Advanced Search
MyIDEAS: Login to save this article or follow this journal

Modelling multivariate failure time associations in the presence of a competing risk

Contents:

Author Info

  • Karen Bandeen-Roche
Registered author(s):

    Abstract

    There has been much research on analysing multivariate failure times, but little that has accommodated failures that arise in the presence of a competing failure process. This paper studies the problem of describing associations among times to such failures. It proposes a modified conditional hazard ratio measure of association that is tailored to competing risks data, develops frailty models and a nonparametric method for describing the proposed measure, and contrasts estimation by proposed methods with the 'standard' of treating competing risks as independently censoring failure times due to targeted causes. The methods are investigated on simulated and real data. Copyright Biometrika Trust 2002, Oxford University Press.

    Download Info

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below under "Related research" whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Bibliographic Info

    Article provided by Biometrika Trust in its journal Biometrika.

    Volume (Year): 89 (2002)
    Issue (Month): 2 (June)
    Pages: 299-314

    as in new window
    Handle: RePEc:oup:biomet:v:89:y:2002:i:2:p:299-314

    Contact details of provider:
    Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK
    Fax: 01865 267 985
    Email:
    Web page: http://biomet.oxfordjournals.org/

    Order Information:
    Web: http://www.oup.co.uk/journals

    Related research

    Keywords:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

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

    Cited by:
    1. Gunky Kim & Mervyn J. Silvapulle & Paramsothy Silvapulle, 2007. "Semiparametric estimation of the dependence parameter of the error terms in multivariate regression," Monash Econometrics and Business Statistics Working Papers 1/07, Monash University, Department of Econometrics and Business Statistics.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:oup:biomet:v:89:y:2002:i:2:p:299-314. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press) or (Christopher F. Baum).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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