Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Roger Koenker
Title: Censored Quantile Regression Redux
Abstract: Quantile regression for censored survival (duration) data offers a more flexible alternative to the Cox proportional hazard model for some applications. We describe three estimation methods for such applications that have been recently incorporated into the R package quantreg: the Powell (1986) estimator for fixed censoring, and two methods for random censoring, one introduced by Portnoy (2003), and the other by Peng and Huang (2008). The Portnoy and Peng-Huang estimators can be viewed, respectively, as generalizations to regression of the Kaplan-Meier and Nelson-Aalen estimators of univariate quantiles for censored observations. Some asymptotic and simulation comparisons are made to highlight advantages and disadvantages of the three methods.

Page views:: 12476. Submitted: 2008-02-20. Published: 2008-07-29.
Paper: Censored Quantile Regression Redux     Download PDF (Downloads: 10902)
quantreg_4.17.tar.gz: R source package Download (Downloads: 2384; 547KB) v27i06.R: R example code from the paper Download (Downloads: 2333; 1KB) R source code for simulations (Tables 2-7, Figures 4-5) Download (Downloads: 2652; 1MB) R source code for simulations (Table 1) Download (Downloads: 2194; 2KB) R source code for simulations (Figure 3) Download (Downloads: 2496; 5MB)

DOI: 10.18637/jss.v027.i06

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.