How differential privacy will affect our understanding of health disparities in the United States
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Cited by:
- J. Tom Mueller & Alexis R. Santos-Lozada, 2022. "The 2020 US Census Differential Privacy Method Introduces Disproportionate Discrepancies for Rural and Non-White Populations," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(4), pages 1417-1430, August.
- Bi, Xuan & Shen, Xiaotong, 2023. "Distribution-invariant differential privacy," Journal of Econometrics, Elsevier, vol. 235(2), pages 444-453.
- Heng Xu & Nan Zhang, 2022. "Implications of Data Anonymization on the Statistical Evidence of Disparity," Management Science, INFORMS, vol. 68(4), pages 2600-2618, April.
- Sigurd Dyrting & Abraham Flaxman & Ethan Sharygin, 2022. "Reconstruction of age distributions from differentially private census data," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(6), pages 2311-2329, December.
- Thayer Alshaabi & David R Dewhurst & James P Bagrow & Peter S Dodds & Christopher M Danforth, 2021. "The sociospatial factors of death: Analyzing effects of geospatially-distributed variables in a Bayesian mortality model for Hong Kong," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-20, March.
- Steven Ruggles & David Riper, 2022. "The Role of Chance in the Census Bureau Database Reconstruction Experiment," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(3), pages 781-788, June.
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Keywords
census; differential privacy; disclosure avoidance; mortality; demography;All these keywords.
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