Abstract
This paper describes ongoing research to protect confidentiality in longitudinal linked data through creation of multiply-imputed, partially synthetic data. We present two enhancements to the methods of [2]. The first is designed to preserve marginal distributions in the partially synthetic data. The second is designed to protect confidential links between sampling frames.
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Abowd, J.M., Woodcock, S.D. (2004). Multiply-Imputing Confidential Characteristics and File Links in Longitudinal Linked Data. In: Domingo-Ferrer, J., Torra, V. (eds) Privacy in Statistical Databases. PSD 2004. Lecture Notes in Computer Science, vol 3050. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25955-8_23
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DOI: https://doi.org/10.1007/978-3-540-25955-8_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22118-0
Online ISBN: 978-3-540-25955-8
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