IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v45y2016i8p2368-2377.html
   My bibliography  Save this article

Resampling method to estimate intra-cluster correlation for clustered binary data

Author

Listed:
  • Hrishikesh Chakraborty
  • Pranab K. Sen

Abstract

Various methods have been proposed to estimate intra-cluster correlation coefficients (ICCs) for correlated binary data, and many are very sensitive to the type of design and underlying distributional assumptions. We proposed a new method to estimate ICC and its 95% confidence intervals based on resampling principles and U-statistics, where we resampled with replacement pairs of individuals from within and between clusters. We concluded from our simulation study that the resampling-based estimates approximate the population ICC more precisely than the analysis of variance and method of moments techniques for different event rates, varying number of clusters, and cluster sizes.

Suggested Citation

  • Hrishikesh Chakraborty & Pranab K. Sen, 2016. "Resampling method to estimate intra-cluster correlation for clustered binary data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(8), pages 2368-2377, April.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:8:p:2368-2377
    DOI: 10.1080/03610926.2013.870202
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2013.870202
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2013.870202?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:45:y:2016:i:8:p:2368-2377. 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.