Advanced Search
MyIDEAS: Login

Association estimation for clustered failure time data with a cure fraction

Contents:

Author Info

  • Chen, Chyong-Mei
  • Lu, Tai-Fang C.
  • Hsu, Chao-Min
Registered author(s):

    Abstract

    Substantial research has been devoted to developing methodology for inferring the association of clustered failure time data. However, in the study of familial disease, there may be a proportion of patients cured or nonsusceptible to the disease. Thus, it is necessary to simultaneously consider two types of association, i.e., the association of the susceptibility of the individuals, and that of the ages at onset between the susceptible individuals. In this paper, we consider the pairwise association in both types of association to reduce the mathematical intractability and the difficulty in specifying the full correlation structure. The former association is measured by the pairwise odds ratio of the binary cure statuses, and the latter by the bivariate Clayton copula with a semiparametric marginal regression model for any pair of correlated failure times. For the marginal model, it is formulated as a fairly general semiparametric regression cure model. A two-stage estimation procedure is adopted for the association estimation. We establish the consistency and asymptotic normality of the estimators for these two types of association. Simulation studies are conducted to assess finite sample properties, and the proposed method is illustrated by a subset of the data in the Australian Twins Study.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.sciencedirect.com/science/article/pii/S0167947312002575
    Download Restriction: Full text for ScienceDirect subscribers only.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 57 (2013)
    Issue (Month): 1 ()
    Pages: 210-222

    as in new window
    Handle: RePEc:eee:csdana:v:57:y:2013:i:1:p:210-222

    Contact details of provider:
    Web page: http://www.elsevier.com/locate/csda

    Related research

    Keywords: Clayton copula; Cure models; Estimating equations; Marginal approach; Pairwise likelihood; Two-stage estimation;

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Chen, Chyong-Mei & Lu, Tai-Fang C., 2012. "Marginal analysis of multivariate failure time data with a surviving fraction based on semiparametric transformation cure models," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 645-655.
    2. Wenbin Lu, 2004. "On semiparametric transformation cure models," Biometrika, Biometrika Trust, vol. 91(2), pages 331-343, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    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:eee:csdana:v:57:y:2013:i:1:p:210-222. 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: (Zhang, Lei).

    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.