Bayesian Multiscale Multiple Imputation With Implications for Data Confidentiality

DOI10.1198/jasa.2009.ap08629zbMath1392.62337OpenAlexW1965017535MaRDI QIDQ5255289

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

Publication date: 15 June 2015

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/jasa.2009.ap08629

zbMATH Keywords

missing datadynamic linear modeldisclosurecell suppressionmulti scale modellingQCEW

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Bayesian inference (62F15) Generalized linear models (logistic models) (62J12)

Related Items (5)

Providing access to confidential research data through synthesis and verification: an application to data on employees of the U.S. federal government ⋮ General and feasible tests with multiply-imputed datasets ⋮ Multiple Improvements of Multiple Imputation Likelihood Ratio Tests ⋮ Spatial change of support models for differentially private decennial census counts of persons by detailed race and ethnicity ⋮ Calibrated imputation of numerical data under linear edit restrictions

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