{
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  "Date": "2022-04-07",
  "Title": "R Package for Designing and Analyzing Randomized Experiments",
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  "Maintainer": "Kosuke Imai <imai@harvard.edu>",
  "Description": "Provides various statistical methods for designing and\nanalyzing randomized experiments. One functionality of the\npackage is the implementation of randomized-block and\nmatched-pair designs based on possibly multivariate\npre-treatment covariates. The package also provides the tools\nto analyze various randomized experiments including cluster\nrandomized experiments, two-stage randomized experiments,\nrandomized experiments with noncompliance, and randomized\nexperiments with missing data.",
  "License": "GPL (>= 2)",
  "LazyLoad": "yes",
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  "RoxygenNote": "7.1.2",
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    "User": "root"
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  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2022-04-12 17:52:32 UTC",
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    "login": "kosukeimai",
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        "Yb",
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        "Tb"
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      "page": "ATEbounds",
      "title": "Bounding the Average Treatment Effect when some of the Outcome Data are Missing",
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    {
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      "title": "Estimation of the Average Treatment Effects in Cluster-Randomized Experiments",
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    {
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      "title": "Estimation of the Average Treatment Effect in Randomized Experiments",
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    },
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    },
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    },
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