Brazilian Journal of Probability and Statistics

Calibration estimation of adjusted Kuk’s randomized response model for sensitive attribute

Chang-Kyoon Son and Jong-Min Kim

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In this paper, we consider the calibration procedure for Su et al.’s [Sociol. Methods Res. 44 (2014) DOI:10.1177/0049124114554459] adjusted Kuk randomized response (RR) technique by using auxiliary information such as gender or age group of respondents associated with the variable of interest. Our proposed calibration method can overcome the problems such as noncoverage and nonresponse. From the efficiency comparison study, we show that the calibrated adjusted Kuk’s RR estimators are more efficient than that of Su et al. [Sociol. Methods Res. 44 (2014) DOI:10.1177/0049124114554459], when the known population cell and marginal counts of auxiliary information are used for the calibration procedure.

Article information

Braz. J. Probab. Stat., Volume 31, Number 1 (2017), 160-178.

Received: January 2015
Accepted: January 2016
First available in Project Euclid: 25 January 2017

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Zentralblatt MATH identifier

Randomized response technique adjusted Kuk’s RRT calibration estimator post-stratification


Son, Chang-Kyoon; Kim, Jong-Min. Calibration estimation of adjusted Kuk’s randomized response model for sensitive attribute. Braz. J. Probab. Stat. 31 (2017), no. 1, 160--178. doi:10.1214/16-BJPS307.

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  • Cochran, W. G. (1977). Sampling Techniques, 3rd ed. New York: John Wiley and Sons.
  • Deville, J. C. and Särndal, C. E. (1992). Calibration estimators in survey sampling. J. Amer. Statist. Assoc. 87, 376–382.
  • Deville, J. C., Särndal, C. E. and Sautory, O. (1993). Generalized ranking procedures in survey sampling. J. Amer. Statist. Assoc. 88, 1013–1020.
  • Kuk, A. Y. C. (1990). Asking sensitive questions indirectly. Biomerika 77, 436–438.
  • Son, C. K., Hong, K. H., Lee, G. S. and Kim, J. M. (2010). The calibration for randomized response estimator. Comm. Statist. Theory Methods 39, 3163–3177.
  • Su, S. C., Sedory, S. A. and Singh, S. (2014). Kuk’s model adjusted for protection and efficiency. Sociol. Methods Res. DOI:10.1177/0049124114554459.
  • Tracy, D. S., Singh, H. E. and Singh, R. (1999). Constructing an unbiased estimator of population mean in finite populations using auxiliary information. Statist. Papers 40, 363–368.
  • Warner, S. L. (1965). Randomized response; a survey technique for eliminating evasive answer bias. J. Amer. Statist. Assoc. 60, 63–69.