Premium
Parametric accelerated failure time models with random effects and an application to kidney transplant survival
Author(s) -
Lambert Philippe,
Collett Dave,
Kimber Alan,
Johnson Rachel
Publication year - 2004
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1876
Subject(s) - random effects model , hazard , parametric statistics , proportional hazards model , hazard ratio , statistics , accelerated failure time model , component (thermodynamics) , survival function , term (time) , parametric model , survival analysis , computer science , econometrics , function (biology) , kidney transplant , transplantation , kidney transplantation , mathematics , medicine , confidence interval , meta analysis , chemistry , physics , organic chemistry , quantum mechanics , evolutionary biology , biology , thermodynamics
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. Copyright © 2004 John Wiley & Sons, Ltd.