Joint Modeling for Record Linkage and Statistical Analysis

• Activity Number: 112
• Type: Invited
• Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Government Statistics Section
• Author(s): Michael Larsen*
• Companies: The George Washington University
• Keywords: File matching ; Full probability model ; Fellegi-Sunter algorithm ; False match ; False nonmatch ; Data fusion

Abstract

Record linkage involves bringing together information from two or more files such that the combined records associate together all the available data individual by individual. The product of record linkage is a file with one record per individual that contains all the information about the individual from the multiple files. The problem is difficult when a unique identification key is not available, there are errors in some variables, some data are missing, and files are large. Probabilistic record linkage computes a probability that records from on different files pertain to a single individual or to different people. Some true links are given low probabilities of matching, whereas some non links are given high probabilities. Errors in linkage designations can cause bias in analyses based on the composite data base. Full probability models are proposed for jointly modeling the record linkage process and subsequent statistical analysis.