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  "Title": "Goodness-of-Fit Measures for Categorical Response Models",
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  "Authors@R": "person(given = \"Ejike R.\",\nfamily = \"Ugba\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"ejike.ugba@outlook.com\",\ncomment = c(ORCID = \"0000-0003-2572-0023\"))",
  "Description": "A post-estimation method for categorical response models\n(CRM). Inputs from objects of class serp(), clm(), polr(),\nmultinom(), mlogit(), vglm() and glm() are currently supported.\nAvailable tests include the Hosmer-Lemeshow tests for the\nbinary, multinomial and ordinal logistic regression; the\nLipsitz and the Pulkstenis-Robinson tests for the ordinal\nmodels. The proportional odds, adjacent-category, and\nconstrained continuation-ratio models are particularly\nsupported at ordinal level. Tests for the proportional odds\nassumptions in ordinal models are also possible with the Brant\nand the Likelihood-Ratio tests. Moreover, several summary\nmeasures of predictive strength (Pseudo R-squared), and some\nuseful error metrics, including, the brier score,\nmisclassification rate and logloss are also available for the\nbinary, multinomial and ordinal models. Ugba, E. R. and\nGertheiss, J. (2018)\n<http://www.statmod.org/workshops_archive_proceedings_2018.html>.",
  "License": "GPL-2 | file LICENSE",
  "URL": "https://github.com/ejikeugba/gofcat",
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  "Author": "Ejike R. Ugba [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0003-2572-0023>)",
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