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  "Date": "2025-12-08",
  "Title": "Ecological Inference in 2x2 Tables",
  "Authors@R": "c(\nperson(\"Kosuke\", \"Imai\", , \"imai@Harvard.Edu\", c(\"aut\", \"cre\")),\nperson(\"Ying\", \"Lu\", , \"ying.lu@nyu.edu\", c(\"aut\")),\nperson(\"Aaron\", \"Strauss\", , \"aaronbstrauss@gmail.com\", c(\"aut\")),\nperson(\"Hubert\", \"Jin\", , \"hubertj@princeton.edu\", c(\"ctb\"))\n)",
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  "Description": "Implements the Bayesian and likelihood methods proposed in\nImai, Lu, and Strauss (2008 <doi:10.1093/pan/mpm017>) and (2011\n<doi:10.18637/jss.v042.i05>) for ecological inference in 2 by 2\ntables as well as the method of bounds introduced by Duncan and\nDavis (1953).  The package fits both parametric and\nnonparametric models using either the Expectation-Maximization\nalgorithms (for likelihood models) or the Markov chain Monte\nCarlo algorithms (for Bayesian models).  For all models, the\nindividual-level data can be directly incorporated into the\nestimation whenever such data are available. Along with\nin-sample and out-of-sample predictions, the package also\nprovides a functionality which allows one to quantify the\neffect of data aggregation on parameter estimation and\nhypothesis testing under the parametric likelihood models.",
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