Affiliations: [a] Department of Statistical Sciences, University of Padova, Padova, Italy | [b] Department for Women's and Children's Health, University of Padova, Padova, Italy | [c] Department of Economics and Statistics, University of Calabria, Arcavacata di Rende, Italy
Corresponding author: Pier Francesco Perri, Department of Economics and Statistics, University of Calabria, Via P. Bucci, 87036 Arcavacata di Rende, Italy. E-mail: [email protected].
Abstract: We discuss a number of privacy protection measures in situations where people are asked highly confidential questions concerning a quantitative sensitive variable. Most of the discussion will be devoted to the measures proposed by [8,11,12,30,31] with particular reference to the trade-off between the level of privacy disclosure and the efficiency of the estimates. Determination of the optimal sample size which would allow researchers to attain a predetermined level of efficiency and privacy is also considered.
Keywords: Randomized linear models, respondent privacy, efficiency, sample size