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Statistical Disclosure Control using Post Randomisation: Variants and Measures for Disclosure Risk

Statistical Disclosure Control using Post Randomisation: Variants and Measures for Disclosure Risk
Statistical Disclosure Control using Post Randomisation: Variants and Measures for Disclosure Risk
This paper discusses the post randomisation method (PRAM) as a method for disclosure control. PRAM protects the privacy of respondent by misclassifying specific variables before data are released to researchers outside the statistical agency. Two variants of the initial idea of PRAM are discussed concerning the information about the misclassification that is given along with the released data. The first variant concerns calibration probabilities and the second variant concerns misclassification proportions. The paper shows that the distinction between the univariate case and multivariate case is important. Additionally, the paper discusses two measures for disclosure risk when PRAM is applied.
M04/01
Southampton Statistical Sciences Research Institute, University of Southampton
Hout, Ardo van den
ef715b14-f442-44a8-96b0-9b5fee020c7f
Elamir, Elsayed A. H.
6c4d439d-372c-4f65-9aab-27b6e0d2fdcc
Hout, Ardo van den
ef715b14-f442-44a8-96b0-9b5fee020c7f
Elamir, Elsayed A. H.
6c4d439d-372c-4f65-9aab-27b6e0d2fdcc

Hout, Ardo van den and Elamir, Elsayed A. H. (2004) Statistical Disclosure Control using Post Randomisation: Variants and Measures for Disclosure Risk (S3RI Methodology Working Papers, M04/01) Southampton, UK. Southampton Statistical Sciences Research Institute, University of Southampton 28pp.

Record type: Monograph (Working Paper)

Abstract

This paper discusses the post randomisation method (PRAM) as a method for disclosure control. PRAM protects the privacy of respondent by misclassifying specific variables before data are released to researchers outside the statistical agency. Two variants of the initial idea of PRAM are discussed concerning the information about the misclassification that is given along with the released data. The first variant concerns calibration probabilities and the second variant concerns misclassification proportions. The paper shows that the distinction between the univariate case and multivariate case is important. Additionally, the paper discusses two measures for disclosure risk when PRAM is applied.

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Published date: 2004

Identifiers

Local EPrints ID: 8174
URI: http://eprints.soton.ac.uk/id/eprint/8174
PURE UUID: 358a7480-720f-414b-8027-f71137f622bd

Catalogue record

Date deposited: 11 Jul 2004
Last modified: 15 Mar 2024 04:51

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Contributors

Author: Ardo van den Hout
Author: Elsayed A. H. Elamir

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