Publications [#258535] of Jerome P. Reiter

Chapters

1. Mitra, R; Reiter, JP, Adjusting survey weights when altering identifying design variables via synthetic data, in Privacy in Statistical Databases, Lecture Notes in Computer Science,, edited by J Domingo Ferrer and L Franconi,, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 4302 (January, 2006), pp. 177-188, Springer, ISSN 0302-9743, ISBN 9783540493303 [Gateway.cgi], [doi]
   (last updated on 2026/01/20)

   Abstract:
   Statistical agencies alter values of identifiers to protect respondents’ confidentiality. When these identifiers are survey design variables, leaving the original survey weights on the file can be a disclosure risk. Additionally, the original weights may not correspond to the altered values, which impacts the quality of design-based (weighted) inferences. In this paper, we discuss some strategies for altering survey weights when altering design variables. We do so in the context of simulating identifiers from probability distributions, i.e. partially synthetic data. Using simulation studies, we illustrate aspects of the quality of inferences based on the different strategies.