JSM 2004 - Toronto

Abstract #301475

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Activity Number: 44
Type: Topic Contributed
Date/Time: Sunday, August 8, 2004 : 4:00 PM to 5:50 PM
Sponsor: Section on Government Statistics
Abstract - #301475
Title: Full Rank Minimal Sufficient Statistics for Disclosure Limitation and Variance Estimation: A Practical Way to Release Count Information
Author(s): Yves Thibaudeau*+ and William E. Winkler
Companies: U.S. Census Bureau and U.S. Census Bureau
Address: 4700 Silver Hill Rd., Washington, DC, 20233-9100,
Keywords: Loglinear Model ; Minimal Sufficient Statistic ; Contingency Table ; Disclosure Limitation ; Sampling Variance
Abstract:

Thibaudeau derives a full-rank minimal sufficient statistic (FRMSS) for contingency tables, under the assumption that a hierarchical log-linear model governs the sampling process. The dimensionality of this statistic is equal to the number of degrees of freedom of the model. The objective of the paper is to show that: 1. Selected components of the FRMSS carry much of the information requested by the user, so it is reasonable to release only these components, thereby also limiting information disclosure. 2. The representation of a contingency table by selected FRMSS components lends itself well to the computation of sampling variances for estimators of interest. We conduct simulations to illustrate these results.


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