<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Remote access can be a powerful tool for providing data access for external researchers. Since the microdata never leave the secure environment of the data-providing agency, alterations of the microdata can be kept to a minimum. Nevertheless, remote access is not free from risk. Many statistical analyses that do not seem to provide disclosive information at first sight can be used by sophisticated intruders to reveal sensitive information. For this reason the list of allowed queries is usually restricted in a remote setting. However, it is not always easy to identify problematic queries. We therefore strongly support the argument that has been made by other authors: that all queries should be monitored carefully and that any microlevel information should always be withheld. As an illustrative example, we use factor score analysis, for which the output of interest - the factor loading of the variables - seems to be unproblematic. However, as we show in the article, the individual factor scores that are usually returned as part of the output can be used to reveal sensitive information. Our empirical evaluations based on a German establishment survey emphasize that this risk is far from a purely theoretical problem.</p></abstract>

Remote access can be a powerful tool for providing data access for external researchers. Since the microdata never leave the secure environment of the data-providing agency, alterations of the microdata can be kept to a minimum. Nevertheless, remote access is not free from risk. Many statistical analyses that do not seem to provide disclosive information at first sight can be used by sophisticated intruders to reveal sensitive information. For this reason the list of allowed queries is usually restricted in a remote setting. However, it is not always easy to identify problematic queries. We therefore strongly support the argument that has been made by other authors: that all queries should be monitored carefully and that any microlevel information should always be withheld. As an illustrative example, we use factor score analysis, for which the output of interest - the factor loading of the variables - seems to be unproblematic. However, as we show in the article, the individual factor scores that are usually returned as part of the output can be used to reveal sensitive information. Our empirical evaluations based on a German establishment survey emphasize that this risk is far from a purely theoretical problem.

Disclosure Risk from Factor Scores

Institute for Employment Research, Statistical Methods, Regensburger Str. 104, Nuremberg 90478, Germany

University of Tuebingen, Mohlstraße 36, 72074 Tuebingen, Germany

Journal of Official Statistics

{"article-title":"Disclosure Risk from Factor Scores"}

Remote access can be a powerful tool for providing data access for external researchers. Since the microdata never leave the secure environment of the...

Disclosure Risk from Factor Scores

Publicado en línea: 14 feb 2014

Páginas: 107 - 122

DOI: https://doi.org/10.2478/jos-2014-0006

Palabras clave
Remote data access, confidentiality, statistical disclosure control, factor analysis

This content is open access.

Disclosure Risk from Factor Scores

Publicado en línea: 14 feb 2014

Páginas: 107 - 122

DOI: https://doi.org/10.2478/jos-2014-0006

Palabras claveRemote data access, confidentiality, statistical disclosure control, factor analysis

This content is open access.

Palabras clave
Remote data access, confidentiality, statistical disclosure control, factor analysis