Abstract #300210

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JSM 2003 Abstract #300210
Activity Number: 438
Type: Topic Contributed
Date/Time: Thursday, August 7, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Government Statistics
Abstract - #300210
Title: Multivariate Controlled Tabular Adjustments For SDL of Sensitive Data Using Latin Hypercube Sampling
Author(s): Ramesh A. Dandekar*+
Companies: Energy Information Administration
Address: 8922 Applecross Lane, Springfield, VA, 22153-1201,
Keywords: statistical disclosure ; tabular data ; synthetic tables ; controlled adjustments
Abstract:

As a part of the survey operation, National Statistical Office typically collects and processes multivariate statistical data and publishes related multivariate tables. Dandekar (2003) demonstrates the use of a simplified controlled tabular adjustment (CTA) method for a statistical Disclosure limitation (SDL) of univariate tabular data. We expand the basic concept of simplified CTA of Dandekar (2003) to process related multivariate tables using Latin Hypercube Sampling (LHS) method. The LHS not only allows maintaining within table univariate statistical properties intact, but also provides a consistent table-to-table multivariate relationship between related sensitive and nonsensitive cells. Our proposed method is applicable for a statistical disclosure control of complex multiple multidimensional linked tabular structures containing hierarchical relations. The by-product of the LHS-based multi variate CTA processing results in to "safe microdata," which in some situations could be used as a public use microdata.

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