Journal of Official Statistics, Vol.14, No.4, 1998. pp. 411–419
Balancing Disclosure Risk Against the Loss of Nonpublication
Alan M. Zaslavsky and Nicholas J. Horton
Abstract:A nondisclosure policy for tabular data on microdata restricts release of information
that could be related to a specific individual. Pannekoek and de Waal (1998) describe a
rule that suppresses data release when the number of people in a cell defined by a
rare characteristic falls below a fixed floor, and show how empirical Bayes methods can be
used to improve the estimation of that number. We argue that the nondisclosure problem can
be formulated as a decision problem in which one loss is associated with the possibility
of disclosure and another with nonpublication of data. This analysis supports a decision
on whether to disclose information in each cell, minimizing the expected sum of the two
losses. We present arguments for several loss functions, considering both tabular and
microdata releases, and illustrate their application to simple simulated data.
Keywords:Confidentiality; disclosure control; decision analysis; cell suppression; microdata.
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