This paper describes a new procedure to unbiasedly estimate the proportions of t population groups, which at least one is very small and then it can be considered a rare group. This procedure guarantees the privacy protection of the interviewees, as it is based on an extension of the Warner randomized response model. As the estimation regards rare groups, the sampling design considered is the inverse sampling. Some characteristics of the proposed estimators are investigated.
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Singh, H.P., Mathur, N.: On inverse binomial randomized response technique. J. Indian Soc. Agric. Stat.
59, 192–198 (2005)
Singh, H.P., Mathur, N.: An improved estimation procedure for estimating the proportion of a population possessing sensitive attribute in unrelated question randomized response technique. Brasilian J. Probab. Stat.
20, 93–110 (2006)
Sukhatme, P.V., Sukhatme, B.V., Sukhatme, S., Asok, C.: Sampling Theory of Surveys with Applications, 3rd edn. Iowa State University Press, Ames, Iowa (USA) and the Indian Society of Agricultural Statistics, New Delhi, India (1984)
Van der Heijden, P.G.M., Bockenholt, U.: Applications of randomized response methodology in e-commerce. In: Jank, W., Shmueli, G. (eds.) Statistical Methods in e-Commerce Research, pp. 401–416. Wiley, New York (2008)
Van der Heijden, P.G.M., Van Gils, G., Bouts, J., Hox, J.J.: A comparison of randomized response, computer-assisted self-interview, and face-to-face direct questioning. Sociol. Methods Res.
28, 505–537 (2000)
Warner, S.L.: Randomized response: A survey technique for eliminating evasive answer bias. J. Am. Stat. Assoc.
60, 63–69 (1965)
Über dieses Kapitel
A Multi-proportion Randomized Response Model Using the Inverse Sampling