Fast Probabilistic Record Linkage with Missing Data
Description
Implements a Fellegi-Sunter probabilistic record linkage model that allows for missing data
and the inclusion of auxiliary information. This includes functionalities to conduct a merge of two
datasets under the Fellegi-Sunter model using the Expectation-Maximization algorithm. In addition,
tools for preparing, adjusting, and summarizing data merges are included. The package implements methods
described in Enamorado, Fifield, and Imai (2019) ''Using a Probabilistic Model to Assist Merging of
Large-scale Administrative Records'', American Political Science Review and is available
at .