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  "Type": "Package",
  "Title": "Methods and Examples from Introduction to the Theory of\nObservational Studies",
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  "Author": "Paul R. Rosenbaum [aut, cre]",
  "Maintainer": "Paul R. Rosenbaum <rosenbaum@wharton.upenn.edu>",
  "Description": "Supplements for a book, \"iTOS\" = \"Introduction to the\nTheory of Observational Studies.\"  Data sets are 'aHDL' from\nRosenbaum (2023a) <doi:10.1111/biom.13558> and 'bingeM' from\nRosenbaum (2023b) <doi:10.1111/biom.13921>.  The function\nmakematch() uses two-criteria matching from Zhang et al. (2023)\n<doi:10.1080/01621459.2021.1981337> to create the matched data\n'bingeM' from 'binge'.  The makematch() function also\nimplements optimal matching (Rosenbaum (1989)\n<doi:10.2307/2290079>) and matching with fine or near-fine\nbalance (Rosenbaum et al. (2007)\n<doi:10.1198/016214506000001059> and Yang et al (2012)\n<doi:10.1111/j.1541-0420.2011.01691.x>).  The book makes use of\ntwo other R packages, 'weightedRank' and 'tightenBlock'.",
  "License": "GPL-2",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-15 07:18:21 UTC",
    "User": "root"
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  "Date/Publication": "2024-09-06 02:55:04 UTC",
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    "extra/citation.json",
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    "computep",
    "ev",
    "evalBal",
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    "makematch",
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    "startcost",
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      "title": "Alcohol and HDL Cholesterol",
      "object": "aHDL",
      "class": [
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      ],
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        "SEQN",
        "age",
        "female",
        "education",
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      ],
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        "age",
        "ageC",
        "female",
        "educationf",
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        "waisthip",
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        "educationf",
        "education",
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        "waisthip",
        "vigor",
        "smokenowf",
        "smokenow",
        "bpRX",
        "smokeQuit",
        "AlcGroup",
        "bpSystolic",
        "bpDiastolic",
        "bpCombined",
        "z",
        "mset",
        "treated"
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      "table": true,
      "tojson": true
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      "page": "iTOS-package",
      "title": "Methods and Examples from Introduction to the Theory of Observational Studies",
      "topics": [
        "iTOS-package",
        "iTOS"
      ]
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    {
      "page": "addcaliper",
      "title": "Add a Caliper to an Existing Cost Matrix",
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      ]
    },
    {
      "page": "addinteger",
      "title": "Add an Integer Penalty to an Existing Distance Matrix",
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    },
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        "Mahalanobis distance"
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    },
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    },
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        "Observational study",
        "Causal inference",
        "Multiple control groups",
        "Unaffected outcome",
        "Placebo outcome",
        "Negative control",
        "Control outcome"
      ],
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      ]
    },
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      "page": "amplify",
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      "concept": [
        "Sensitivity analysis",
        "Observational study",
        "Causal inference",
        "Amplification",
        "Amplify",
        "Interpretation of sensitivity analyses",
        "rbounds"
      ],
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        "Causal inference",
        "Matching"
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        "Two-criteria matching",
        "Propensity score",
        "Network optimization"
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