A Bayesian semiparametric transformation model incorporating frailties

We describe a Bayesian semiparametric (failure time) transformation model for which an unknown monotone transformation of failure times is assumed linearly dependent on observed covariates with an unspecified error distribution. The two unknowns: the monotone transformation and error distribution are assigned prior distributions with large supports. Our class of regression model includes the proportional hazards, accelerated failure time, and frailty models. Numerical examples are presented.