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 |
Reference manual: | mclogit.pdf |
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 imports: | abn, EQUALSTATS, projpred |
Reverse suggests: | insight, marginaleffects, parameters, performance, WeightIt |
Reverse enhances: | prediction, stargazer |
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