Bayesian estimation of proportion and sensitivity level in randomized response procedures
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DOI: 10.1007/s00184-009-0242-7
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References listed on IDEAS
- Migon, Helio S. & Tachibana, Vilma M., 1997. "Bayesian approximations in randomized response model," Computational Statistics & Data Analysis, Elsevier, vol. 24(4), pages 401-409, June.
- 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.
- Shaul Bar-Lev & Elizabeta Bobovich & Benzion Boukai, 2003. "A common conjugate prior structure for several randomized response models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 101-113, June.
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Cited by:
- 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.
- 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.
- Heiko Groenitz, 2015. "Using prior information in privacy-protecting survey designs for categorical sensitive variables," Statistical Papers, Springer, vol. 56(1), pages 167-189, February.
- Hua Xin & Jianping Zhu & Tzong-Ru Tsai & Chieh-Yi Hung, 2021. "Hierarchical Bayesian Modeling and Randomized Response Method for Inferring the Sensitive-Nature Proportion," Mathematics, MDPI, vol. 9(19), pages 1-12, October.
- Lucio Barabesi & Giancarlo Diana & Pier Perri, 2013. "Design-based distribution function estimation for stigmatized populations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(7), pages 919-935, October.
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Keywords
Randomized response method; Proportion estimation; Sensitivity level estimation; Bayesian inference; Beta distribution mixture;All these keywords.
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