Application of quantile regression models for biomedical data

A new lack-of-fit test for censored quantile regression models with multiple or even high-dimensional covariates will be presented. The test is based on the cumulative sum of residuals with respect to unidimensional linear projections of the covariates. The test is then adapting the ideas presented in [1], to cope with high-dimensional covariates, to the test proposed by [2]. The limit distribution of the empirical process associated with the test statistic will be shown. Furthermore, in order to approximate the critical values of the test, a bootstrap mechanism is used, which is similar to the proposal developed in [3]. In addition, an extensive simulation study and an interesting real data application will be presented in order to show the behaviour of the new test in practice