Package: nestedLogit Title: Nested Dichotomy Logistic Regression Models Version: 0.4.2 Date: 2026-05-27 Authors@R: c( person("John", "Fox", , "jfox@mcmaster.ca", role = "aut", comment = c(ORCID = "0000-0002-1196-8012")), person("Michael", "Friendly", , "friendly@yorku.ca", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3237-0941")), person("Achim", "Zeileis", , "Achim.Zeileis@uibk.ac.at", role = "ctb", comment = c(ORCID = "0000-0003-0918-3766")) ) Description: 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. License: GPL (>=2) URL: https://github.com/friendly/nestedLogit, https://friendly.github.io/nestedLogit/ BugReports: https://github.com/friendly/nestedLogit/issues Depends: R (>= 4.1.0) Imports: broom, car, dplyr, effects, graphics, grDevices, stats, stringr, tibble, scales Suggests: AER, carData, equatiomatic, DescTools, geomtextpath, ggplot2, ggeffects, here, insight, lobstr, knitr, nnet, parameters, performance, rmarkdown, see, spelling, testthat, tidyr, MASS, VGAM, mlogit, vcd VignetteBuilder: knitr, rmarkdown Encoding: UTF-8 Language: en-US LazyData: TRUE Roxygen: list(markdown = TRUE) Config/roxygen2/version: 8.0.0 Config/pak/sysreqs: cmake make libicu-dev Repository: https://friendly.r-universe.dev Date/Publication: 2026-05-27 22:10:50 UTC RemoteUrl: https://github.com/friendly/nestedLogit RemoteRef: HEAD RemoteSha: b0a0ac7fee00170ca9da9f7cd7e336d4021218a0 NeedsCompilation: no Packaged: 2026-07-04 12:59:39 UTC; root Author: John Fox [aut] (ORCID: ), Michael Friendly [aut, cre] (ORCID: ), Achim Zeileis [ctb] (ORCID: ) Maintainer: Michael Friendly