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ordinal  

Regression Models for Ordinal Data
View on CRAN: Click here


Download and install ordinal package within the R console
Install from CRAN:
install.packages("ordinal")

Install from Github:
library("remotes")
install_github("cran/ordinal")

Install by package version:
library("remotes")
install_version("ordinal", "2025.12-29")



Attach the package and use:
library("ordinal")
Maintained by
Rune Haubo Bojesen Christensen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2010-03-07
Latest Update: 2024-08-19
Description:
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.
How to cite:
Rune Haubo Bojesen Christensen (2010). ordinal: Regression Models for Ordinal Data. R package version 2025.12-29, https://cran.r-project.org/web/packages/ordinal. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 06:37), 2010.03-04 (2010-03-07 18:09), 2010.04-22 (2010-04-23 10:26), 2010.05-06 (2010-05-06 23:00), 2010.05-17 (2010-05-22 08:36), 2010.06-12 (2010-06-13 10:22), 2010.07-06 (2010-07-24 22:21), 2010.07-23 (2010-09-28 15:18), 2010.12-13 (2010-12-14 16:52), 2010.12-15 (2010-12-16 13:53), 2011.04-21 (2011-05-02 12:06), 2011.05-10 (2011-05-16 14:16), 2011.08-11 (2011-08-11 12:07), 2011.08-12 (2011-08-12 22:01), 2011.09-14 (2011-09-14 08:21), 2012.01-19 (2012-01-20 11:03), 2012.09-10 (2012-09-10 12:22), 2012.09-11 (2012-09-12 07:14), 2013.9-30 (2013-09-30 12:46), 2014.11-12 (2014-11-13 14:50), 2014.11-14 (2014-11-14 14:35), 2014.12-22 (2014-12-23 16:21), 2015.1-21 (2015-01-21 21:29), 2015.6-28 (2015-06-28 16:50), 2018.4-19 (2018-04-19 21:17), 2018.8-25 (2018-08-26 00:20), 2019.3-9 (2019-03-09 13:40), 2019.4-25 (2019-04-25 22:30), 2019.12-10 (2019-12-15 23:10), 2022.11-16 (2022-11-16 23:30), 2023.12-4.1 (2024-08-19 11:01), 2023.12-4 (2023-12-04 12:50)
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