Some Advances on Bayesian Record Linkage and Inference for Linked Data

• Activity Number: 586
• Type: Topic Contributed
• Date/Time: Wednesday, August 7, 2013 : 2:00 PM to 3:50 PM
• Sponsor: Government Statistics Section
• Author(s): Andrea Tancredi*+ and Brunero Liseo
• Companies: Sapienza University of Rome and University of La Sapienza
• Keywords: Capture-recapture ; Linkage errors ; MCMC ; Population size estimation ; Linear regression

Abstract

In this paper we review some recent advances on Bayesian methodology for performing record linkage and for making inference using the resulting matched units. In particular, we frame the record linkage issue into a formal statistical model comprising both the matching variables and the other variables included in the inferential stage. This way, we account for matching process uncertainty in linked data inference but we also cause a feed-back propagation of the information between the interesting inferential model and the record linkage stage. To obtain posterior summaries we will use standard Bayesian computational techniques. Although the resulting methodology for linked data inference is quite general, we will focus on population size estimation and on the multiple regression context.