Examining the robustness of fully synthetic data techniques for data with binary variables

DOI10.1080/00949650902744438zbMath1197.65016OpenAlexW2101588196MaRDI QIDQ3589962

Ofer Harel, Gregory J. Matthews, Robert Aseltine

Publication date: 17 September 2010

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949650902744438

zbMATH Keywords

numerical examplesconfidentialitymultiple imputationsynthetic datadisclosure limitation

Mathematics Subject Classification ID

Related Items (1)

Data confidentiality: a review of methods for statistical disclosure limitation and methods for assessing privacy

Uses Software

• R
• MICE

Cites Work

• Unnamed Item
• Releasing Multiply Imputed, Synthetic Public use Microdata: An Illustration and Empirical Study
• Data-swapping: A technique for disclosure control
• Fully conditional specification in multivariate imputation
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Suppression Methodology and Statistical Disclosure Control
• Bias reduction of maximum likelihood estimates

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