IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v39y2010i2p206-221.html
   My bibliography  Save this article

An Alternative to the Bar-Lev, Bobovitch, and Boukai Randomized Response Model

Author

Listed:
  • Oluseun Odumade

    (Cornell University, Ithaca, NY, USA)

  • Sarjinder Singh

    (Texas A&M University-Kingsville, Kingsville, TX, USA, kuss2008@tamuk.edu)

Abstract

In this article, an alternative randomized response model is proposed. The proposed model is found to be more efficient than the randomized response model studied by Bar-Lev, Bobovitch, and Boukai (2004). The relative efficiency of the proposed model is studied with respect to the Bar-Lev et al. (2004) model under various situations.

Suggested Citation

  • 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.
  • Handle: RePEc:sae:somere:v:39:y:2010:i:2:p:206-221
    DOI: 10.1177/0049124110378094
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124110378094
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0049124110378094?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 & 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.
    2. Shaul K. Bar-Lev & Elizabeta Bobovitch & Benzion Boukai, 2004. "A note on randomized response models for quantitative data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 60(3), pages 255-260, November.
    3. Christopher R. Gjestvang & Sarjinder Singh, 2006. "A new randomized response model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(3), pages 523-530, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Antonio Arcos & María del Rueda & Sarjinder Singh, 2015. "A generalized approach to randomised response for quantitative variables," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 1239-1256, May.
    2. 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.
    3. Housila P. Singh & Swarangi M. Gorey, 2017. "A Generalized Randomized Response Model," Statistics in Transition New Series, Polish Statistical Association, vol. 18(4), pages 669-686, December.

    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. Antonio Arcos & María del Rueda & Sarjinder Singh, 2015. "A generalized approach to randomised response for quantitative variables," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 1239-1256, May.
    2. Giancarlo Diana & Pier Francesco Perri, 2010. "New scrambled response models for estimating the mean of a sensitive quantitative character," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(11), pages 1875-1890.
    3. María del Mar Rueda & Beatriz Cobo & Antonio Arcos, 2021. "Regression Models in Complex Survey Sampling for Sensitive Quantitative Variables," Mathematics, MDPI, vol. 9(6), pages 1-13, March.
    4. Kuo-Chung Huang, 2010. "Unbiased estimators of mean, variance and sensitivity level for quantitative characteristics in finite population sampling," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 71(3), pages 341-352, May.
    5. Housila P. Singh & Swarangi M. Gorey, 2017. "A Generalized Randomized Response Model," Statistics in Transition New Series, Polish Statistical Association, vol. 18(4), pages 669-686, December.
    6. Erum Zahid & Javid Shabbir & Sat Gupta & Ronald Onyango & Sadia Saeed, 2022. "A generalized class of estimators for sensitive variable in the presence of measurement error and non-response," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-19, January.
    7. Dihidar Kajal & Bhattacharya Manjima, 2017. "Estimating Sensitive Population Proportion Using a Combination of Binomial and Hypergeometric Randomized Responses by Direct and Inverse Mechanism," Statistics in Transition New Series, Polish Statistical Association, vol. 18(2), pages 193-210, June.
    8. María del Mar García Rueda & Pier Francesco Perri & Beatriz Rodríguez Cobo, 2018. "Advances in estimation by the item sum technique using auxiliary information in complex surveys," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(3), pages 455-478, July.
    9. Amitava Saha, 2011. "An optional scrambled randomized response technique for practical surveys," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(2), pages 139-149, March.
    10. Jong-Min Kim & Matthew Elam, 2007. "A stratified unrelated question randomized response model," Statistical Papers, Springer, vol. 48(2), pages 215-233, April.
    11. Lucio Barabesi & Marzia Marcheselli, 2010. "Bayesian estimation of proportion and sensitivity level in randomized response procedures," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 72(1), pages 75-88, July.
    12. Lucio Barabesi & Giancarlo Diana & Pier Perri, 2015. "Gini index estimation in randomized response surveys," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(1), pages 45-62, January.
    13. Shu-Ching Su & Stephen A. Sedory & Sarjinder Singh, 2015. "Kuk’s Model Adjusted for Protection and Efficiency," Sociological Methods & Research, , vol. 44(3), pages 534-551, August.
    14. Singh Housila P. & Gorey Swarangi M., 2017. "A Generalized Randomized Response Model," Statistics in Transition New Series, Polish Statistical Association, vol. 18(4), pages 669-686, December.
    15. 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.
    16. Zawar Hussain & Mashail M. Al-Sobhi & Bander Al-Zahrani & Housila P. Singh & Tanveer A. Tarray, 2016. "Improved randomized response in additive scrambling models," Mathematical Population Studies, Taylor & Francis Journals, vol. 23(4), pages 205-221, October.
    17. Shu-Hui Hsieh & Shen-Ming Lee & Chin-Shang Li & Su-Hao Tu, 2016. "An alternative to unrelated randomized response techniques with logistic regression analysis," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(4), pages 601-621, November.
    18. Singh, Sarjinder & Kim, Jong-Min, 2011. "A pseudo-empirical log-likelihood estimator using scrambled responses," Statistics & Probability Letters, Elsevier, vol. 81(3), pages 345-351, March.
    19. Priyanka Kumari & Trisandhya Pidugu, 2019. "Modelling Sensitive Issues On Successive Waves," Statistics in Transition New Series, Polish Statistical Association, vol. 20(1), pages 41-65, March.
    20. Sarjinder Singh & Stephen A. Sedory, 2011. "Cramer-Rao Lower Bound of Variance in Randomized Response Sampling," Sociological Methods & Research, , vol. 40(3), pages 536-546, August.

    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:39:y:2010:i:2:p:206-221. 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.