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Censored Quantile Regression Redux

  • Roger Koenker
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    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.

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    Article provided by American Statistical Association in its journal Journal of Statistical Software.

    Volume (Year): 27 ()
    Issue (Month): i06 ()
    Pages:

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    Handle: RePEc:jss:jstsof:27:i06
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    1. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    2. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    3. Peng, Limin & Huang, Yijian, 2008. "Survival Analysis With Quantile Regression Models," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 637-649, June.
    4. Lindgren, Anna, 1997. "Quantile regression with censored data using generalized L1 minimization," Computational Statistics & Data Analysis, Elsevier, vol. 23(4), pages 509-524, February.
    5. repec:cup:cbooks:9780521845731 is not listed on IDEAS
    6. repec:cup:cbooks:9780521608275 is not listed on IDEAS
    7. Fitzenberger, Bernd & Winker, Peter, 2007. "Improving the computation of censored quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 88-108, September.
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