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  "Title": "Missing Item Responses Imputation for Test and Assessment Data",
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  "Authors@R": "c(person(\"Shenghai\", \"Dai\", role = c(\"aut\", \"cre\"), \nemail = \"s.dai@wsu.edu\"),\nperson(\"Xiaolin\", \"Wang\", role = \"aut\"),\nperson(\"Dubravka\", \"Svetina\", role = \"aut\"))",
  "Author": "Shenghai Dai [aut, cre], Xiaolin Wang [aut], Dubravka Svetina\n[aut]",
  "Maintainer": "Shenghai Dai <s.dai@wsu.edu>",
  "Description": "Functions for imputing missing item responses for\ndichotomous and polytomous test and assessment data. This\npackage enables missing imputation methods that are suitable\nfor test and assessment data, including: listwise (LW) deletion\n(see De Ayala et al. 2001\n<doi:10.1111/j.1745-3984.2001.tb01124.x>), treating as\nincorrect (IN, see Lord, 1974 <doi:\n10.1111/j.1745-3984.1974.tb00996.x>; Mislevy & Wu, 1996 <doi:\n10.1002/j.2333-8504.1996.tb01708.x>; Pohl et al., 2014 <doi:\n10.1177/0013164413504926>), person mean imputation (PM), item\nmean imputation (IM), two-way (TW) and response function (RF)\nimputation, (see Sijtsma & van der Ark, 2003 <doi:\n10.1207/s15327906mbr3804_4>), logistic regression (LR)\nimputation, predictive mean matching (PMM), and\nexpectation–maximization (EM) imputation (see Finch, 2008 <doi:\n10.1111/j.1745-3984.2008.00062.x>).",
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    {
      "page": "EMimpute",
      "title": "EM Imputation",
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      ]
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      "title": "This main function imputes for missing responses using selected method",
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      "title": "Item Mean (IM) Imputation",
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      ]
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