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