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Activity Number: 518
Type: Invited
Date/Time: Thursday, August 10, 2006 : 10:30 AM to 12:20 PM
Sponsor: Business and Economics Statistics Section
Abstract - #305108
Title: Quality-Preserving Controlled Tabular Adjustment: an Alternative to Cell Suppression for Disclosure Limitation of Tabular Magnitude Data
Author(s): Lawrence H. Cox*+
Companies: National Center for Health Statistics
Address: Room 3211, Hyattsville, MD, 20782-2003,
Keywords: linear programming ; distribution ; confidentiality
Abstract:

Cell suppression thwarts standard methods of data analysis and is not describable probabilistically nor amenable to statistical methods for missing data. An alternative is controlled tabular adjustment (CTA). CTA replaces disclosure cells by safe values, adjusts remaining values to rebalance tabular equations, and performs optimally over a range of measures of 'closeness.' Recent research extends CTA to quality-preserving CTA by augmenting the linear constraint system with linear constraints that mimic important distributional parameters and statistics. In most cases, this can mitigate significant changes to the underlying distribution, in both univariate and multivariate settings. We control changes to means, variances, correlations, covariances, and regression coefficients. Based on linear programming, these formulations are easy to implement or enhance.

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