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Assessing quantile prediction with censored quantile regression models

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  • Ruosha Li
  • Limin Peng

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  • Ruosha Li & Limin Peng, 2017. "Assessing quantile prediction with censored quantile regression models," Biometrics, The International Biometric Society, vol. 73(2), pages 517-528, June.
  • Handle: RePEc:bla:biomet:v:73:y:2017:i:2:p:517-528
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    File URL: http://hdl.handle.net/10.1111/biom.12627
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    References listed on IDEAS

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    1. Noh, Hohsuk & El Ghouch, Anouar & Van Keilegom, Ingrid, 2013. "Assessing model adequacy in possibly misspecified quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 558-569.
    2. Wang, Huixia Judy & Wang, Lan, 2009. "Locally Weighted Censored Quantile Regression," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1117-1128.
    3. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    4. Uno, Hajime & Cai, Tianxi & Tian, Lu & Wei, L.J., 2007. "Evaluating Prediction Rules for t-Year Survivors With Censored Regression Models," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 527-537, June.
    5. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    6. Pei-Yun Chen & Anastasios A. Tsiatis, 2001. "Causal Inference on the Difference of the Restricted Mean Lifetime Between Two Groups," Biometrics, The International Biometric Society, vol. 57(4), pages 1030-1038, December.
    7. 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.
    8. Wang, Hansheng & Leng, Chenlei, 2007. "Unified LASSO Estimation by Least Squares Approximation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1039-1048, September.
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    Cited by:

    1. Cuihong Zhang & Jing Ning & Steven H. Belle & Robert H. Squires & Jianwen Cai & Ruosha Li, 2022. "Assessing predictive discrimination performance of biomarkers in the presence of treatment‐induced dependent censoring," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1137-1157, November.
    2. Jia, Yichen & Jeong, Jong-Hyeon, 2022. "Deep learning for quantile regression under right censoring: DeepQuantreg," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).

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