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  "Title": "Detect and Check for Separation and Infinite Maximum Likelihood\nEstimates",
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  "Authors@R": "c(person(given = \"Ioannis\", family = \"Kosmidis\", role = c(\"aut\", \"cre\"), email = \"ioannis.kosmidis@warwick.ac.uk\", comment = c(ORCID = \"0000-0003-1556-0302\")),\nperson(given = \"Dirk\", family = \"Schumacher\", role = \"aut\", email = \"mail@dirk-schumacher.net\"),\nperson(given = \"Florian\", family = \"Schwendinger\", role = \"aut\", email = \"FlorianSchwendinger@gmx.at\"),\nperson(given = \"Kjell\", family = \"Konis\", role = \"ctb\", email = \"kjell.konis@me.com\"))",
  "Description": "Provides pre-fit and post-fit methods for detecting\nseparation and infinite maximum likelihood estimates in\ngeneralized linear models with categorical responses. The\npre-fit methods apply on binomial-response generalized liner\nmodels such as logit, probit and cloglog regression, and can be\ndirectly supplied as fitting methods to the glm() function.\nThey solve the linear programming problems for the detection of\nseparation developed in Konis (2007,\n<https://ora.ox.ac.uk/objects/uuid:8f9ee0d0-d78e-4101-9ab4-f9cbceed2a2a>)\nusing 'ROI' <https://cran.r-project.org/package=ROI> or\n'lpSolveAPI' <https://cran.r-project.org/package=lpSolveAPI>.\nThe post-fit methods apply to models with categorical\nresponses, including binomial-response generalized linear\nmodels and multinomial-response models, such as baseline\ncategory logits and adjacent category logits models; for\nexample, the models implemented in the 'brglm2'\n<https://cran.r-project.org/package=brglm2> package. The\npost-fit methods successively refit the model with increasing\nnumber of iteratively reweighted least squares iterations, and\nmonitor the ratio of the estimated standard error for each\nparameter to what it has been in the first iteration. According\nto the results in Lesaffre & Albert (1989,\n<https://www.jstor.org/stable/2345845>), divergence of those\nratios indicates data separation.",
  "URL": "https://github.com/ikosmidis/detectseparation",
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  "Date/Publication": "2026-04-29 13:09:44 UTC",
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  "RemoteRef": "HEAD",
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    "User": "root"
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  "Author": "Ioannis Kosmidis [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-1556-0302>),\nDirk Schumacher [aut],\nFlorian Schwendinger [aut],\nKjell Konis [ctb]",
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        "HG"
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        "check_infinite_estimates"
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      "title": "A simple diagnostic of whether the maximum likelihood estimates are infinite",
      "topics": [
        "check_infinite_estimates.glm"
      ]
    },
    {
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      "title": "Detect Infinite Estimates",
      "topics": [
        "detectInfiniteEstimates",
        "detect_infinite_estimates"
      ]
    },
    {
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      "title": "Detect Separation",
      "topics": [
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        "detect_separation",
        "print.detect_separation"
      ]
    },
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      "topics": [
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