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A new randomized response model

Author

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  • Christopher R. Gjestvang
  • Sarjinder Singh

Abstract

Summary. We suggest an efficient randomized response model that can easily be adjusted to be more efficient than the Warner, Mangat and Singh, and Mangat methods by selecting certain parameters of the proposed randomization device.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:jorssb:v:68:y:2006:i:3:p:523-530
    DOI: 10.1111/j.1467-9868.2006.00554.x
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    Citations

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    Cited by:

    1. 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.
    2. Lucio Barabesi & Sara Franceschi & Marzia Marcheselli, 2012. "A randomized response procedure for multiple-sensitive questions," Statistical Papers, Springer, vol. 53(3), pages 703-718, August.
    3. 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.
    4. Michael Lee Johnson & Stephen A. Sedory & Sarjinder Singh, 2019. "Alternative Methods to Make Efficient Use of Two Decks of Cards in Randomized Response Sampling," Sociological Methods & Research, , vol. 48(1), pages 62-91, February.
    5. Singh Housila P. & Gorey Swarangi M., 2017. "A Generalized Randomized Response Model," Statistics in Transition New Series, Statistics Poland, vol. 18(4), pages 669-686, December.
    6. 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.
    7. Esponda, Fernando & Guerrero, Victor M., 2009. "Surveys with negative questions for sensitive items," Statistics & Probability Letters, Elsevier, vol. 79(24), pages 2456-2461, December.
    8. Sarjinder Singh, 2020. "Reply to the correction by Grover and Kaur: a new randomized response model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 865-868, July.
    9. 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.
    10. Truong-Nhat Le & Shen-Ming Lee & Phuoc-Loc Tran & Chin-Shang Li, 2023. "Randomized Response Techniques: A Systematic Review from the Pioneering Work of Warner (1965) to the Present," Mathematics, MDPI, vol. 11(7), pages 1-26, April.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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, Statistics Poland, vol. 18(2), pages 193-210, June.
    16. Kajal Dihidar & Manjima Bhattacharya, 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.
    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. 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.
    19. 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.
    20. Shu-Hui Hsieh & Shen-Ming Lee & Su-Hao Tu, 2018. "Randomized response techniques for a multi-level attribute using a single sensitive question," Statistical Papers, Springer, vol. 59(1), pages 291-306, March.
    21. 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.

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