IDEAS home Printed from https://ideas.repec.org/a/vrs/offsta/v39y2023i4p571-590n5.html
   My bibliography  Save this article

Application of Sampling Variance Smoothing Methods for Small Area Proportion Estimation

Author

Listed:
  • You Yong
  • Hidiroglou Mike

    (1 Statistics Canada, Ottawa, K1A 0T6, Canada)

Abstract

Sampling variance smoothing is an important topic in small area estimation. In this article, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis and simulation study indicate that the proposed sampling variance smoothing methods perform very well for small area estimation.

Suggested Citation

  • You Yong & Hidiroglou Mike, 2023. "Application of Sampling Variance Smoothing Methods for Small Area Proportion Estimation," Journal of Official Statistics, Sciendo, vol. 39(4), pages 571-590, December.
    • Handle: RePEc:vrs:offsta:v:39:y:2023:i:4:p:571-590:n:5
    DOI: 10.2478/jos-2023-0026
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/jos-2023-0026
    Download Restriction: no
    File URL: https://libkey.io/10.2478/jos-2023-0026?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
    ---><---

    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:vrs:offsta:v:39:y:2023:i:4:p:571-590:n:5. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.