Abstract Details
Activity Number:
|
301
|
Type:
|
Topic Contributed
|
Date/Time:
|
Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Survey Research Methods Section
|
Abstract - #307806 |
Title:
|
Data Smearing: An Approach to Disclosure Limitation for Tabular Data
|
Author(s):
|
Daniell Toth*+
|
Companies:
|
Bureau of Labor Statistics
|
Keywords:
|
contingency tables ;
synthetic data ;
confidentiality ;
nearest neighbor
|
Abstract:
|
Statistical agencies often collect sensitive data for release to the public at aggregated levels in the form of tables. In this article, we propose a new disclosure limitation method to replace the full set of micro-data with synthetic data for use in producing released data in tabular form. This synthetic data is obtained by breaking each unit's data into small pieces and spreading them among the nearest neighbors by repeatedly sampling from the set of fragmented original micro-data. The synthetic data is produced in a way to give approximately unbiased estimates for aggregate cells as the number of units in the cell increases. The method is applied to the U.S. Bureau of Labor Statistics' Quarterly Census of Employment and Wages data, which is released to the public quarterly, in tabular form, aggregated across varying scales of time, area, and economic sector.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.