fastLink-package: Fast Probabilistic Record Linkage with Missing Data

In fastLink: Fast Probabilistic Record Linkage with Missing Data

Fast Probabilistic Record Linkage with Missing Data

Description

fastLink implements methods developed by Enamorado, Fifield, and Imai (2018) ”Using a Probabilistic Model to Assist Merging of Large-scale Administrative Records”, to probabilistically merge large datasets using the Fellegi-Sunter model while allowing for missing data and the inclusion of auxiliary information. The current version of this package conducts a merge of two datasets under the Fellegi-Sunter model, using the Expectation-Maximization Algorithm. In addition, tools for conducting and summarizing data merges are included.

Author(s)

Ted Enamorado [e-mail], Ben Fifield [e-mail], and Kosuke Imai [e-mail]

Maintainer: Ted Enamorado [e-mail]

References

Enamorado, Ted, Ben Fifield and Kosuke Imai. (2019) "Using a Probabilistic Model to Assist Merging of Large-scale Administrative Records." American Political Science Review. Vol. 113, No. 2. Available at https://imai.fas.harvard.edu/research/files/linkage.pdf.

fastLink documentation built on Nov. 17, 2023, 9:06 a.m.