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Assessing the disclosure protection provided by misclassification for survey microdata

Shlomo, Natalie and Skinner, Chris (2009) Assessing the disclosure protection provided by misclassification for survey microdata , Southampton, UK Southampton Statistical Sciences Reseach Institute 25pp. (S3RI Methodology Working Papers, M09/14).

Record type: Monograph (Working Paper)


Government statistical agencies often apply statistical disclosure limitation techniques to survey microdata to protect confidentiality. There is a need for ways to assess the protection provided. This paper develops some simple methods for disclosure limitation techniques which perturb the values of categorical identifying variables. The methods are applied in numerical experiments based upon census data from the United Kingdom which are subject to two perturbation techniques: data swapping and the post randomisation method. Some simplifying approximations to the measure of risk are found to work well in capturing the impacts of these techniques. These approximations provide simple extensions of existing risk assessment methods based upon Poisson log-linear models. A numerical experiment is also undertaken to assess the impact of multivariate misclassification with an increasing number of identifying variables. The methods developed in this paper may also be used to obtain more realistic assessments of risk which take account of the kinds of measurement and other non-sampling errors commonly arising in surveys.

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Published date: 7 August 2009
Keywords: disclosure risk, identification risk, log linear model, measurement error, post randomization method, data swapping.


Local EPrints ID: 67250
PURE UUID: eed9c863-a4f5-4848-8b38-0860d0223749

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Date deposited: 07 Aug 2009
Last modified: 19 Jul 2017 00:20

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Author: Natalie Shlomo
Author: Chris Skinner

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