IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v46y2017i3p565-585.html
   My bibliography  Save this article

A Dexterous Optional Randomized Response Model

Author

Listed:
  • Tanveer A. Tarray
  • Housila P. Singh
  • Zaizai Yan

Abstract

This article addresses the problem of estimating the proportion π S of the population belonging to a sensitive group using optional randomized response technique in stratified sampling based on Mangat model that has proportional and Neyman allocation and larger gain in efficiency. Numerically, it is found that the suggested model is more efficient than Kim and Warde stratified randomized response model and Mangat model.

Suggested Citation

  • Tanveer A. Tarray & Housila P. Singh & Zaizai Yan, 2017. "A Dexterous Optional Randomized Response Model," Sociological Methods & Research, , vol. 46(3), pages 565-585, August.
    • Handle: RePEc:sae:somere:v:46:y:2017:i:3:p:565-585
    DOI: 10.1177/0049124115605332
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124115605332
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124115605332?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
    ---><---

    References listed on IDEAS

    as
    1. Jong-Min Kim & Matthew Elam, 2007. "A stratified unrelated question randomized response model," Statistical Papers, Springer, vol. 48(2), pages 215-233, April.
    2. D. Tracy & S. Osahan, 1995. "A partial randomized response strategy," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 4(2), pages 315-321, December.
    3. Jong-Min Kim & M. E. Elam, 2005. "A two-stage stratified Warner’s randomized response model using optimal allocation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 61(1), pages 1-7, February.
    4. Singh, Housila P. & Tarray, Tanveer A., 2014. "A dexterous randomized response model for estimating a rare sensitive attribute using Poisson distribution," Statistics & Probability Letters, Elsevier, vol. 90(C), pages 42-45.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Oluseun Odumade & Sarjinder Singh, 2010. "An Alternative to the Bar-Lev, Bobovitch, and Boukai Randomized Response Model," Sociological Methods & Research, , vol. 39(2), pages 206-221, November.
    2. Horng-Jinh Chang & Mei-Pei Kuo, 2012. "Estimation of population proportion in randomized response sampling using weighted confidence interval construction," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(5), pages 655-672, July.
    3. Jong-Min Kim & Matthew Elam, 2007. "A stratified unrelated question randomized response model," Statistical Papers, Springer, vol. 48(2), pages 215-233, April.
    4. Kuo-Chung Huang, 2008. "Estimation for sensitive characteristics using optional randomized response technique," Quality & Quantity: International Journal of Methodology, Springer, vol. 42(5), pages 679-686, October.
    5. Sally Abdelfatah & Reda Mazloum, 2016. "An efficient two-stage randomized response model under stratified random sampling," Mathematical Population Studies, Taylor & Francis Journals, vol. 23(4), pages 222-238, October.
    6. Jun-Wu Yu & Guo-Liang Tian & Man-Lai Tang, 2008. "Two new models for survey sampling with sensitive characteristic: design and analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 67(3), pages 251-263, April.
    7. Kumari Priyanka & Pidugu Trisandhya & Richa Mittal, 2018. "Dealing sensitive characters on successive occasions through a general class of estimators using scrambled response techniques," METRON, Springer;Sapienza Università di Roma, vol. 76(2), pages 203-230, August.
    8. Mausumi Bose, 2015. "Respondent privacy and estimation efficiency in randomized response surveys for discrete-valued sensitive variables," Statistical Papers, Springer, vol. 56(4), pages 1055-1069, November.
    9. Singh, Housila P. & Tarray, Tanveer A., 2014. "A dexterous randomized response model for estimating a rare sensitive attribute using Poisson distribution," Statistics & Probability Letters, Elsevier, vol. 90(C), pages 42-45.
    10. Housila P. Singh & Tanveer A. Tarray, 2015. "An Efficient Alternative Mixed Randomized Response Procedure," Sociological Methods & Research, , vol. 44(4), pages 706-722, November.

    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:sae:somere:v:46:y:2017:i:3:p:565-585. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: SAGE Publications (email available below). General contact details of provider: .

    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.