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  "Package": "ThresholdROC",
  "Type": "Package",
  "Title": "Optimum Threshold Estimation",
  "Version": "2.10.0",
  "Date": "2026-07-27",
  "Authors@R": "c(person(\"Sara\", \"Perez-Jaume\", email = \"spjaume@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-9805-4810\")),\nperson(\"Natalia\", \"Pallares\", role = \"aut\", comment = c(ORCID = \"0000-0002-1462-379X\")),\nperson(\"Konstantina\", \"Skaltsa\", role = \"aut\"))",
  "Description": "Functions that provide point and interval estimations of\noptimum thresholds for continuous diagnostic tests. The\nmethodology used is based on minimizing an overall cost\nfunction in the two- and three-state settings. We also provide\nfunctions for sample size determination and estimation of\ndiagnostic accuracy measures. We also include graphical tools.\nThe statistical methodology used here can be found in\nPerez-Jaume et al (2017) <doi:10.18637/jss.v082.i04> and in\nSkaltsa et al (2010, 2012) <doi:10.1002/bimj.200900294>,\n<doi:10.1002/sim.4369>.",
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  "Author": "Sara Perez-Jaume [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-9805-4810>), Natalia Pallares\n[aut] (ORCID: <https://orcid.org/0000-0002-1462-379X>),\nKonstantina Skaltsa [aut]",
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    "secondDer3",
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      "title": "Alzheimer's disease data",
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        "Status"
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      "title": "Diagnostic accuracy measures of binary diagnostic tests",
      "topics": [
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