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  • Articles and reports: 11-522-X202200100007
    Description: With the availability of larger and more diverse data sources, Statistical Institutes in Europe are inclined to publish statistics on smaller groups than they used to do. Moreover, high impact global events like the Covid crisis and the situation in Ukraine may also ask for statistics on specific subgroups of the population. Publishing on small, targeted groups not only raises questions on statistical quality of the figures, it also raises issues concerning statistical disclosure risk. The principle of statistical disclosure control does not depend on the size of the groups the statistics are based on. However, the risk of disclosure does depend on the group size: the smaller a group, the higher the risk. Traditional ways to deal with statistical disclosure control and small group sizes include suppressing information and coarsening categories. These methods essentially increase the (mean) group sizes. More recent approaches include perturbative methods that have the intention to keep the group sizes small in order to preserve as much information as possible while reducing the disclosure risk sufficiently. In this paper we will mention some European examples of special focus group statistics and discuss the implications on statistical disclosure control. Additionally, we will discuss some issues that the use of perturbative methods brings along: its impact on disclosure risk and utility as well as the challenges in proper communication thereof.
    Release date: 2024-03-25

  • Articles and reports: 11-522-X20030017691
    Description:

    This paper explains how results of European research projects on statistical disclosure control (SDC) can be used in the production of official statistics. It describes two related software packages for producing safe data: tau-ARGUS for tabular data, and mu-ARGUS for microdata.

    Release date: 2005-01-26
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Articles and reports (2)

Articles and reports (2) ((2 results))

  • Articles and reports: 11-522-X202200100007
    Description: With the availability of larger and more diverse data sources, Statistical Institutes in Europe are inclined to publish statistics on smaller groups than they used to do. Moreover, high impact global events like the Covid crisis and the situation in Ukraine may also ask for statistics on specific subgroups of the population. Publishing on small, targeted groups not only raises questions on statistical quality of the figures, it also raises issues concerning statistical disclosure risk. The principle of statistical disclosure control does not depend on the size of the groups the statistics are based on. However, the risk of disclosure does depend on the group size: the smaller a group, the higher the risk. Traditional ways to deal with statistical disclosure control and small group sizes include suppressing information and coarsening categories. These methods essentially increase the (mean) group sizes. More recent approaches include perturbative methods that have the intention to keep the group sizes small in order to preserve as much information as possible while reducing the disclosure risk sufficiently. In this paper we will mention some European examples of special focus group statistics and discuss the implications on statistical disclosure control. Additionally, we will discuss some issues that the use of perturbative methods brings along: its impact on disclosure risk and utility as well as the challenges in proper communication thereof.
    Release date: 2024-03-25

  • Articles and reports: 11-522-X20030017691
    Description:

    This paper explains how results of European research projects on statistical disclosure control (SDC) can be used in the production of official statistics. It describes two related software packages for producing safe data: tau-ARGUS for tabular data, and mu-ARGUS for microdata.

    Release date: 2005-01-26
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