Multiply-Imputing Confidential Characteristics and File Links in Longitudinal Linked Data
نویسندگان
چکیده
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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تاریخ انتشار 2004