mclogit: Multinomial Logit Models, with or without Random Effects or Overdispersion

Provides estimators for multinomial logit models in their conditional logit and baseline logit variants, with or without random effects, with or without overdispersion. Random effects models are estimated using the PQL technique (based on a Laplace approximation) or the MQL technique (based on a Solomon-Cox approximation). Estimates should be treated with caution if the group sizes are small.

Version:	0.9.6
Depends:	stats, Matrix
Imports:	memisc, methods
Suggests:	MASS, nnet
Enhances:	emmeans
Published:	2022-10-27
DOI:	10.32614/CRAN.package.mclogit
Author:	Martin Elff
Maintainer:	Martin Elff <mclogit at elff.eu>
BugReports:	https://github.com/melff/mclogit/issues
License:	GPL-2
URL:	http://mclogit.elff.eu,https://github.com/melff/mclogit/
NeedsCompilation:	no
Materials:	NEWS ChangeLog
In views:	MixedModels
CRAN checks:	mclogit results

Documentation:

Reference manual:

mclogit.pdf

Downloads:

Package source:	mclogit_0.9.6.tar.gz
Windows binaries:	r-devel: mclogit_0.9.6.zip, r-release: mclogit_0.9.6.zip, r-oldrel: mclogit_0.9.6.zip
macOS binaries:	r-release (arm64): mclogit_0.9.6.tgz, r-oldrel (arm64): mclogit_0.9.6.tgz, r-release (x86_64): mclogit_0.9.6.tgz, r-oldrel (x86_64): mclogit_0.9.6.tgz
Old sources:	mclogit archive

Reverse dependencies:

Reverse imports:	abn, EQUALSTATS, projpred
Reverse suggests:	ggeffects, insight, marginaleffects, parameters, performance, WeightIt
Reverse enhances:	prediction, stargazer

Linking:

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