A Bayesian semiparametric accelerated failure time model. Academic Article

abstract

• A Bayesian semiparametric approach is described for an accelerated failure time model. The error distribution is assigned a Plya tree prior and the regression parameters a noninformative hierarchical prior. Two cases are considered: the first assumes error terms are exchangeable; the second assumes that error terms are partially exchangeable. A Markov chain Monte Carlo algorithm is described to obtain a predictive distribution for a future observation given both uncensored and censored data.

authors

• Mallick, Bani

published proceedings

• Biometrics

author list (cited authors)

• Walker, S., & Mallick, B. K.

citation count

• 112

complete list of authors

• Walker, S||Mallick, BK

publication date

• June 1999

publisher

• Oxford University Press (OUP)  Publisher

keywords

• Algorithms
• Bayes Theorem
• Biometry
• Humans
• Markov Chains
• Models, Statistical
• Monte Carlo Method
• Neoplasms
• Survival Analysis

Digital Object Identifier (DOI)

• 10.1111/j.0006-341x.1999.00477.x

start page

• 477

end page

• 483

volume

• 55

issue

• 2

URL

• http://dx.doi.org/10.1111/j.0006-341x.1999.00477.x