IDEAS home Printed from https://ideas.repec.org/a/spr/lifeda/v22y2016i3d10.1007_s10985-015-9340-1.html
   My bibliography  Save this article

Analysis of error-prone survival data under additive hazards models: measurement error effects and adjustments

Author

Listed:
  • Ying Yan

    (University of Waterloo)

  • Grace Y. Yi

    (University of Waterloo)

Abstract

Covariate measurement error occurs commonly in survival analysis. Under the proportional hazards model, measurement error effects have been well studied, and various inference methods have been developed to correct for error effects under such a model. In contrast, error-contaminated survival data under the additive hazards model have received relatively less attention. In this paper, we investigate this problem by exploring measurement error effects on parameter estimation and the change of the hazard function. New insights of measurement error effects are revealed, as opposed to well-documented results for the Cox proportional hazards model. We propose a class of bias correction estimators that embraces certain existing estimators as special cases. In addition, we exploit the regression calibration method to reduce measurement error effects. Theoretical results for the developed methods are established, and numerical assessments are conducted to illustrate the finite sample performance of our methods.

Suggested Citation

  • Ying Yan & Grace Y. Yi, 2016. "Analysis of error-prone survival data under additive hazards models: measurement error effects and adjustments," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(3), pages 321-342, July.
    • Handle: RePEc:spr:lifeda:v:22:y:2016:i:3:d:10.1007_s10985-015-9340-1
    DOI: 10.1007/s10985-015-9340-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10985-015-9340-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10985-015-9340-1?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
    ---><---

    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. Xiao Song & Yijian Huang, 2005. "On Corrected Score Approach for Proportional Hazards Model with Covariate Measurement Error," Biometrics, The International Biometric Society, vol. 61(3), pages 702-714, September.
    2. Yi Li & Louise Ryan, 2004. "Survival Analysis With Heterogeneous Covariate Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 724-735, January.
    3. Jiancheng Jiang & Zhou Haibo, 2007. "Additive hazard regression with auxiliary covariates," Biometrika, Biometrika Trust, vol. 94(2), pages 359-369.
    4. Liuquan Sun & Zhigang Zhang & Jianguo Sun, 2006. "Additive hazards regression of failure time data with covariate measurement errors," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(4), pages 497-509, November.
    5. Li Y. & Lin X., 2003. "Functional Inference in Frailty Measurement Error Models for Clustered Survival Data Using the SIMEX Approach," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 191-203, January.
    6. Hu, Chengcheng & Lin, D.Y., 2004. "Semiparametric Failure Time Regression With Replicates of Mismeasured Covariates," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 105-118, January.
    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. Xiaobo Wang & Jiayu Huang & Guosheng Yin & Jian Huang & Yuanshan Wu, 2023. "Double bias correction for high-dimensional sparse additive hazards regression with covariate measurement errors," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 115-141, January.

    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. Ying Yan & Grace Y. Yi, 2016. "A Class of Functional Methods for Error-Contaminated Survival Data Under Additive Hazards Models with Replicate Measurements," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 684-695, April.
    2. Sandip Barui & Grace Y. Yi, 2020. "Semiparametric methods for survival data with measurement error under additive hazards cure rate models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 421-450, July.
    3. 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.
    4. Yijian Huang & Ching†Yun Wang, 2018. "Cox regression with dependent error in covariates," Biometrics, The International Biometric Society, vol. 74(1), pages 118-126, March.
    5. Pamela A. Shaw & Ross L. Prentice, 2012. "Hazard Ratio Estimation for Biomarker-Calibrated Dietary Exposures," Biometrics, The International Biometric Society, vol. 68(2), pages 397-407, June.
    6. Wang, Xuan & Wang, Qihua, 2015. "Semiparametric linear transformation model with differential measurement error and validation sampling," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 67-80.
    7. Eil, David & Lien, Jaimie W., 2014. "Staying ahead and getting even: Risk attitudes of experienced poker players," Games and Economic Behavior, Elsevier, vol. 87(C), pages 50-69.
    8. Li-Pang Chen & Grace Y. Yi, 2021. "Semiparametric methods for left-truncated and right-censored survival data with covariate measurement error," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 481-517, June.
    9. Menggang Yu & Bin Nan, 2010. "Regression Calibration in Semiparametric Accelerated Failure Time Models," Biometrics, The International Biometric Society, vol. 66(2), pages 405-414, June.
    10. William Liu, 2023. "A Theory Guide to Using Control Functions to Instrument Hazard Models," Papers 2312.03165, arXiv.org.
    11. Zhuowei Sun & Hongyuan Cao & Li Chen, 2022. "Regression analysis of additive hazards model with sparse longitudinal covariates," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(2), pages 263-281, April.
    12. 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.
    13. Mengling Liu & Wenbin Lu & Chi-hong Tseng, 2010. "Cox Regression in Nested Case–Control Studies with Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 66(2), pages 374-381, June.
    14. Yih-Huei Huang & Chi-Chung Wen & Yu-Hua Hsu, 2015. "The Extensively Corrected Score for Measurement Error Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(4), pages 911-924, December.
    15. Ying Yan & Haibo Zhou & Jianwen Cai, 2017. "Improving efficiency of parameter estimation in case-cohort studies with multivariate failure time data," Biometrics, The International Biometric Society, vol. 73(3), pages 1042-1052, September.
    16. Yuhang Xu & Yehua Li & Xiao Song, 2016. "Locally Efficient Semiparametric Estimators for Proportional Hazards Models with Measurement Error," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 558-572, June.
    17. Xiaoping Shi & Yanyan Liu & Yuanshan Wu, 2014. "Auxiliary covariate in additive hazards regression for survival data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 101-113, March.
    18. Cheng Zheng & Yiwen Zhang & Ying Huang & Ross Prentice, 2023. "Using Controlled Feeding Study for Biomarker Development in Regression Calibration for Disease Association Estimation," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 57-113, April.
    19. 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.
    20. Li‐Pang Chen & Grace Y. Yi, 2021. "Analysis of noisy survival data with graphical proportional hazards measurement error models," Biometrics, The International Biometric Society, vol. 77(3), pages 956-969, September.

    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:spr:lifeda:v:22:y:2016:i:3:d:10.1007_s10985-015-9340-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.