nestedLogit: Nested Dichotomy Logistic Regression Models

Provides functions for specifying and fitting nested dichotomy logistic regression models for a multi-category response and methods for summarising and plotting those models. Nested dichotomies are statistically independent, and hence provide an additive decomposition of tests for the overall 'polytomous' response. When the dichotomies make sense substantively, this method can be a simpler alternative to the standard 'multinomial' logistic model which compares response categories to a reference level. See: J. Fox (2016), "Applied Regression Analysis and Generalized Linear Models", 3rd Ed., ISBN 1452205663.

Version: 0.3.2
Depends: R (≥ 3.5.0)
Imports: broom, car, dplyr, effects, graphics, grDevices, stats, stringr, tibble
Suggests: carData, geomtextpath, ggplot2, ggeffects, here, lobstr, knitr, nnet, rmarkdown, scales, spelling, testthat, tidyr
Published: 2023-06-22
DOI: 10.32614/CRAN.package.nestedLogit
Author: John Fox ORCID iD [aut], Michael Friendly ORCID iD [aut, cre], Achim Zeileis ORCID iD [ctb]
Maintainer: Michael Friendly <friendly at yorku.ca>
BugReports: https://github.com/friendly/nestedLogit/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/friendly/nestedLogit
NeedsCompilation: no
Language: en-US
Materials: NEWS
CRAN checks: nestedLogit results

Documentation:

Reference manual: nestedLogit.pdf
Vignettes: Nested-dichotomies logistic regression models
Plotting nestedLogit models with ggplot2
Standard Errors of Fitted Category Probabilities by the Delta Method for the Nested Logit Model

Downloads:

Package source: nestedLogit_0.3.2.tar.gz
Windows binaries: r-devel: nestedLogit_0.3.2.zip, r-release: nestedLogit_0.3.2.zip, r-oldrel: nestedLogit_0.3.2.zip
macOS binaries: r-release (arm64): nestedLogit_0.3.2.tgz, r-oldrel (arm64): nestedLogit_0.3.2.tgz, r-release (x86_64): nestedLogit_0.3.2.tgz, r-oldrel (x86_64): nestedLogit_0.3.2.tgz
Old sources: nestedLogit archive

Reverse dependencies:

Reverse suggests: ggeffects, insight, parameters, performance

Linking:

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