Randomized response methods for quantitative sensitive data are treated in an unified approach which includes the use of auxiliary information at the estimation stage. A class of estimators for the mean of a sensitive variable is proposed under a generic randomization model and the optimum estimator is obtained. Some special models are discussed in detail.To evaluate the degree of respondents' confidentiality in models using auxiliary variables, a new measure of privacy protection is introduced. Different models are then compared both from the perspective of efficiency and privacy protection.

A class of estimators for quantitative sensitive data

PERRI, PIER FRANCESCO
2011-01-01

Abstract

Randomized response methods for quantitative sensitive data are treated in an unified approach which includes the use of auxiliary information at the estimation stage. A class of estimators for the mean of a sensitive variable is proposed under a generic randomization model and the optimum estimator is obtained. Some special models are discussed in detail.To evaluate the degree of respondents' confidentiality in models using auxiliary variables, a new measure of privacy protection is introduced. Different models are then compared both from the perspective of efficiency and privacy protection.
2011
privacy protection measures; regression-type estimator; scrambled responses; simulation; auxiliary variable
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/126217
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