Abstract: By using the  flexible, robust, and  widely  applicable characteristics of the Interquantile regression model, we established an additive Interquantile regression model for data with right-censored response variables, time-dependent covariates, and partially nonlinear structures to  avoid the instability issues that traditional quantile regression models might encounter when estimating adjacent quantiles separately, we also estimated the unknown parameters of adjacent quantile intervals through a weighted rank estimation process combined with differential evolution algorithm. The simulation research results show the excellent performance of the proposed method under finite samples, and it is applied  to the Stanford heart transplant data in the United States.

Key words:  , Interquantile regression, right-censored response, time-dependent covariate, partially nonlinear structure