Layne, M.: Estimating Record Linkage Error Rates Using Administrative Records Data

• Activity Number: 23
• Type: Topic Contributed
• Date/Time: Sunday, August 4, 2013 : 2:00 PM to 3:50 PM
• Sponsor: Survey Research Methods Section
• Author(s): Mary Layne*+ and Deborah Wagner and Cynthia Rothhaas
• Companies: U.S. Census Bureau and U.S. Census Bureau and U.S. Census Bureau
• Keywords: probablistic record linkage ; false match rate ; Census Bureau ; federal data

Abstract

The Census Bureau's Person Identification Validation System (PVS) assigns unique person identifiers to federal, commercial, and survey data to facilitate linkages across files. PVS uses probabilistic matching to assign a unique Census Bureau identifier for each person. This paper presents a method to measure the false match rate in PVS following the approach of Belin and Rubin (1995).

The Belin and Rubin methodology requires truth data to estimate a mixture model. The parameters from the mixture model are used to obtain point estimates of the false match rate for each of the PVS search modules. The truth data requirement is satisfied by the Census Bureau's unique access to high quality name, date of birth, address and Social Security (SSN) data. Truth data are quickly created for the Belin and Rubin model and do not involve a clerical review process. These truth data are used to create estimates for the Belin and Rubin parameters, making the approach more practicable. Error rates are computed for all search modules in federal administrative records data and commercial data.