Bayesian methods for missing covariates in cure rate models

摘要

We propose methods for Bayesian inference for missing covariate data with a novel class of semi- parametric survival models with a cure fraction. We allow the missing covariates to be either categorical or continuous and specify a parametric distribution for the covariates that is written as a sequence of one dimensional conditional distributions. We assume that the missing covariate are missing at random(MAR)throughout. We propose an informative class of joint prior distribution for the regression coefficients and the parameters arising from the covariate distributions. The proposed class of priors are shown to be useful in recovering information on the missing covariate especially in situations where the missing data fraction is large.