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.

Polisicchio, M., Porro, F. (2014). A Multi-proportion Randomized Response Model Using the Inverse Sampling. In Contributions to Sampling Statistics (pp. 199-218). Springer International Publishing [10.1007/978-3-319-05320-2_13].

A Multi-proportion Randomized Response Model Using the Inverse Sampling

POLISICCHIO, MARCELLA
Primo
;
PORRO, FRANCESCO
Ultimo
2014

Abstract

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.
Capitolo o saggio
Inverse sampling, Randomized response, Sensitive questions
English
Contributions to Sampling Statistics
2014
978-3-319-05319-6
Springer International Publishing
199
218
Polisicchio, M., Porro, F. (2014). A Multi-proportion Randomized Response Model Using the Inverse Sampling. In Contributions to Sampling Statistics (pp. 199-218). Springer International Publishing [10.1007/978-3-319-05320-2_13].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/103579
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