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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Mitra, R., Reiter, J.P. (2006). Adjusting Survey Weights When Altering Identifying Design Variables Via Synthetic Data. In: Domingo-Ferrer, J., Franconi, L. (eds) Privacy in Statistical Databases. PSD 2006. Lecture Notes in Computer Science, vol 4302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11930242_16
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DOI: https://doi.org/10.1007/11930242_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49330-3
Online ISBN: 978-3-540-49332-7
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