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, pages 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: Add references at CitEc
Citations Track citations by RSS feed

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: http://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.tandf.co.uk/journals/subscription.asp

Access Statistics for this article

Journal of Applied Statistics is edited by Professor Gopal K. Kanji

More articles in Journal of Applied Statistics from Taylor and Francis Journals
Series data maintained by Michael McNulty ().