Estimation of Varying Coeffcient Model with Randomly Right-Censored Covariate

Data is often rightly-censored due to loss of follow-up, drop-out from experiments or end of clinical trials. The treatment of right-censored data has attracted the interest of many researchers. Most existing studies focus on the cases that the response variable is censored. Predictors in the regression model may also suffer from right-censoring. However, there is only sporadic work on the treatment of censored covariates. In this paper, the estimation of a varying coeffcient model with randomly right-censored covariate is investigated. To deal with the right-censoring, we adjust the objective function directly through an inverse probability weighting, instead of the adjustment of the right-censored predictor. Estimation of the regression coeffcient are proposed. The asymptotic properties of the proposed estimator is strictly investigated. Numerical simulations and real-data analyses show that the proposed method has good finite sample properties.