ordinal: Regression Models for Ordinal Data

Implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature. Multiple random effect terms are allowed and they may be nested, crossed or partially nested/crossed. Restrictions of symmetry and equidistance can be imposed on the thresholds (cut-points/intercepts). Standard model methods are available (summary, anova, drop-methods, step, confint, predict etc.) in addition to profile methods and slice methods for visualizing the likelihood function and checking convergence.

Version: 2015.6-28
Depends: R (≥ 2.13.0), methods
Imports: ucminf, MASS, Matrix
Suggests: lme4, nnet, xtable, testthat (≥ 0.8)
Published: 2015-06-28
Author: Rune Haubo Bojesen Christensen [aut, cre]
Maintainer: Rune Haubo Bojesen Christensen <rune.haubo at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: ordinal citation info
Materials: NEWS
In views: Econometrics, Psychometrics
CRAN checks: ordinal results


Reference manual: ordinal.pdf
Vignettes: Analysis of ordinal data with cumulative link models
clm tutorial
clmm2 tutorial
Package source: ordinal_2015.6-28.tar.gz
Windows binaries: r-devel: ordinal_2015.6-28.zip, r-release: ordinal_2015.6-28.zip, r-oldrel: ordinal_2015.6-28.zip
OS X El Capitan binaries: r-release: ordinal_2015.6-28.tgz
OS X Mavericks binaries: r-oldrel: ordinal_2015.6-28.tgz
Old sources: ordinal archive

Reverse dependencies:

Reverse depends: RcmdrPlugin.MPAStats
Reverse imports: crch, MXM, optimus, rcompanion, Wrapped
Reverse suggests: agridat, AICcmodavg, catdata, dotwhisker, effects, ensemblepp, generalhoslem, lsmeans, mlt.docreg, RVAideMemoire, sensR, sure
Reverse enhances: memisc, MuMIn, prediction, stargazer, texreg


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