Abstract Details
Activity Number:
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355
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 11:35 AM to 12:20 PM
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Sponsor:
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Survey Research Methods Section
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Abstract #313984
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Title:
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Releasing Synthetic Microdata for Magnitude Tabular Data
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Author(s):
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Lan Wei*+ and Jerome P. Reiter
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Companies:
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Duke University and Duke University
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Keywords:
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Data Confidentiality ;
Mixture Model ;
Nonparametric Bayesian
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Abstract:
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Establishment microdata is subjected to strict confidential protection. Releasing it while providing meaningful statistical inference is a challenge. This is especially true for micro discrete/count data with fixed marginal totals. We develop a new statistical disclosure limitation (SDL) technique based on data synthesis. We propose a mixture of Poisson distributions for multivariate count data and a synthesis method subject to fixed marginal totals. We apply the procedure to a data from the Colombian Annual Manufacturing Survey. The results show that the synthetic data can provide high utility. We also present a method for disclosure risk assessment.
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Authors who are presenting talks have a * after their name.
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