A flexible model for survival data with a cure rate: a Bayesian approach

Vicente Cancho, Josemar Rodrigues and Mario de Castro

Journal of Applied Statistics, 2011, vol. 38, issue 1, 57-70

Abstract: In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real data set.

Keywords: survival analysis; cure rate models; long-term survival models; negative binomial distribution; Bayesian analysis; piecewise exponential distribution; Weibull distribution (search for similar items in EconPapers)
Date: 2011
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/02664760903254052 (text/html)
Access to full text is restricted to subscribers.

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:taf:japsta:v:38:y:2011:i:1:p:57-70

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20

DOI: 10.1080/02664760903254052

Access Statistics for this article

Journal of Applied Statistics is currently edited by Robert Aykroyd

More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().