title: Censored quantile regression with recursive partitioning-based weights.
abstract: Censored quantile regression provides a useful alternative to the Cox proportional hazards model for analyzing survival data. It directly models the conditional quantile of the survival time and hence is easy to interpret. Moreover, it relaxes the proportionality constraint on the hazard function associated with the popular Cox model and is natural for modeling heterogeneity of the data. Recently, Wang and Wang (2009. Locally weighted censored quantile regression. Journal of the American Statistical Association 103, 1117-1128) proposed a locally weighted censored quantile regression approach that allows for covariate-dependent censoring and is less restrictive than other censored quantile regression methods. However, their kernel smoothing-based weighting scheme requires all covariates to be continuous and encounters practical difficulty with even a moderate number of covariates. We propose a new weighting approach that uses recursive partitioning, e.g. survival trees, that offers greater flexibility in handling covariate-dependent censoring in moderately high dimensions and can incorporate both continuous and discrete covariates. We prove that this new weighting scheme leads to consistent estimation of the quantile regression coefficients and demonstrate its effectiveness via Monte Carlo simulations. We also illustrate the new method using a widely recognized data set from a clinical trial on primary biliary cirrhosis.
authors: Division of Biostatistics, School of Public Heath, University of Minnesota, Minneapolis, MN 55455, USA.
authors: Andrew
authors: A
authors: Wey
authors: Lan
authors: L
authors: Wang
authors: Kyle
authors: K
authors: Rudser
mesh_terms: D001663:Bilirubin / Q000097:blood; D003198:Computer Simulation; D006801:Humans; D053208:Kaplan-Meier Estimate; D008105:Liver Cirrhosis, Biliary / Q000188:drug therapy; D015233:Models, Statistical; D009010:Monte Carlo Method; D010396:Penicillamine / Q000627:therapeutic use; D011517:Prothrombin Time; D012044:Regression Analysis
chemical_list: D010396:Penicillamine; D001663:Bilirubin
keywords: Censored quantile regression; Recursive partitioning; Survival analysis; Survival ensembles
references: Stat Med. 2012 Jul 20;31(16):1722-37
references: 22362470