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Quantile Regression Models with Multivariate Failure Time Data

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  • Guosheng Yin
  • Jianwen Cai

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  • Guosheng Yin & Jianwen Cai, 2005. "Quantile Regression Models with Multivariate Failure Time Data," Biometrics, The International Biometric Society, vol. 61(1), pages 151-161, March.
    • Handle: RePEc:bla:biomet:v:61:y:2005:i:1:p:151-161
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2005.030815.x
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    References listed on IDEAS

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    1. Lindgren, Anna, 1997. "Quantile regression with censored data using generalized L1 minimization," Computational Statistics & Data Analysis, Elsevier, vol. 23(4), pages 509-524, February.
    2. Khan, Shakeeb & Powell, James L., 2001. "Two-step estimation of semiparametric censored regression models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 73-110, July.
    3. Fitzenberger, Bernd, 1998. "The moving blocks bootstrap and robust inference for linear least squares and quantile regressions," Journal of Econometrics, Elsevier, vol. 82(2), pages 235-287, February.
    4. Heejung Bang & Anastasios A. Tsiatis, 2002. "Median Regression with Censored Cost Data," Biometrics, The International Biometric Society, vol. 58(3), pages 643-649, September.
    5. Buchinsky, Moshe, 1995. "Estimating the asymptotic covariance matrix for quantile regression models a Monte Carlo study," Journal of Econometrics, Elsevier, vol. 68(2), pages 303-338, August.
    6. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    7. Bilias, Yannis & Chen, Songnian & Ying, Zhiliang, 2000. "Simple resampling methods for censored regression quantiles," Journal of Econometrics, Elsevier, vol. 99(2), pages 373-386, December.
    8. Ying, Z. & Wei, L. J., 1994. "The Kaplan-Meier Estimate for Dependent Failure Time Observations," Journal of Multivariate Analysis, Elsevier, vol. 50(1), pages 17-29, July.
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    Citations

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    Cited by:

    1. Liu Yuan & Bottai Matteo, 2009. "Mixed-Effects Models for Conditional Quantiles with Longitudinal Data," The International Journal of Biostatistics, De Gruyter, vol. 5(1), pages 1-24, November.
    2. Xiaoming Lu & Zhaozhi Fan, 2015. "Weighted quantile regression for longitudinal data," Computational Statistics, Springer, vol. 30(2), pages 569-592, June.
    3. Xianghua Luo & Chiung-Yu Huang & Lan Wang, 2013. "Quantile Regression for Recurrent Gap Time Data," Biometrics, The International Biometric Society, vol. 69(2), pages 375-385, June.
    4. Jingle Wang & Ming Zheng, 2012. "Wavelet detection of change points in hazard rate models with censored dependent data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 765-781.
    5. Amadou Barry & Karim Oualkacha & Arthur Charpentier, 2021. "Weighted asymmetric least squares regression with fixed-effects," Papers 2108.04737, arXiv.org.
    6. Xie, Shangyu & Wan, Alan T.K. & Zhou, Yong, 2015. "Quantile regression methods with varying-coefficient models for censored data," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 154-172.
    7. Akram Yazdani & Hojjat Zeraati & Mehdi Yaseri & Shahpar Haghighat & Ahmad Kaviani, 2022. "Laplace regression with clustered censored data," Computational Statistics, Springer, vol. 37(3), pages 1041-1068, July.
    8. Taoufik Bouezmarni & Jeroen Rombouts, 2008. "Density and hazard rate estimation for censored and α-mixing data using gamma kernels," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(7), pages 627-643.
    9. Fu, Liya & Wang, You-Gan & Zhu, Min, 2015. "A Gaussian pseudolikelihood approach for quantile regression with repeated measurements," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 41-53.
    10. Fu, Liya & Wang, You-Gan, 2016. "Efficient parameter estimation via Gaussian copulas for quantile regression with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 492-502.
    11. Tao Hu & Baosheng Liang, 2021. "A New Class of Estimators Based on a General Relative Loss Function," Mathematics, MDPI, vol. 9(10), pages 1-19, May.
    12. Jiang, Liewen & Bondell, Howard D. & Wang, Huixia Judy, 2014. "Interquantile shrinkage and variable selection in quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 208-219.
    13. Fu, Liya & Wang, You-Gan, 2012. "Quantile regression for longitudinal data with a working correlation model," Computational Statistics & Data Analysis, Elsevier, vol. 56(8), pages 2526-2538.
    14. Ioannis Badounas & Georgios Pitselis, 2020. "Loss Reserving Estimation With Correlated Run-Off Triangles in a Quantile Longitudinal Model," Risks, MDPI, vol. 8(1), pages 1-26, February.
    15. Maria Marino & Alessio Farcomeni, 2015. "Linear quantile regression models for longitudinal experiments: an overview," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 229-247, August.
    16. Jung-Yu Cheng & Shinn-Jia Tzeng, 2014. "Quantile regression of right-censored length-biased data using the Buckley–James-type method," Computational Statistics, Springer, vol. 29(6), pages 1571-1592, December.
    17. Chien-Lin Su & Russell J. Steele & Ian Shrier, 2021. "The semiparametric accelerated trend-renewal process for recurrent event data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(3), pages 357-387, July.
    18. Wenjing Yin & Sihai Dave Zhao & Feng Liang, 2022. "Bayesian penalized Buckley-James method for high dimensional bivariate censored regression models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(2), pages 282-318, April.
    19. Ruosha Li & Yu Cheng & Qingxia Chen & Jason Fine, 2017. "Quantile association for bivariate survival data," Biometrics, The International Biometric Society, vol. 73(2), pages 506-516, June.

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