22 citations · 82 across the 24 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
stat.AP2018★ 6 cited
Bayesian Data Synthesis and Disclosure Risk Quantification: An Application to the Consumer Expenditure Surveys
Jingchen Hu, Terrance D. Savitsky
The release of synthetic data generated from a model estimated on the data helps statistical agencies disseminate respondent-level data with high utility and privacy protection. Mo…
stat.ME2018★ 22 cited
Bayesian Estimation of Attribute and Identification Disclosure Risks in Synthetic Data
Jingchen Hu
The synthetic data approach to data confidentiality has been actively researched on, and for the past decade or so, a good number of high quality work on developing innovative synt…
stat.AP2018★ 1 cited
Synthesizing geocodes to facilitate access to detailed geographical information in large scale administrative data
Joerg Drechsler, Jingchen Hu
We investigate whether generating synthetic data can be a viable strategy for providing access to detailed geocoding information for external researchers, without compromising the…