IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v49y2020i1p116-124.html
   My bibliography  Save this article

Sample size calculation for count outcomes in cluster randomization trials with varying cluster sizes

Author

Listed:
  • Jijia Wang
  • Song Zhang
  • Chul Ahn

Abstract

In many cluster randomization studies, cluster sizes are not fixed and may be highly variable. For those studies, sample size estimation assuming a constant cluster size may lead to under-powered studies. Sample size formulas have been developed to incorporate the variability in cluster size for clinical trials with continuous and binary outcomes. Count outcomes frequently occur in cluster randomized studies. In this paper, we derive a closed-form sample size formula for count outcomes accounting for the variability in cluster size. We compare the performance of the proposed method with the average cluster size method through simulation. The simulation study shows that the proposed method has a better performance with empirical powers and type I errors closer to the nominal levels.

Suggested Citation

  • Jijia Wang & Song Zhang & Chul Ahn, 2020. "Sample size calculation for count outcomes in cluster randomization trials with varying cluster sizes," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(1), pages 116-124, January.
  • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:1:p:116-124
    DOI: 10.1080/03610926.2018.1532004
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2018.1532004
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03610926.2018.1532004?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.

    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:taf:lstaxx:v:49:y:2020:i:1:p:116-124. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.