{
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  "Package": "nbpMatching",
  "Type": "Package",
  "Title": "Functions for Optimal Non-Bipartite Matching",
  "Version": "1.5.6",
  "Date": "2024-09-23",
  "Author": "Cole Beck [aut, cre], Bo Lu [aut], Robert Greevy [aut]",
  "Maintainer": "Cole Beck <cole.beck@vumc.org>",
  "Authors@R": "c(person(\"Cole\", \"Beck\", role = c(\"aut\", \"cre\"),\nemail = \"cole.beck@vumc.org\"),\nperson(\"Bo\", \"Lu\", role = \"aut\"),\nperson(\"Robert\", \"Greevy\", role = \"aut\"))",
  "Description": "Perform non-bipartite matching and matched randomization.\nA \"bipartite\" matching utilizes two separate groups, e.g.\nsmokers being matched to nonsmokers or cases being matched to\ncontrols. A \"non-bipartite\" matching creates mates from one big\ngroup, e.g. 100 hospitals being randomized for a two-arm\ncluster randomized trial or 5000 children who have been exposed\nto various levels of secondhand smoke and are being paired to\nform a greater exposure vs. lesser exposure comparison. At the\ncore of a non-bipartite matching is a N x N distance matrix for\nN potential mates. The distance between two units expresses a\nmeasure of similarity or quality as mates (the lower the\nbetter). The 'gendistance()' and 'distancematrix()' functions\nassist in creating this. The 'nonbimatch()' function creates\nthe matching that minimizes the total sum of distances between\nmates; hence, it is referred to as an \"optimal\" matching. The\n'assign.grp()' function aids in performing a matched\nrandomization. Note bipartite matching can be performed using\nthe prevent option in 'gendistance()'.",
  "License": "GPL (>= 2)",
  "URL": "https://github.com/couthcommander/nbpMatching",
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  "Repository": "https://couthcommander.r-universe.dev",
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  "_realowner": "couthcommander",
  "_cranurl": true,
  "_releases": [
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      "date": "2009-09-18"
    },
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      "date": "2012-10-29"
    },
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      "date": "2012-11-05"
    },
    {
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      "date": "2013-04-17"
    },
    {
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      "date": "2015-01-20"
    },
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      "date": "2015-05-14"
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    "full.qom",
    "gendistance",
    "get.sets",
    "make.phantoms",
    "nonbimatch",
    "qom",
    "quantile",
    "runner",
    "scalar.dist",
    "subsetMatches"
  ],
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      "page": "nbpMatching-package",
      "title": "Nonbipartite Matching",
      "topics": [
        "nbpMatching-package",
        "nbpMatching"
      ]
    },
    {
      "page": "assign.grp",
      "title": "Random Group Assignment",
      "topics": [
        "assign.grp",
        "assign.grp,data.frame-method",
        "assign.grp,nonbimatch-method"
      ]
    },
    {
      "page": "distancematrix",
      "title": "Distance matrix",
      "topics": [
        "distancematrix",
        "distancematrix,character-method",
        "distancematrix,data.frame-method",
        "distancematrix,list-method",
        "distancematrix,matrix-method",
        "distancematrix-class"
      ]
    },
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      "title": "Data Imputation",
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        "fill.missing,data.frame-method"
      ]
    },
    {
      "page": "gendistance",
      "title": "Generate a Distance Matrix",
      "topics": [
        "gendistance",
        "gendistance,data.frame-method"
      ]
    },
    {
      "page": "get.sets",
      "title": "Get named sets of matches",
      "topics": [
        "get.sets",
        "get.sets,data.frame-method",
        "get.sets,nonbimatch-method"
      ]
    },
    {
      "page": "make.phantoms",
      "title": "Add Phantom Rows and Columns",
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        "make.phantoms,ANY,missing-method",
        "make.phantoms,data.frame,numeric-method",
        "make.phantoms,matrix,numeric-method"
      ]
    },
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      "title": "Nonbipartite Matching",
      "topics": [
        "nonbimatch",
        "nonbimatch,distancematrix-method",
        "nonbimatch-class"
      ]
    },
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        "qom,data.frame,data.frame-method",
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      ]
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        "quantile,distancematrix-method"
      ]
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        "scalar.dist,vector-method"
      ]
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      "title": "Subset Matches",
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      ]
    }
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