Statistical disclosure limitation in the presence of edit rules
We compare two general strategies for performing statistical disclosure limitation (SDL) for continuous micro data subject to edit rules. In the first, existing SDL methods are applied, and any constraint-violating values they produce are replaced using a constraint-preserving imputation procedure. In the second, the SDL methods are modified to prevent them from generating violations. We present a simulation study, based on data from the Colombian Annual Manufacturing Survey, that evaluates the performance of the two strategies as applied to several SDL methods. The results suggest that differences in risk-utility profiles across SDL methods dwarf differences between the two general strategies. Among the SDL strategies, variants of micro aggregation and partially synthetic data offer the most attractive risk-utility profiles.
Duke Scholars
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- 4905 Statistics
- 1603 Demography
- 0104 Statistics
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- 4905 Statistics
- 1603 Demography
- 0104 Statistics