IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v66y2004i3p719-733.html
   My bibliography  Save this article

A nonparametric test to compare survival distributions with covariate adjustment

Author

Listed:
  • Glenn Heller
  • E. S. Venkatraman

Abstract

Summary. The analysis of covariance is a technique that is used to improve the power of a k‐sample test by adjusting for concomitant variables. If the end point is the time of survival, and some observations are right censored, the score statistic from the Cox proportional hazards model is the method that is most commonly used to test the equality of conditional hazard functions. In many situations, however, the proportional hazards model assumptions are not satisfied. Specifically, the relative risk function is not time invariant or represented as a log‐linear function of the covariates. We propose an asymptotically valid k‐sample test statistic to compare conditional hazard functions which does not require the assumption of proportional hazards, a parametric specification of the relative risk function or randomization of group assignment. Simulation results indicate that the performance of this statistic is satisfactory. The methodology is demonstrated on a data set in prostate cancer.

Suggested Citation

  • Glenn Heller & E. S. Venkatraman, 2004. "A nonparametric test to compare survival distributions with covariate adjustment," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(3), pages 719-733, August.
    • Handle: RePEc:bla:jorssb:v:66:y:2004:i:3:p:719-733
    DOI: 10.1111/j.1467-9868.2004.b5364.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9868.2004.b5364.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9868.2004.b5364.x?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
    ---><---

    Citations

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


    Cited by:

    1. de Luna, Xavier & Johansson, Per, 2009. "Non-Parametric Inference for the Effect of a Treatment on Survival Times with Application in the Health and Social Sciences," IZA Discussion Papers 3966, Institute of Labor Economics (IZA).
    2. de Luna, Xavier & Johansson, Per, 2007. "Matching estimators for the effect of a treatment on survival times," Working Paper Series 2007:1, IFAU - Institute for Evaluation of Labour Market and Education Policy.

    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:bla:jorssb:v:66:y:2004:i:3:p:719-733. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.