ordinal-package: Regression Models for Ordinal Data via Cumulative Link...

Description Details Author(s) Examples


This package facilitates analysis of ordinal (ordered categorical data) via cumulative link models (CLMs) and cumulative link mixed models (CLMMs). Robust and efficient computational methods gives speedy and accurate estimation. A wide range of methods for model fits aids the data analysis.


Package: ordinal
Type: Package
License: GPL (>= 2)
LazyLoad: yes

This package implements cumualtive link models and cumulative link models with normally distributed random effects, denoted cumulative link mixed (effects) models. Cumulative link models are also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models.

Cumulative link models are fitted with clm and the main features are:

Cumulative link mixed models are fitted with clmm and the main features are:

In addition to the reference manual several vignettes describe aspects of the package. Two brief tutorials on clm and clmm introduces the use of these functions. The Primer vignette is a 30-page introduction to cumulative link models.

A major update of the package in August 2011 introduced new and improved implementations of clm and clmm. The old implementations are available with clm2 and clmm2. At the time of writing there is functionality in clm2 and clmm2 not yet available in clm and clmm. This includes flexible link functions (log-gamma and Aranda-Ordaz links) and a profile method for random effect variance parameters in CLMMs. The new implementations are expected to take over the old implementations at some point, hence the latter will eventually be deprecated and defunct.


Rune Haubo B Christensen

Maintainer: Rune Haubo B Christensen <[email protected]>


## A simple cumulative link model:
fm1 <- clm(rating ~ contact + temp, data=wine)

## A simple cumulative link mixed model:
fmm1 <- clmm(rating ~ contact + temp + (1|judge), data=wine)

ordinal documentation built on May 2, 2019, 5:47 p.m.