Do Disclosure Controls To Protect Confidentiality Degrade the Quality of the Data? Data from the 2002 Trends in Mathematics and Science Study

• Activity Number: 311
• Type: Topic Contributed
• Date/Time: Tuesday, August 9, 2005 : 2:00 PM to 3:50 PM
• Sponsor: Section on Government Statistics
• Author(s): Steven Kaufman*+ and Marilyn Seastrom and Shep Roey
• Companies: National Center for Education Statistics and National Center for Education Statistics and Westat
• Keywords: Disclosure Control ; Quality ; Pertubation

Abstract

The National Center for Education Statistics (NCES) in the U.S. Department of Education has had in place since 1987 a formal process for disclosure control to protect the confidentiality of potentially identifiable data in public use microdata files. This paper explores the disclosure control techniques used at NCES, with a focus on the potential impact of each technique on data quality. Historically, NCES has used the removal of all direct identifiers, coarsening techniques such as collapsing categories and top and bottom coding to avoid outliers, and a distance measure analysis of the sample institutions against available institution frames to identify further potential disclosures that require more coarsening of the data. In a 2002 revision of the NCES Statistical Standards, an additional disclosure edit was introduced involving either blanking and imputing or data swapping on a sample of cases. Each additional alteration to the data has the potential for negatively impacting the quality and usability of the data. Techniques currently in use at NCES will be demonstrated with data from the 2003 Trends in International Mathematics and Science Study.