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. © Springer-Verlag 2004.
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CITATION STYLE
Abowd, J. M., & Woodcock, S. D. (2004). Multiply-imputing confidential characteristics and file links in longitudinal linked data. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3050, 290–297. https://doi.org/10.1007/978-3-540-25955-8_23
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