IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v62y2000i4p657-665.html
   My bibliography  Save this article

Failure time regression with continuous covariates measured with error

Author

Listed:
  • Halbo Zhou
  • C.‐Y. Wang

Abstract

We consider failure time regression analysis with an auxiliary variable in the presence of a validation sample. We extend the nonparametric inference procedure of Zhou and Pepe to handle a continuous auxiliary or proxy covariate. We estimate the induced relative risk function with a kernel smoother and allow the selection probability of the validation set to depend on the observed covariates. We present some asymptotic properties for the kernel estimator and provide some simulation results. The method proposed is illustrated with a data set from an on‐going epidemiologic study.

Suggested Citation

  • Halbo Zhou & C.‐Y. Wang, 2000. "Failure time regression with continuous covariates measured with error," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 657-665.
    • Handle: RePEc:bla:jorssb:v:62:y:2000:i:4:p:657-665
    DOI: 10.1111/1467-9868.00255
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-9868.00255
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-9868.00255?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

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


    Cited by:

    1. Sun, Yanqing & Li, Mei & Gilbert, Peter B., 2016. "Goodness-of-fit test of the stratified mark-specific proportional hazards model with continuous mark," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 348-358.
    2. Guangren Yang & Yanqing Sun & Li Qi & Peter B. Gilbert, 2017. "Estimation of Stratified Mark-Specific Proportional Hazards Models Under Two-Phase Sampling with Application to HIV Vaccine Efficacy Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 259-283, June.
    3. Sehee Kim & Yi Li & Donna Spiegelman, 2016. "A semiparametric copula method for Cox models with covariate measurement error," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(1), pages 1-16, January.
    4. Wendy F. Greene & Jianwen Cai, 2004. "Measurement Error in Covariates in the Marginal Hazards Model for Multivariate Failure Time Data," Biometrics, The International Biometric Society, vol. 60(4), pages 987-996, December.
    5. Yanyan Liu & Haibo Zhou & Jianwen Cai, 2009. "Estimated Pseudopartial-Likelihood Method for Correlated Failure Time Data with Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 65(4), pages 1184-1193, December.
    6. Feifei Yan & Lin Zhu & Yanyan Liu & Jianwen Cai & Haibo Zhou, 2021. "Semiparametric regression based on quadratic inference function for multivariate failure time data with auxiliary information," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(2), pages 269-299, April.
    7. Dongxiao Han & Liuquan Sun & Yanqing Sun & Li Qi, 2017. "Mark-specific additive hazards regression with continuous marks," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 467-494, July.
    8. Li Qi & Yanqing Sun & Peter B. Gilbert, 2017. "Generalized semiparametric varying-coefficient model for longitudinal data with applications to adaptive treatment randomizations," Biometrics, The International Biometric Society, vol. 73(2), pages 441-451, June.
    9. Xiaofei Wang & Haibo Zhou, 2010. "Design and Inference for Cancer Biomarker Study with an Outcome and Auxiliary-Dependent Subsampling," Biometrics, The International Biometric Society, vol. 66(2), pages 502-511, June.
    10. Yanqin Feng & Yurong Chen, 2018. "Regression analysis of current status data with auxiliary covariates and informative observation times," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(2), pages 293-309, April.
    11. Xiaofei Wang & Haibo Zhou, 2006. "A Semiparametric Empirical Likelihood Method for Biased Sampling Schemes with Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 62(4), pages 1149-1160, December.
    12. David M. Zucker & Donna Spiegelman, 2004. "Inference for the Proportional Hazards Model with Misclassified Discrete-Valued Covariates," Biometrics, The International Biometric Society, vol. 60(2), pages 324-334, June.
    13. Yanqin Feng & Ling Ma & Jianguo Sun, 2015. "Regression Analysis of Current Status Data Under the Additive Hazards Model with Auxiliary Covariates," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 118-136, March.
    14. Liu, Yanyan & Wu, Yuanshan & Zhou, Haibo, 2010. "Multivariate failure times regression with a continuous auxiliary covariate," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 679-691, March.
    15. Haibo Zhou & Jianwei Chen & Jianwen Cai, 2002. "Random Effects Logistic Regression Analysis with Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 58(2), pages 352-360, June.
    16. Qu, Lianqiang & Song, Xinyuan & Sun, Liuquan, 2018. "Identification of local sparsity and variable selection for varying coefficient additive hazards models," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 119-135.
    17. Zhaozhi Fan & Xiao-Feng Wang, 2009. "Marginal hazards model for multivariate failure time data with auxiliary covariates," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(7), pages 771-786.
    18. Chen, Yurong & Feng, Yanqin & Sun, Jianguo, 2015. "Regression analysis of multivariate current status data with auxiliary covariates under the additive hazards model," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 34-45.
    19. Shanshan Zhao & Ross L. Prentice, 2014. "Covariate measurement error correction methods in mediation analysis with failure time data," Biometrics, The International Biometric Society, vol. 70(4), pages 835-844, December.
    20. Haibo Zhou & Jinhong You & Bin Zhou, 2010. "Statistical inference for fixed-effects partially linear regression models with errors in variables," Statistical Papers, Springer, vol. 51(3), pages 629-650, September.

    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:jorssb:v:62:y:2000:i:4:p:657-665. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.