Journal of Official Statistics, Vol.14, No.4, 1998. pp. 361–372
Estimating the Re-identification Risk Per Record in Microdata
C.J. Skinner and D.J. Holmes
Abstract: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.
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