Estimating the re-identification risk per record in microdata
Skinner, C.J. and Holmes, D.J. (1998) Estimating the re-identification risk per record in microdata. Journal of Official Statistics, 14, (4), 361-372.
Full text not available from this repository.
A measure of re-identification risk at the record level has a variety of potential uses in statistical disclosure control for microdata. The conceptual basis of such a measure is considered. The risk is conceived of broadly as the evidence in support of a link between the record and the unit in the population from which it is derived. For discrete key variables subject to no measurement error, a measure is derived which reflects the probability that the record is unique in the population. Under certain assumptions, two approaches are described for estimating this measure from the microdata. These approaches are applied to a 10% sample of microdata from the 1991 Census in Great Britain. It is found that the resulting risk measures can indeed be used successfully to establish whether sample unique records are unique in the population. The implications of these findings are discussed.
|Keywords:||key variable, log-linear model, lognormal distribution, population uniqueness, statistical disclosure control|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||University Structure - Pre August 2011 > School of Social Sciences > Social Statistics
|Date Deposited:||20 Dec 2007|
|Last Modified:||02 Mar 2012 13:28|
|Contributors:||Skinner, C.J. (Author)
Holmes, D.J. (Author)
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)