Censored quantile regression redux

Roger Koenker

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)1-25
Number of pages25
JournalJournal of Statistical Software
Volume27
Issue number6
DOIs
StatePublished - Jul 2008

Keywords

  • Censored data
  • Quantile regression

ASJC Scopus subject areas

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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