IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v75y2019i4p1276-1287.html
   My bibliography  Save this article

On null hypotheses in survival analysis

Author

Listed:
  • Mats J. Stensrud
  • Kjetil Røysland
  • Pål C. Ryalen

Abstract

The conventional nonparametric tests in survival analysis, such as the log‐rank test, assess the null hypothesis that the hazards are equal at all times. However, hazards are hard to interpret causally, and other null hypotheses are more relevant in many scenarios with survival outcomes. To allow for a wider range of null hypotheses, we present a generic approach to define test statistics. This approach utilizes the fact that a wide range of common parameters in survival analysis can be expressed as solutions of differential equations. Thereby, we can test hypotheses based on survival parameters that solve differential equations driven by cumulative hazards, and it is easy to implement the tests on a computer. We present simulations, suggesting that our tests perform well for several hypotheses in a range of scenarios. As an illustration, we apply our tests to evaluate the effect of adjuvant chemotherapies in patients with colon cancer, using data from a randomized controlled trial.

Suggested Citation

  • Mats J. Stensrud & Kjetil Røysland & Pål C. Ryalen, 2019. "On null hypotheses in survival analysis," Biometrics, The International Biometric Society, vol. 75(4), pages 1276-1287, December.
    • Handle: RePEc:bla:biomet:v:75:y:2019:i:4:p:1276-1287
    DOI: 10.1111/biom.13102
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/biom.13102
    Download Restriction: no
    File URL: https://libkey.io/10.1111/biom.13102?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. Larry F. León & Ray Lin & Keaven M. Anderson, 2020. "On Weighted Log-Rank Combination Tests and Companion Cox Model Estimators," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(2), pages 225-245, July.

    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:biomet:v:75:y:2019:i:4:p:1276-1287. 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: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.