U.S. Department of Commerce

Research Reports

You are here: Census.govSubjects A to ZResearch Reports Sorted by Year › Abstract of RRS2006/01
Skip top of page navigation

Modeling and Quality of Masked Microdata

William E. Winkler

KEY WORDS: Data Mining; Likelihood, Loglinear, Multivariate

ABSTRACT

Statistical organizations collect data via survey forms and other methods. The microdata are valuable for modeling and analysis. To produce a public-use file, the organizations mask the data in a manner that may prevent re-identification of data associated with individual entities. The public-use microdata may allow one or two sets of analyses that approximately reproduce analyses that could be performed on the original microdata. This paper describes a general method of creating models of data that is related to methods of creating appropriate aggregates of data that are needed for sufficient statistics in general classes of models (Moore and Lee 1998, DuMouchel et al. 2000, Owen 2003). If the aggregates can be approximately reproduced, then the masked microdata may allow one or more analyses that correspond to analyses on the original, non-public microdata. It will typically not yield data suitable for general analyses.

CITATION:

Source: U.S. Census Bureau, Statistical Research Division

Created: January 13, 2006
Last revised: January 13, 2006


[PDF] or PDF denotes a file in Adobe’s Portable Document Format. To view the file, you will need the Adobe® Reader® Off Site available free from Adobe.

This symbol Off Site indicates a link to a non-government web site. Our linking to these sites does not constitute an endorsement of any products, services or the information found on them. Once you link to another site you are subject to the policies of the new site.

Source: U.S. Census Bureau | Statistical Research Division | (301) 763-3215 (or chad.eric.russell@census.gov) |   Last Revised: October 08, 2010