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'' <doi:10.1017/S0003055418000783> and is available at <https://imai.fas.harvard.edu/research/linkage.html>.
Package details |
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Author | Ted Enamorado [aut, cre], Ben Fifield [aut], Kosuke Imai [aut] |
Maintainer | Ted Enamorado <ted.enamorado@gmail.com> |
License | GPL (>= 3) |
Version | 0.6.1 |
Package repository | View on CRAN |
Installation |
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