Frailty models for survival data

A frailty model is a random effects model for time variables, where the random effect (the frailty) has a multiplicative effect on the hazard. It can be used for univariate (independent) failure times, i.e. to describe the influence of unobserved covariates in a proportional hazards model. More inte...

Full description

Saved in:
Bibliographic Details
Published in:Lifetime data analysis 1995, Vol.1 (3), p.255-273
Main Author: Hougaard, P
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Child
Female
Humans
Male
Middle Aged
Models, Statistical
Mortality
Multivariate Analysis
Proportional Hazards Models
Survival Analysis
Twins
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A frailty model is a random effects model for time variables, where the random effect (the frailty) has a multiplicative effect on the hazard. It can be used for univariate (independent) failure times, i.e. to describe the influence of unobserved covariates in a proportional hazards model. More interesting, however, is to consider multivariate (dependent) failure times generated as conditionally independent times given the frailty. This approach can be used both for survival times for individuals, like twins or family members, and for repeated events for the same individual. The standard assumption is to use a gamma distribution for the frailty, but this is a restriction that implies that the dependence is most important for late events. More generally, the distribution can be stable, inverse Gaussian, or follow a power variance function exponential family. Theoretically, large differences are seen between the choices. In practice, using the largest model makes it possible to allow for more general dependence structures, without making the formulas too complicated.
ISSN:1380-7870
1572-9249
DOI:10.1007/BF00985760