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A class of estimators for quantitative sensitive data

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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.

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Authors and Affiliations

  1. Department of Statistical Sciences, University of Padova, Via Cesare Battisti, 241, 35121, Padova, Italy

    Giancarlo Diana

  2. Department of Economics and Statistics, University of Calabria, Via P. Bucci, Cubo 0C, 87036, Arcavacata di Rende, Italy

    Pier Francesco Perri

Authors
  1. Giancarlo Diana
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  2. Pier Francesco Perri
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Correspondence to Pier Francesco Perri.

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Diana, G., Perri, P.F. A class of estimators for quantitative sensitive data. Stat Papers 52, 633–650 (2011). https://doi.org/10.1007/s00362-009-0273-1

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  • DOI: https://doi.org/10.1007/s00362-009-0273-1

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