46 citations
- U.S. National Science FoundationUS7 papers
- Vassar CollegeUS5 papers
- National Center for Science and Engineering StatisticsUS3 papers
- Amherst CollegeUS1 paper
- Educational Testing ServiceUS1 paper
- National University of SingaporeSG1 paper
- RTI InternationalUS1 paper
- University of California, Santa CruzUS1 paper
- University of IowaUS1 paper
- Western UniversityCA1 paper
Showing 2019Show all
3 papers · 1 filter
stat.ME2019★ 8 cited
Bayesian Pseudo Posterior Mechanism under Asymptotic Differential Privacy
Terrance D. Savitsky, Matthew R. Williams, Jingchen Hu
We propose a Bayesian pseudo posterior mechanism to generate record-level synthetic databases equipped with an probabilistic differential privacy (pDP) guarantee, where $δ…
stat.ME2019★ 12 cited
Risk-Efficient Bayesian Data Synthesis for Privacy Protection
Jingchen Hu, Terrance D. Savitsky, Matthew R. Williams
Statistical agencies utilize models to synthesize respondent-level data for release to the public for privacy protection. In this work, we efficiently induce privacy protection int…
stat.CO2019★ 1 cited
Optimization of Survey Weights under a Large Number of Conflicting Constraints
Matthew R. Williams, Terrance D. Savitsky
In the analysis of survey data, sampling weights are needed for consistent estimation of the population. However, the original inverse probability weights from the survey sample de…