IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v154y2019ic11.html
   My bibliography  Save this article

Estimating equations of additive mean residual life model with censored length-biased data

Author

Listed:
  • Wu, Hongping
  • Cao, Xiaomin
  • Du, Caifeng

Abstract

Estimating equations for additive mean residual life model (AMRL) are proposed through the unique structure of length-biased data. Asymptotic properties of the estimators are stated. Small simulations are also conducted to evaluate their performance in a finite sample.

Suggested Citation

  • Wu, Hongping & Cao, Xiaomin & Du, Caifeng, 2019. "Estimating equations of additive mean residual life model with censored length-biased data," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
    • Handle: RePEc:eee:stapro:v:154:y:2019:i:c:11
    DOI: 10.1016/j.spl.2019.07.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715219301890
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2019.07.002?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. Kwun Chuen Gary Chan & Ying Qing Chen & Chong-Zhi Di, 2012. "Proportional mean residual life model for right-censored length-biased data," Biometrika, Biometrika Trust, vol. 99(4), pages 995-1000.
    2. Chiung-yu Huang & Jing Qin, 2012. "Composite Partial Likelihood Estimation Under Length-Biased Sampling, With Application to a Prevalent Cohort Study of Dementia," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(499), pages 946-957, September.
    3. Y. Q. Chen & S. Cheng, 2006. "Linear life expectancy regression with censored data," Biometrika, Biometrika Trust, vol. 93(2), pages 303-313, June.
    4. Chen, Ying Qing, 2007. "Additive Expectancy Regression," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 153-166, March.
    5. 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.
    6. Ma, Huijuan & Zhang, Feipeng & Zhou, Yong, 2015. "Composite estimating equation approach for additive risk model with length-biased and right-censored data," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 45-53.
    7. Sun, Liuquan & Zhang, Zhigang, 2009. "A Class of Transformed Mean Residual Life Models With Censored Survival Data," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 803-815.
    8. Xiaolin Chen & Qihua Wang, 2015. "Semiparametric Proportional Mean Residual Life Model With Censoring Indicators Missing at Random," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(24), pages 5161-5188, December.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    3. Yang, Guangren & Zhou, Yong, 2014. "Semiparametric varying-coefficient study of mean residual life models," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 226-238.
    4. Yixin Wang & Ying Qing Chen, 2019. "Estimating Attributable Life Expectancy Under the Proportional Mean Residual Life Model," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 659-676, December.
    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. Peng Jin & Anne Zeleniuch-Jacquotte & Mengling Liu, 2020. "Generalized mean residual life models for case-cohort and nested case-control studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 789-819, October.
    7. Ruiwen Zhou & Jianguo Sun, 2022. "Estimation of the Proportional Mean Residual Life Model with Internal and Longitudinal Covariates," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(3), pages 550-563, December.
    8. Zahra Mansourvar & Torben Martinussen & Thomas H. Scheike, 2015. "Semiparametric regression for restricted mean residual life under right censoring," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(12), pages 2597-2613, December.
    9. Chi Hyun Lee & Jing Ning & Yu Shen, 2019. "Model diagnostics for the proportional hazards model with length-biased data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(1), pages 79-96, January.
    10. Yu Shen & Jing Ning & Jing Qin, 2017. "Nonparametric and semiparametric regression estimation for length-biased survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 3-24, January.
    11. Zhang, Qiaozhen & Dai, Hongsheng & Fu, Bo, 2016. "A proportional hazards model for time-to-event data with epidemiological bias," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 224-236.
    12. Zhiping Qiu & Jing Qin & Yong Zhou, 2016. "Composite Estimating Equation Method for the Accelerated Failure Time Model with Length-biased Sampling Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 396-415, June.
    13. James H. McVittie & Ana F. Best & David B. Wolfson & David A. Stephens & Julian Wolfson & David L. Buckeridge & Shahinaz M. Gadalla, 2023. "Survival Modelling for Data From Combined Cohorts: Opening the Door to Meta Survival Analyses and Survival Analysis Using Electronic Health Records," International Statistical Review, International Statistical Institute, vol. 91(1), pages 72-87, April.
    14. Junshan Shen & Wei Liang & Shuyuan He, 2012. "Likelihood ratio inference for mean residual life," Statistical Papers, Springer, vol. 53(2), pages 401-408, May.
    15. Yifei Sun & Kwun Chuen Gary Chan & Jing Qin, 2018. "Simple and fast overidentified rank estimation for right†censored length†biased data and backward recurrence time," Biometrics, The International Biometric Society, vol. 74(1), pages 77-85, March.
    16. Yifan He & Yong Zhou, 2020. "Nonparametric and semiparametric estimators of restricted mean survival time under length-biased sampling," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 761-788, October.
    17. Fei Gao & Kwun Chuen Gary Chan, 2019. "Semiparametric regression analysis of length‐biased interval‐censored data," Biometrics, The International Biometric Society, vol. 75(1), pages 121-132, March.
    18. Xiaolin Chen & Qihua Wang, 2013. "Semiparametric proportional mean residual life model with covariates missing at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(3), pages 647-663, September.
    19. Chengbo Li & Yong Zhou, 2021. "The estimation for the general additive–multiplicative hazard model using the length-biased survival data," Statistical Papers, Springer, vol. 62(1), pages 53-74, February.
    20. Zamanzade, Elham & Parvardeh, Afshin & Asadi, Majid, 2019. "Estimation of mean residual life based on ranked set sampling," Computational Statistics & Data Analysis, Elsevier, vol. 135(C), pages 35-55.

    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:eee:stapro:v:154:y:2019:i:c:11. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.