|Title||Bayesian Transformation Models for Multivariate Survival Data.|
|Publication Type||Journal Article|
|Year of Publication||2014|
|Authors||DE Castro, Mário, Ming-Hui Chen, Joseph G. Ibrahim, and John P. Klein|
|Journal||Scand Stat Theory Appl|
|Date Published||2014 Mar|
In this paper we propose a general class of gamma frailty transformation models for multivariate survival data. The transformation class includes the commonly used proportional hazards and proportional odds models. The proposed class also includes a family of cure rate models. Under an improper prior for the parameters, we establish propriety of the posterior distribution. A novel Gibbs sampling algorithm is developed for sampling from the observed data posterior distribution. A simulation study is conducted to examine the properties of the proposed methodology. An application to a data set from a cord blood transplantation study is also reported.
|Alternate Journal||Scand Stat Theory Appl|
|Original Publication||Bayesian transformation models for multivariate survival data.|
|PubMed Central ID||PMC4040529|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R01 GM070335 / GM / NIGMS NIH HHS / United States
Bayesian Transformation Models for Multivariate Survival Data.