Dynamic Bayesian Models for Survival Data

Dani Gamerman

Journal of the Royal Statistical Society Series C, 1991, vol. 40, issue 1, 63-79

Abstract: Dynamic models are proposed for the study of survival data with explanatory variables whose effects change through time. The parameters modelling these effects are allowed to vary between time intervals and a system equation provides the stochastic link for adjacent values. Sequential analysis is used, based on a factorization of the likelihood over the time intervals. The updating equations are obtained via the dynamic generalized modelling approach of West, Harrison and Migon. Predictive features for follow‐up studies and analysis of new observations are obtained and some numerical applications are provided.

Date: 1991
References: Add references at CitEc
Citations: View citations in EconPapers (22)

Downloads: (external link)
https://doi.org/10.2307/2347905

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:40:y:1991:i:1:p:63-79

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().