Bayesian Estimation of Disclosure Risks for Multiply Imputed, Synthetic Data

Agencies seeking to disseminate public use microdata, i.e., data on individual records, can replace confidential values with multiple draws from statistical models estimated with the collected data. We present a famework for evaluating disclosure risks inherent in releasing multiply-imputed, synthe...

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Bibliographic Details
Main Authors: Jerome P. Reiter, Quanli Wang, Biyuan Zhang
Format: Article
Language:English
Published: Labor Dynamics Institute 2014-06-01
Series:The Journal of Privacy and Confidentiality
Subjects:
Online Access:https://journalprivacyconfidentiality.org/index.php/jpc/article/view/635