A Comparative Assessment of Disclosure Risk and Data Quality Between MASSC and Other Statistical Disclosure Limitation Methods

• Activity Number: 625
• Type: Contributed
• Date/Time: Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Section on Survey Research Methods
• Author(s): Feng Yu*+ and Neeraja S. Sathe
• Companies: RTI International and RTI International
• Keywords: Statistical Disclosure Limitation ; MASSC ; PRAM ; Random Swapping ; Disclosure Risk ; Information Loss

Abstract

MASSC (an acronym for Micro-Agglomeration, optimal probabilistic Substitution, optimal probabilistic Subsampling, and optimal weight Calibration) is a statistical disclosure limitation (SDL) methodology developed at RTI International for simultaneous confidentiality and analytic utility protection. In this paper, MASSC was compared with two other SDL methods by examining the degree to which these methods impact data quality and lower disclosure risk. The other SDL methods are Post Randomization Method (PRAM) and Random Swapping. The sample was taken from the 2006 and 2007 National Survey on Drug Use and Health (NSDUH) public use files (PUFs) as an initial data set for treatment, where the original PUFs were viewed as the "population" and the three methods were compared via simulations. For risk assessment, the matching probability was calculated to discover if a record in a treated sample can be correctly linked to the corresponding record in the "population." For utility assessment, each treatment's impact on direct estimates and its impact on inference and on estimated regression-model parameters were compared.