Semiparametric Accelerated Failure Time Models for Censored Data
Subhashis Ghosal · 2006
An accelerated failure time (AFT) semiparametric regression model for censored data is analyzed as an alternative to the widely used proportional hazards survival model.The statistical inference is based on a nonparametric Bayesian approach that uses a Dirichlet process prior for the mixing distribution.Consistency of the posterior distribution of the regression parameters in the Euclidean metric is established under certain conditions.Finite sample parameter estimates along with associated measure of un-certainties can be computed by a MCMC method. Simulation studies are presented to provide empirical validation of the new method.Analysis of data from two studies are provided to show the easy applicability of the proposed method.