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A Per-Record Risk of Disclosure Using a Poisson-Inverse Gaussian Regression Model
Stockholm University, Faculty of Social Sciences, Department of Statistics.
2002 (English)Report (Other academic)
Abstract [en]

Per-record measures of disclosure risk have potential uses in statistical disclosure control programs as a means of identifying sensitive or atypical records in public-use microdata files. A measure intended for sample data based on the Poisson-inverse Gaussian distribution and overdispersed log-linear modeling is presented. An empirical example indicates that the proposed model performs approximately as well as the Poisson-lognormal model of Skinner and Holmes (1998) and may be a tractable alternative as the required computational effort is significantly smaller. It is also demonstrated how to extend the application to take into account population level information. The empirical results indicate that using population level information sharpens the risk measure.

Place, publisher, year, edition, pages
2002. , 25 p.
Series
Research Report / Department of Statistics, Stockholm University, ISSN 0280-7564 ; 2002:9
Keyword [en]
disclosure control; log-linear models; Poisson-inverse Gaussian; risk-per-record; uniqueness
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:su:diva-96546OAI: oai:DiVA.org:su-96546DiVA: diva2:666504
Available from: 2013-11-22 Created: 2013-11-22 Last updated: 2013-11-22

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