The Randomized Response (RR) technique is a well-established interview procedure which guarantees privacy protection in social surveys dealing with sensitive items. The RR method assumes a stochastic mechanism to create uncertainty about the true status of the respondents in order to ensure privacy protection and to avoid tendencies to dissimulate or respond in a socially desirable direction. A very general model for the RR method was introduced by Franklin (Commun Stat Theory Methods 18:489–505, 1989)when a single-sensitive question is under study.However, since social surveys are often based on questionnaires containing more than a singlesensitive question, the analysis of multivariate RR data is of considerable interest. This paper focuses on the generalization of the Franklin model in a multiple-sensitive question setting and on related inferential issues.
Barabesi, L., Franceschi, S., Marcheselli, M. (2012). A randomized response procedure for multiple-sensitive questions. STATISTICAL PAPERS, 53, 703-718 [10.1007/s00362-011-0374-5].
A randomized response procedure for multiple-sensitive questions
BARABESI, LUCIO;Franceschi S.;MARCHESELLI, MARZIA
2012-01-01
Abstract
The Randomized Response (RR) technique is a well-established interview procedure which guarantees privacy protection in social surveys dealing with sensitive items. The RR method assumes a stochastic mechanism to create uncertainty about the true status of the respondents in order to ensure privacy protection and to avoid tendencies to dissimulate or respond in a socially desirable direction. A very general model for the RR method was introduced by Franklin (Commun Stat Theory Methods 18:489–505, 1989)when a single-sensitive question is under study.However, since social surveys are often based on questionnaires containing more than a singlesensitive question, the analysis of multivariate RR data is of considerable interest. This paper focuses on the generalization of the Franklin model in a multiple-sensitive question setting and on related inferential issues.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/41824
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