JSM 2004 - Toronto

Abstract #300986

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Activity Number: 44
Type: Topic Contributed
Date/Time: Sunday, August 8, 2004 : 4:00 PM to 5:50 PM
Sponsor: Section on Government Statistics
Abstract - #300986
Title: Sharing Confidential Data Among Multiple Agencies Using Multiply Imputed, Synthetic Data
Author(s): Christine N. Kohnen*+ and Jerome Reiter
Companies: Duke University and Duke University
Address: Box 90251, Durham, NC, 27708-0251,
Keywords: Disclosure Limitation ; Combining Rules ; Multiple Imputation ; Synthetic Data
Abstract:

As the amount of data collected by agencies increases, they may find it beneficial to share their information to create one large database. This new combined database would then provide all involved agencies with a better view of the units recorded; however, such an endeavor would require the cooperation of all involved agencies to disseminate possibly sensitive information. Such a request may not be granted as it could reveal respondents' actual data. One approach to safely sharing their data is for agencies to provide synthetic data rather than real data. This talk will discuss the use of multiple imputation to share data among statistical agencies. We will present inferential methods for combining multiple datasets and will illustrate the approach with simulations.

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