IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v36y2009i12p1361-1367.html
   My bibliography  Save this article

An improved randomized response model: estimation of mean

Author

Listed:
  • Christopher Gjestvang
  • Sarjinder Singh

Abstract

In this paper, we suggest a new randomized response model useful for collecting information on quantitative sensitive variables such as drug use and income. The resultant estimator has been found to be better than the usual additive randomized response model. An interesting feature of the proposed model is that it is free from the known parameters of the scrambling variable unlike the additive model due to Himmelfarb and Edgell [S. Himmelfarb and S.E. Edgell, Additive constant model: a randomized response technique for eliminating evasiveness to quantitative response questions, Psychol. Bull. 87(1980), 525-530]. Relative efficiency of the proposed model has also been studied with the corresponding competitors. At the end, an application of the proposed model has been discussed.

Suggested Citation

  • Christopher Gjestvang & Sarjinder Singh, 2009. "An improved randomized response model: estimation of mean," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(12), pages 1361-1367.
    • Handle: RePEc:taf:japsta:v:36:y:2009:i:12:p:1361-1367
    DOI: 10.1080/02664760802684151
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/02664760802684151
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664760802684151?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tanveer AT & Housila PS, 2017. "An Improved Estimation Procedure of the Mean of a Sensitive Variable Using Auxiliary Information," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 3(2), pages 26-33, October.
    2. Muhammad Azeem & Sundus Hussain & Musarrat Ijaz & Najma Salahuddin, 2024. "An improved quantitative randomized response technique for data collection in sensitive surveys," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 329-341, February.
    3. Cheon-Sig Lee & Shu-Ching Su & Katrina Mondragon & Veronica I. Salinas & Monique L. Zamora & Stephen Andrew Sedory & Sarjinder Singh, 2016. "Comparison of Cramer–Rao lower bounds of variances for at least equal protection of respondents," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(2), pages 80-99, May.

    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:36:y:2009:i:12:p:1361-1367. 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.