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Bayesian Multiscale Multiple Imputation With Implications for Data Confidentiality

Author

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  • Holan, Scott H.
  • Toth, Daniell
  • Ferreira, Marco A. R.
  • Karr, Alan F.

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Suggested Citation

  • Holan, Scott H. & Toth, Daniell & Ferreira, Marco A. R. & Karr, Alan F., 2010. "Bayesian Multiscale Multiple Imputation With Implications for Data Confidentiality," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 564-577.
    • Handle: RePEc:bes:jnlasa:v:105:i:490:y:2010:p:564-577
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    Cited by:

    1. Sara Zapata‐Marin & Alexandra M. Schmidt & Scott Weichenthal & Eric Lavigne, 2023. "Modeling temporally misaligned data across space: The case of total pollen concentration in Toronto," Environmetrics, John Wiley & Sons, Ltd., vol. 34(8), December.
    2. Toth Daniell, 2014. "Data Smearing: An Approach to Disclosure Limitation for Tabular Data," Journal of Official Statistics, Sciendo, vol. 30(4), pages 839-857, December.
    3. Harrison Quick, 2021. "Generating Poisson‐distributed differentially private synthetic data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1093-1108, July.
    4. Erik Dietzenbacher & Manfred Lenzen & Bart Los & Dabo Guan & Michael L. Lahr & Ferran Sancho & Sangwon Suh & Cuihong Yang, 2013. "Input--Output Analysis: The Next 25 Years," Economic Systems Research, Taylor & Francis Journals, vol. 25(4), pages 369-389, December.
    5. John M. Abowd & Ian M. Schmutte & Lars Vilhuber, 2018. "Disclosure Limitation and Confidentiality Protection in Linked Data," Working Papers 18-07, Center for Economic Studies, U.S. Census Bureau.
    6. Jing Yi & Samantha Cohen & Sarah Rehkamp & Patrick Canning & Miguel I. Gómez & Houtian Ge, 2023. "Overcoming data barriers in spatial agri‐food systems analysis: A flexible imputation framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 686-701, September.

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