Mitra, Robin ![]() |
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.
Item Type: | Conference or Workshop Item (Paper) |
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Status: | Published |
Schools: | Mathematics |
Publisher: | Springer Verlag |
ISBN: | 978-3-540-49330-3 |
ISSN: | 0302-9743 |
Last Modified: | 06 May 2023 02:00 |
URI: | https://orca.cardiff.ac.uk/id/eprint/141143 |
Citation Data
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