JSM 2005 - Toronto

Abstract #303027

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 203
Type: Other
Date/Time: Tuesday, August 9, 2005 : 8:30 AM to 10:20 AM
Sponsor: ASA
Abstract - #303027
Title: Introduction to Statistical Disclosure Limitation or How to Release Useful Data Without Violating Promises of Confidentiality
Author(s): Stephen Fienberg*+
Companies: Carnegie Mellon University
Address: Department of Statistics, Pittsburgh, PA, 15213,
Keywords: cell suppression ; data masking ; data swapping ; reporting multiple partial summaries ; sampling ; synthetic data
Abstract:

Statisticians are under increasing pressure to assure data releases do not violate federal and state laws and regulations, such as those associated with HIPPA. There are a variety of methods used to protect confidentiality of statistical data. In this presentation, we articulate basic principles for choosing among disclosure limitation methods and review common approaches to explore how they accord with the principles. Among the methods are cell suppression, data swapping, adding random noise, reporting multiple partial summaries, sampling, and synthetic data.

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Revised March 2005