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Activity Number:
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509
- Methodological Innovations and Applications in Government Statistics
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Type:
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Contributed
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Date/Time:
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Wednesday, August 2, 2017 : 10:30 AM to 12:20 PM
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Sponsor:
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Government Statistics Section
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Abstract #324092
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Title:
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Combination of Multiplicative Noise and Conditional Group Swapping to Protect Sensitive Survey Data from Disclosure
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Author(s):
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Anna Oganian*
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Companies:
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National Center for Health Statistics
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Keywords:
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statistical disclosure limitation ;
swapping ;
multiplicative noise ;
propensity scores
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Abstract:
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Applications of data swapping and noise are among the most widely used methods for Statistical Disclosure Limitation (SDL) by statistical agencies for public-use non-interactive data release. The core ideas of swapping and noise are conceptually easy to understand and are naturally suited for masking purposes. We believe that they are worth revisiting with a special emphasis given to the utility aspects of these methods and to the ways of combining the methods to increase their efficiency and reliability. We will present and discuss two methods of disclosure limitation based on swapping and noise, which can work together in synergy while protecting continuous and categorical variables. The first method is a version of multiplicative noise that preserves means and covariance together with some structural constraints in the data. The second method is loosely based on swapping. It is designed with the goal of preserving the relationships between strata-defining variables with other variables in the survey. We will show how these methods can be applied together enhancing each other's efficiency.
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Authors who are presenting talks have a * after their name.
