ordinal (2015.6-28)

1 user

Regression Models for Ordinal Data.

http://cran.r-project.org/web/packages/ordinal

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.

Maintainer: Rune Haubo Bojesen Christensen
Author(s): Rune Haubo Bojesen Christensen [aut, cre]

License: GPL (>= 2)

Uses: MASS, Matrix, ucminf, lme4, xtable, nnet, testthat
Reverse depends: RcmdrPlugin.MPAStats, sensR
Reverse suggests: agridat, AICcmodavg, dotwhisker, effects, generalhoslem, lsmeans, mlt.docreg, RVAideMemoire, sensR, sure
Reverse enhances: memisc, MuMIn, prediction, stargazer, texreg

Released about 2 years ago.


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