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A Framework for Evaluating the Utility of Data Altered to Protect Confidentiality

Author

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  • Karr, A.F.
  • Kohnen, C.N.
  • Oganian, A.
  • Reiter, J.P.
  • Sanil, A.P.

Abstract

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Suggested Citation

  • Karr, A.F. & Kohnen, C.N. & Oganian, A. & Reiter, J.P. & Sanil, A.P., 2006. "A Framework for Evaluating the Utility of Data Altered to Protect Confidentiality," The American Statistician, American Statistical Association, vol. 60, pages 224-232, August.
    • Handle: RePEc:bes:amstat:v:60:y:2006:m:august:p:224-232
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    Citations

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    Cited by:

    1. Claire McKay Bowen & Fang Liu & Bingyue Su, 2021. "Differentially private data release via statistical election to partition sequentially," METRON, Springer;Sapienza Università di Roma, vol. 79(1), pages 1-31, April.
    2. Jörg Drechsler, 2015. "Multiple Imputation of Multilevel Missing Data—Rigor Versus Simplicity," Journal of Educational and Behavioral Statistics, , vol. 40(1), pages 69-95, February.
    3. Joshua Snoke & Gillian M. Raab & Beata Nowok & Chris Dibben & Aleksandra Slavkovic, 2018. "General and specific utility measures for synthetic data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 663-688, June.
    4. Mario Trottini, 2008. "Data disclosure limitation as a decision problem," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 109-134.
    5. repec:crs:wpidms:m2016-07 is not listed on IDEAS
    6. Tatiana Komarova & Denis Nekipelov & Evgeny Yakovlev, 2018. "Identification, data combination, and the risk of disclosure," Quantitative Economics, Econometric Society, vol. 9(1), pages 395-440, March.
    7. Reiter, Jerome P. & Oganian, Anna & Karr, Alan F., 2009. "Verification servers: Enabling analysts to assess the quality of inferences from public use data," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1475-1482, February.
    8. Javier Miranda & Lars Vilhuber, 2016. "Using Partially Synthetic Microdata to Protect Sensitive Cells in Business Statistics," Working Papers 16-10, Center for Economic Studies, U.S. Census Bureau.
    9. Joseph W. Sakshaug & Trivellore E. Raghunathan, 2014. "Generating synthetic microdata to estimate small area statistics in the American Community Survey," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(3), pages 341-368, June.
    10. Soumya Mukherjee & Aratrika Mustafi & Aleksandra Slavkovi'c & Lars Vilhuber, 2023. "Assessing Utility of Differential Privacy for RCTs," Papers 2309.14581, arXiv.org.
    11. Reiter, Jerome P. & Drechsler, Jörg, 2007. "Releasing multiply-imputed synthetic data generated in two stages to protect confidentiality," IAB-Discussion Paper 200720, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    12. David J. Hand, 2018. "Statistical challenges of administrative and transaction data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 555-605, June.
    13. Jahangir Alam M. & Dostie Benoit & Drechsler Jörg & Vilhuber Lars, 2020. "Applying data synthesis for longitudinal business data across three countries," Statistics in Transition New Series, Polish Statistical Association, vol. 21(4), pages 212-236, August.
    14. James Jackson & Robin Mitra & Brian Francis & Iain Dove, 2022. "Using saturated count models for user‐friendly synthesis of large confidential administrative databases," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1613-1643, October.
    15. Loong Bronwyn & Rubin Donald B., 2017. "Multiply-Imputed Synthetic Data: Advice to the Imputer," Journal of Official Statistics, Sciendo, vol. 33(4), pages 1005-1019, December.
    16. Ian Lundberg & Arvind Narayanan & Karen Levy & Matthew Salganik, 2018. "Privacy, ethics, and data access: A case study of the Fragile Families Challenge," Working Papers wp18-09-ff, Princeton University, School of Public and International Affairs, Center for Research on Child Wellbeing..
    17. Templ Matthias, 2015. "Quality Indicators for Statistical Disclosure Methods: A Case Study on the Structure of Earnings Survey," Journal of Official Statistics, Sciendo, vol. 31(4), pages 737-761, December.
    18. Tatiana Komarova & Denis Nekipelov, 2020. "Identification and Formal Privacy Guarantees," Papers 2006.14732, arXiv.org, revised May 2021.

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