IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v52y2025i4p868-893.html
   My bibliography  Save this article

A class of infinite number of unbiased estimators using weighted squared distance for two-deck randomized response model

Author

Listed:
  • Daryan Naatjes
  • Stephen A. Sedory
  • Sarjinder Singh

Abstract

We develop a collection of unbiased estimators for the proportion of a population bearing a sensitive characteristic using a randomized response technique with two decks of cards for any choice of weights. The efficiency of the estimator depends on the weights, and we demonstrate how to find an optimal choice. The coefficients of skewness and kurtosis are introduced. We support our findings with a simulation study that models a real survey dataset. We suggest that a careful choice of such weights can also lead to all estimates of proportion lying between [0, 1]. In addition, we illustrate the use of the estimators in a recent study that estimates the proportion of students, 18 years and over, who had returned to the campus and tested positive for COVID-19.

Suggested Citation

  • Daryan Naatjes & Stephen A. Sedory & Sarjinder Singh, 2025. "A class of infinite number of unbiased estimators using weighted squared distance for two-deck randomized response model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 52(4), pages 868-893, March.
    • Handle: RePEc:taf:japsta:v:52:y:2025:i:4:p:868-893
    DOI: 10.1080/02664763.2024.2399574
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2024.2399574
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2024.2399574?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:japsta:v:52:y:2025:i:4:p:868-893. 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/CJAS20 .

    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.