IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v65y2016i5p755-773.html
   My bibliography  Save this article

Quantile residual life regression with longitudinal biomarker measurements for dynamic prediction

Author

Listed:
  • Ruosha Li
  • Xuelin Huang
  • Jorge Cortes

Abstract

No abstract is available for this item.

Suggested Citation

  • Ruosha Li & Xuelin Huang & Jorge Cortes, 2016. "Quantile residual life regression with longitudinal biomarker measurements for dynamic prediction," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(5), pages 755-773, November.
    • Handle: RePEc:bla:jorssc:v:65:y:2016:i:5:p:755-773
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssc.12152
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Dimitris Rizopoulos, 2011. "Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data," Biometrics, The International Biometric Society, vol. 67(3), pages 819-829, September.
    3. Liuquan Sun & Xinyuan Song & Zhigang Zhang, 2012. "Mean residual life models with time-dependent coefficients under right censoring," Biometrika, Biometrika Trust, vol. 99(1), pages 185-197.
    4. Tianle Hu & Bin Nan & Xihong Lin & James M. Robins, 2011. "Time-dependent cross ratio estimation for bivariate failure times," Biometrika, Biometrika Trust, vol. 98(2), pages 341-354.
    5. Yingye Zheng & Tianxi Cai & Ziding Feng, 2006. "Application of the Time-Dependent ROC Curves for Prognostic Accuracy with Multiple Biomarkers," Biometrics, The International Biometric Society, vol. 62(1), pages 279-287, March.
    6. Hans C. Van Houwelingen, 2007. "Dynamic Prediction by Landmarking in Event History Analysis," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(1), pages 70-85, March.
    7. Y. Q. Chen & N. P. Jewell & X. Lei & S. C. Cheng, 2005. "Semiparametric Estimation of Proportional Mean Residual Life Model in Presence of Censoring," Biometrics, The International Biometric Society, vol. 61(1), pages 170-178, March.
    8. Jong-Hyeon Jeong & Sin-Ho Jung & Joseph P. Costantino, 2008. "Nonparametric Inference on Median Residual Life Function," Biometrics, The International Biometric Society, vol. 64(1), pages 157-163, March.
    9. Jianhua Z. Huang, 2002. "Varying-coefficient models and basis function approximations for the analysis of repeated measurements," Biometrika, Biometrika Trust, vol. 89(1), pages 111-128, March.
    10. 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.
    11. Peng, Limin & Fine, Jason P., 2009. "Competing Risks Quantile Regression," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1440-1453.
    12. Zhezhen Jin, 2003. "Rank-based inference for the accelerated failure time model," Biometrika, Biometrika Trust, vol. 90(2), pages 341-353, June.
    13. David C. Schmittlein & Donald G. Morrison, 1981. "The Median Residual Lifetime: A Characterization Theorem and an Application," Operations Research, INFORMS, vol. 29(2), pages 392-399, April.
    14. Wang, You-Gan & Shao, Quanxi & Zhu, Min, 2009. "Quantile regression without the curse of unsmoothness," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3696-3705, August.
    15. 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.
    16. Jing Ning & Karen Bandeen-Roche, 2014. "Estimation of time-dependent association for bivariate failure times in the presence of a competing risk," Biometrics, The International Biometric Society, vol. 70(1), pages 10-20, March.
    17. Sin-Ho Jung & Jong-Hyeon Jeong & Hanna Bandos, 2009. "Regression on Quantile Residual Life," Biometrics, The International Biometric Society, vol. 65(4), pages 1203-1212, December.
    18. Yingye Zheng & Patrick J. Heagerty, 2005. "Partly Conditional Survival Models for Longitudinal Data," Biometrics, The International Biometric Society, vol. 61(2), pages 379-391, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kyu Hyun Kim & Daniel J. Caplan & Sangwook Kang, 2023. "Smoothed quantile regression for censored residual life," Computational Statistics, Springer, vol. 38(2), pages 1001-1022, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kyu Hyun Kim & Daniel J. Caplan & Sangwook Kang, 2023. "Smoothed quantile regression for censored residual life," Computational Statistics, Springer, vol. 38(2), pages 1001-1022, June.
    2. 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.
    3. Giulia Barbati & Alessio Farcomeni, 2018. "Prognostic assessment of repeatedly measured time-dependent biomarkers, with application to dilated cardiomyopathy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(3), pages 545-557, August.
    4. Marlena Maziarz & Patrick Heagerty & Tianxi Cai & Yingye Zheng, 2017. "On longitudinal prediction with time-to-event outcome: Comparison of modeling options," Biometrics, The International Biometric Society, vol. 73(1), pages 83-93, March.
    5. Zahra Mansourvar & Torben Martinussen & Thomas H. Scheike, 2016. "An Additive–Multiplicative Restricted Mean Residual Life Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 487-504, June.
    6. Ying Cui & Limin Peng, 2022. "Assessing dynamic covariate effects with survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(4), pages 675-699, October.
    7. Peng Liu & Yixin Wang & Yong Zhou, 2015. "Quantile residual lifetime with right-censored and length-biased data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(5), pages 999-1028, October.
    8. Luis Alexander Crouch & Cheng Zheng & Ying Qing Chen, 2017. "Estimating a Treatment Effect in Residual Time Quantiles Under the Additive Hazards Model," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 298-315, June.
    9. 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.
    10. Yuanshan Wu & Yanyuan Ma & Guosheng Yin, 2015. "Smoothed and Corrected Score Approach to Censored Quantile Regression With Measurement Errors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1670-1683, December.
    11. Liang Li & Sheng Luo & Bo Hu & Tom Greene, 2017. "Dynamic Prediction of Renal Failure Using Longitudinal Biomarkers in a Cohort Study of Chronic Kidney Disease," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 357-378, December.
    12. Pang, Lei & Lu, Wenbin & Wang, Huixia Judy, 2012. "Variance estimation in censored quantile regression via induced smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 785-796.
    13. Hao, Meiling & Lin, Yuanyuan & Shen, Guohao & Su, Wen, 2023. "Nonparametric inference on smoothed quantile regression process," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    14. Gongjun Xu & Tony Sit & Lan Wang & Chiung-Yu Huang, 2017. "Estimation and Inference of Quantile Regression for Survival Data Under Biased Sampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1571-1586, October.
    15. Sihai Dave Zhao & Yi Li, 2014. "Score test variable screening," Biometrics, The International Biometric Society, vol. 70(4), pages 862-871, December.
    16. Yimeng Liu & Liwen Wu & Gong Tang & Abdus S. Wahed, 2023. "A series of two-sample non-parametric tests for quantile residual life time," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 234-252, January.
    17. Narisetty, Naveen & Koenker, Roger, 2022. "Censored quantile regression survival models with a cure proportion," Journal of Econometrics, Elsevier, vol. 226(1), pages 192-203.
    18. Yu Zheng & Tianxi Cai, 2017. "Augmented estimation for t‐year survival with censored regression models," Biometrics, The International Biometric Society, vol. 73(4), pages 1169-1178, December.
    19. De Backer, Mickael & El Ghouch, Anouar & Van Keilegom, Ingrid, 2017. "An Adapted Loss Function for Censored Quantile Regression," LIDAM Discussion Papers ISBA 2017003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    20. Paul Frédéric Blanche & Anders Holt & Thomas Scheike, 2023. "On logistic regression with right censored data, with or without competing risks, and its use for estimating treatment effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 441-482, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssc:v:65:y:2016:i:5:p:755-773. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.