B0554
Title: A single index model for censored quantile regression
Authors: Jianhui Zhou - University of Virginia (United States) [presenting]
Miao Lu - University of Virginia (United States)
Abstract: Quantile regression has been getting more attention in survival analysis recently due to its interpretability. For possible nonlinear relationship between survival time and risk factors, we study a single index model for censored quantile regression, and employ the local linear approximation for the unknown link function. To account for censoring, we consider the redistribution-of-mass to obtain a weighted quantile regression estimator. The developed estimator can be penalized for variable selection purpose. The asymptotic properties of the developed estimators are investigated. The performance of the developed estimation and variable selection methods is illustrated in simulation studies, and the methods are applied to a real data example.
