The University of Southampton
University of Southampton Institutional Repository

A Weibull regression model with gamma frailties for multivariate survival data

Sahu, Sujit K., Dey, Dipak K., Aslanidou, Helen and Sinha, Debajyoti (1997) A Weibull regression model with gamma frailties for multivariate survival data Lifetime Data Analysis, 3, (2), pp. 123-137. (doi:10.1023/A:1009605117713).

Record type: Article


Frequently in the analysis of survival data, survival times within the same group are correlated due to unobserved co-variates. One way these co-variates can be included in the model is as frailties. These frailty random block effects generate dependency between the survival times of the individuals which are conditionally independent given the frailty. Using a conditional proportional hazards model, in conjunction with the frailty, a whole new family of models is introduced. By considering a gamma frailty model, often the issue is to find an appropriate model for the baseline hazard function. In this paper a flexible baseline hazard model based on a correlated prior process is proposed and is compared with a standard Weibull model. Several model diagnostics methods are developed and model comparison is made using recently developed Bayesian model selection criteria. The above methodologies are applied to the McGilchrist and Aisbett (1991) kidney infection data and the analysis is performed using Markov Chain Monte Carlo methods.

Full text not available from this repository.

More information

Published date: 1997
Keywords: autocorrelated prior process, conditional predictive ordinate, frailty, markov chain monte carlo methods, model determination, posterior predictive loss, proportional hazards model, weibull model
Organisations: Statistics


Local EPrints ID: 30019
ISSN: 1380-7870
PURE UUID: 88e849d6-d68a-4197-bd2c-b4f30601245a
ORCID for Sujit K. Sahu: ORCID iD

Catalogue record

Date deposited: 11 May 2007
Last modified: 17 Jul 2017 15:56

Export record



Author: Sujit K. Sahu ORCID iD
Author: Dipak K. Dey
Author: Helen Aslanidou
Author: Debajyoti Sinha

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.