3177-92 (2004)
Permanent URL http://hdl.handle.net/2078.1/9972