{
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  "Type": "Package",
  "Package": "FedIRT",
  "Title": "Federated Item Response Theory Models",
  "Version": "1.1.0",
  "Authors@R": "c(\nperson(\"Biying\", \"Zhou\", email = \"zby.zhou@mail.utoronto.ca\", role = \"cre\"),\nperson(\"Feng\", \"Ji\", email = \"f.ji@utoronto.ca\", role = \"aut\"))",
  "Description": "Integrate Item Response Theory (IRT) and Federated\nLearning to estimate traditional IRT models, including the\n2-Parameter Logistic (2PL) and the Graded Response Models, with\nenhanced privacy. It allows for the estimation in a distributed\nmanner without compromising accuracy. A user-friendly 'shiny'\napplication is included.",
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  "Author": "Biying Zhou [cre], Feng Ji [aut]",
  "Maintainer": "Biying Zhou <zby.zhou@mail.utoronto.ca>",
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      "title": "Federated IRT model",
      "topics": [
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      "topics": [
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