IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v96y2009i1p237-242.html
   My bibliography  Save this article

A note on cause-specific residual life

Author

Listed:
  • J.-H. Jeong
  • J. P. Fine

Abstract

In medical research, investigators often wish to characterize the distributions of remaining lifetimes. While nonparametric analyses of residual life distributions have been widely studied with independently right-censored data, residual life analysis has not been examined in the competing risks setting, with multiple, potentially dependent, failure types. We define the cause-specific residual life distribution as the residual cumulative incidence function conditionally on survival to a given time. Because of the improper form of the cause-specific distribution, the mean cause-specific residual lifetime does not exist, theoretically. We develop nonparametric inferences for the cause-specific residual life function and its corresponding quantiles, which may exist. Theoretical justification, including uniform consistency and weak convergence, is established. Simulation studies and a breast cancer data analysis demonstrate the practical utility of the methods. Copyright 2009, Oxford University Press.

Suggested Citation

  • J.-H. Jeong & J. P. Fine, 2009. "A note on cause-specific residual life," Biometrika, Biometrika Trust, vol. 96(1), pages 237-242.
    • Handle: RePEc:oup:biomet:v:96:y:2009:i:1:p:237-242
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/biomet/asn063
    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.

    Citations

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


    Cited by:

    1. P. Sankaran & N. Midhu, 2016. "Testing exponentiality using mean residual quantile function," Statistical Papers, Springer, vol. 57(1), pages 235-247, March.
    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. Lee, Minjung & Han, Junhee, 2016. "Covariate-adjusted quantile inference with competing risks," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 57-63.

    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:oup:biomet:v:96:y:2009:i:1:p:237-242. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/biomet .

    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.