Package: ordinal 2023.12-4

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.

Authors:Rune Haubo Bojesen Christensen [aut, cre]

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Bug tracker:https://github.com/runehaubo/ordinal/issues

On CRAN:

28 exports 32 stars 8.64 score 6 dependencies 161 dependents 97 mentions 1.5k scripts 52.1k downloads

Last updated 10 months agofrom:f38646c44d. Checks:OK: 7 NOTE: 2. Indexed: yes.

Exports:clmclm.controlclm.fitclm2clm2.controlclmmclmm.controlclmm2clmm2.controlcondVarconvergencedgumbeldlgammadrop.coefgcauchyggumbelglgammaglogisgnormnominal_testpgumbelplgammaqgumbelranefrgumbelscale_testsliceVarCorr

Dependencies:latticeMASSMatrixnlmenumDerivucminf