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  "Title": "Fast Probabilistic Record Linkage with Missing Data",
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  "Authors@R": "c(\nperson(\"Ted\", \"Enamorado\", email = \"ted.enamorado@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Ben\", \"Fifield\", email = \"benfifield@gmail.com\", role = c(\"aut\")),\nperson(\"Kosuke\", \"Imai\", email = \"imai@harvard.edu\", role = c(\"aut\"))\n)",
  "Description": "Implements a Fellegi-Sunter probabilistic record linkage\nmodel that allows for missing data and the inclusion of\nauxiliary information. This includes functionalities to conduct\na merge of two datasets under the Fellegi-Sunter model using\nthe Expectation-Maximization algorithm. In addition, tools for\npreparing, adjusting, and summarizing data merges are included.\nThe package implements methods described in Enamorado, Fifield,\nand Imai (2019) ''Using a Probabilistic Model to Assist Merging\nof Large-scale Administrative Records''\n<doi:10.1017/S0003055418000783> and is available at\n<https://imai.fas.harvard.edu/research/linkage.html>.",
  "License": "GPL(>= 3)",
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    "matchesLink",
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    "preprocText",
    "stringSubset",
    "tableCounts"
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    },
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      "object": "samplematch",
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      "title": "Fast Probabilistic Record Linkage with Missing Data",
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      "title": "aggconfusion",
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      "title": "County-level outflow rates by state",
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      "title": "emlinkMARmov",
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    {
      "page": "plot.fastLink",
      "title": "Plot matching patterns of the EM object by posterior probability of match",
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