A quantile regression estimator for interval-censored data

Abstract

Abstract We describe an estimating equation that can be used to fit quantile regression models to interval-censored data. The proposed estimator presents important advantages over the existing methods, and can be applied when the data are a mixture of interval-censored, left-censored, and right-censored observations. We describe estimation and inference, report simulation results, and apply the proposed method to analyze the Signal Tandmobiel® data. The necessary R code has been incorporated in the existing R package c t q r $\mathtt{c}\mathtt{t}\mathtt{q}\mathtt{r}$ .