The relative frailty variance and shared frailty models

C. Paddy Farrington, Steffen Unkel, Karim Anaya-Izquierdo

Research output: Contribution to journalArticlepeer-review

16 Citations (SciVal)

Abstract

The relative frailty variance among survivors provides a readily interpretable measure of how the heterogeneity of a population, as represented by a frailty model, evolves over time. We discuss the properties of the relative frailty variance, show that it characterizes frailty distributions and that, suitably rescaled, it may be used to compare patterns of dependence across models and data sets. In shared frailty models, the relative frailty variance is closely related to the cross-ratio function, which is estimable from bivariate survival data. We investigate the possible shapes of the relative frailty variance function for the purpose of model selection, and we review available frailty distribution families in this context. We introduce several new families with contrasting properties, including simple but flexible time varying frailty models. The benefits of the approach that we propose are illustrated with two applications to bivariate current status data obtained from serological surveys.
Original languageEnglish
Pages (from-to)673-696
Number of pages24
JournalJournal of the Royal Statistical Society: Series B - Statistical Methodology
Volume74
Issue number4
Early online date15 Feb 2012
DOIs
Publication statusPublished - Sept 2012

Keywords

  • Cross-ratio function, Cure model, Current status data, Frailty, Heterogeneity, Relative frailty variance, Shared frailty model, Survival data, Time varying frailty

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