IDEAS home Printed from https://ideas.repec.org/a/spr/metrik/v60y2004i1p73-91.html
   My bibliography  Save this article

Efficient rank tests for semiparametric competing risk models

Author

Listed:
  • Jan Beyersmann
  • Arnold Janssen
  • Claus-Dieter Mayer

Abstract

We consider a semiparametric competing risk model given by k independent survival times. The paper offers an asymptotic treatment of tests for the semiparametric null hypothesis of equality of the underlying risks. It turns out that modified rank tests are asymptotically efficient for certain semiparametric submodels, where the baseline hazard is a nuisance parameter. In addition, the asymptotic relative efficiency of the present tests is derived. A comparison of asymptotic power functions can then be used to classify various tests proposed earlier in the literature. For instance a chi-square type test is efficient for proportional hazards. Data driven tests of likelihood ratio type are proposed for cones of alternatives. We will consider certain stochastically increasing alternatives as a special example. The paper shows how the concept of local asymptotic normality of Le Cam works for hazard oriented models. Copyright Springer-Verlag 2004

Suggested Citation

  • Jan Beyersmann & Arnold Janssen & Claus-Dieter Mayer, 2004. "Efficient rank tests for semiparametric competing risk models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 60(1), pages 73-91, July.
  • Handle: RePEc:spr:metrik:v:60:y:2004:i:1:p:73-91
    DOI: 10.1007/s001840300297
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s001840300297
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s001840300297?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.

    Citations

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


    Cited by:

    1. Félix Belzunce & Eva-María Ortega & Franco Pellerey & José Ruiz, 2007. "On rankings and top choices in random utility models with dependent utilities," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 66(2), pages 197-212, 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:metrik:v:60:y:2004:i:1:p:73-91. 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: 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.