swMATH ID: 43076
Software Authors: Ejike R. Ugba
Description: R package gofcat: Goodness-of-Fit Measures for Categorical Response Models. A post-estimation method for categorical response models (CRM). Inputs from objects of class serp(), clm(), polr(), multinom(), mlogit(), vglm() and glm() are currently supported. Available tests include the Hosmer-Lemeshow tests for the binary, multinomial and ordinal logistic regression; the Lipsitz and the Pulkstenis-Robinson tests for the ordinal models. The proportional odds, adjacent-category, and constrained continuation-ratio models are particularly supported at ordinal level. Tests for the proportional odds assumptions in ordinal models are also possible with the Brant and the Likelihood-Ratio tests. Moreover, several summary measures of predictive strength (Pseudo R-squared), and some useful error metrics, including, the brier score, misclassification rate and logloss are also available for the binary, multinomial and ordinal models. Ugba, E. R. and Gertheiss, J. (2018) <http://www.statmod.org/workshops_archive_proceedings_2018.html>.
Homepage: https://cran.r-project.org/web/packages/gofcat/index.html
Source Code:  https://github.com/cran/gofcat
Dependencies: R
Keywords: gofcat; R; R package; goodness-of-fit; GOF; categorical response models; CRMs; Journal of Open Source Software
Related Software: VGAM; serp; performance; generalhoslem; brant; mlogitgof; CRAN; pkgdown; stats; Mlogit; MASS (R); nnet; ordinal; ResourceSelection; AICcmodavg; goftest; R
Cited in: 0 Documents

Standard Articles

1 Publication describing the Software Year
gofcat: An R package for goodness-of-fit of categorical response models Link
Ejike R. Ugba