ordinal: Regression Models for Ordinal Data

This package implements 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). 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: 2012.09-11
Depends: R (≥ 2.13.0), MASS, ucminf, Matrix
Imports: numDeriv
Suggests: lme4, nnet, xtable
Published: 2012-09-12
Author: Rune Haubo B Christensen
Maintainer: Rune Haubo B Christensen <rhbc at imm.dtu.dk>
License: GPL (≥ 2)
NeedsCompilation: yes
In views: Econometrics
CRAN checks: ordinal results


Package source: ordinal_2012.09-11.tar.gz
MacOS X binary: ordinal_2012.09-11.tgz
Windows binary: ordinal_2012.09-11.zip
Reference manual: ordinal.pdf
Vignettes: Analysis of ordinal data with cumulative link models
clm tutorial
clmm2 tutorial
Old sources: ordinal archive

Reverse dependencies:

Reverse depends: RcmdrPlugin.MPAStats, sensR
Reverse suggests: AICcmodavg, catdata
Reverse enhances: MuMIn