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: 2015.1-21
Depends: R (≥ 2.13.0), methods
Imports: ucminf, MASS, Matrix
Suggests: lme4, nnet, xtable, testthat (≥ 0.8)
Published: 2015-01-21
Author: Rune Haubo Bojesen Christensen [aut, cre]
Maintainer: Rune Haubo Bojesen Christensen <rhbc at dtu.dk>
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

Downloads:

Reference manual: ordinal.pdf
Vignettes: Analysis of ordinal data with cumulative link models
clm tutorial
clmm2 tutorial
Package source: ordinal_2015.1-21.tar.gz
Windows binaries: r-devel: ordinal_2015.1-21.zip, r-release: ordinal_2015.1-21.zip, r-oldrel: ordinal_2015.1-21.zip
OS X Snow Leopard binaries: r-release: ordinal_2015.1-21.tgz, r-oldrel: ordinal_2015.1-21.tgz
OS X Mavericks binaries: r-release: ordinal_2015.1-21.tgz
Old sources: ordinal archive

Reverse dependencies:

Reverse depends: RcmdrPlugin.MPAStats
Reverse imports: crch
Reverse suggests: AICcmodavg, catdata, lsmeans, RVAideMemoire, sensR
Reverse enhances: MuMIn, stargazer, texreg