Package: mclogit 0.9.17.1

mclogit: Multinomial Logit Models for Categorical Responses and Discrete Choices

Provides estimators for multinomial logit models in their conditional logit (for discrete choices) and baseline logit variants (for categorical responses), optionally with overdispersion or random effects. 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.

Authors:Martin Elff [aut, cre]

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manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
mclogit/json (API)

# Install 'mclogit' in R:
install.packages('mclogit', repos = c('https://melff.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/melff/mclogit/issues

Pkgdown/docs site:https://melff.github.io

Datasets:
  • electors - Class, Party Position, and Electoral Choice
  • Transport - Choice of Means of Transport

On CRAN:

Conda:

11.81 score 23 stars 4 packages 307 scripts 11k downloads 5 mentions 12 exports 8 dependencies

Last updated from:9984941893. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK407
source / vignettesOK413
linux-release-x86_64OK320
macos-release-arm64OK211
macos-oldrel-arm64OK148
windows-develOK199
windows-releaseOK211
windows-oldrelOK120
wasm-releaseOK277

Exports:dispersiongetSummary.mblogitgetSummary.mclogitgetSummary.mmblogitgetSummary.mmclogitmblogitmclogitmclogit.controlmclogit.fitmmclogit.controlmmclogit.fitPQLMQLrebase

Dependencies:data.tablejsonlitelatticeMASSMatrixmemiscnlmeyaml

Baseline-category logit models
$$\ln\frac | References

Last update: 2026-01-05
Started: 2023-12-27

Conditional logit models
$$\ln\frac | References

Last update: 2026-01-05
Started: 2023-12-27

Bias reduction using Firth's penalized likelihood technique
Application of the technique to conditional and baseline logit models | In case of the models supported by the mclogit package, the difference betweenFirth's PML technique and conventional ML estimation is that it solves for eachcoefficient $\alpha_q$ the modified gradient equation$$0 | U^*(\alpha_q) | \frac{\partial\ell}{\partial\alpha_q}+\frac12\mathrm{tr}\left((\boldsymbol{X}'\boldsymbol{W}\boldsymbol{X})^{-1}\boldsymbol{X}'\frac{\partial\boldsymbol{W}}{\partial\alpha_q}\boldsymbol{X}\right)$$instead of$$0 | U(\alpha_q) | Like the conventional MLE, the mclogit package uses an IWLS-algorithm,however, using a modified working response vector with elements$$y_{ij}^* | \boldsymbol{x}{ij}'\boldsymbol{\alpha} +\frac{y{ij}-\pi_{ij}}{\pi_{ij}}+\frac12\sum_r\sum_s\zeta_{ij,rs}I^{(r,s)}$$where $I^{(r,s)}$ is the $r,s$ element of$(\boldsymbol{X}'\boldsymbol{W}\boldsymbol{X})^{-1}$and$$\begin{aligned}\zeta_{ij,rs}&=(x_{ijr}-\sum_kx_{ikr}\pi_{ik})(x_{ijs}-\sum_l\pi_{il}x_{ils}) | A comparison of results obtained with other packages | References

Last update: 2026-01-05
Started: 2026-01-04

The IWLS algorithm used to fit conditional logit models
$$\frac | \sum_ | \sum_{i,j}\boldsymbol{x}{ij}(n{ij}-n_{i+}\pi_{ij}) | \sum_{i,j}\boldsymbol{x}{ij}n{i+}(y_{ij}-\pi_{ij}) | $$\frac | \sum_ | \sum_{i,j,k}\boldsymbol{x}{ij}n{i+}(\delta_{jk}-\pi_{ij}\pi_{ik})\boldsymbol{x}_{ij}' | $$\boldsymbol | \boldsymbol | \left(\frac | $$\boldsymbol | \boldsymbol{X}'\boldsymbol{W}\boldsymbol{X}\boldsymbol{\alpha}^{(s)}+\boldsymbol{X}'\boldsymbol{N}(\boldsymbol{y}-\boldsymbol{\pi}) | \boldsymbol{X}'\boldsymbol{W}\left(\boldsymbol{X}\boldsymbol{\alpha}^{(s)}+\boldsymbol{W}^-\boldsymbol{N}(\boldsymbol{y}-\boldsymbol{\pi})\right) | $$\boldsymbol | $$y_ | References

Last update: 2025-12-27
Started: 2023-12-27

Approximate Inference for Multinomial Logit Models with Random Effects
The problem | $$\mathcal{L}_{\text{cpl}}(\boldsymbol{y},\boldsymbol{b}) | $$\mathcal{L}_{\text{obs}}(\boldsymbol{y}) | \int\exp\left(\ell_ | The Laplace approximation and PQL | Laplace approximation | $$\ell_{\text{cpl}}(\boldsymbol{y},\boldsymbol{b})\approx\ell(\boldsymbol{y}|\tilde{\boldsymbol{b}};\boldsymbol{\alpha}) | $$\ell^*_ | \ln\int \exp(\ell_ | \ell(\boldsymbol{y}|\tilde{\boldsymbol{b}};\boldsymbol{\alpha}) | \frac12\tilde | \frac12\ln\det(\boldsymbol{\Sigma}) | Penalized quasi-likelihood (PQL) | $$\begin | The Solomon-Cox approximation and MQL | The Solomon-Cox approximation | $$\ell_ | $$\ln\int \exp(\ell_ | \ell(\boldsymbol{y}|\boldsymbol{0};\boldsymbol{\alpha}) | \frac12\boldsymbol{g}_0'\left(\boldsymbol{H}_0+\boldsymbol{\Sigma}^{-1}\right)^{-1}\boldsymbol{g}_0 | Marginal quasi-likelhood (MQL) | References

Last update: 2023-12-27
Started: 2023-12-27

Random effects in baseline logit models and conditional logit models
References

Last update: 2023-12-27
Started: 2023-12-27

The relation between baseline logit and conditional logit models

Last update: 2023-12-27
Started: 2023-12-27

Readme and manuals

Help Manual

Help pageTopics
Overdispersion in Multinomial Logit Modelsdispersion dispersion.mclogit
Class, Party Position, and Electoral Choiceelectors
`getSummary` MethodsgetSummary.mblogit getSummary.mclogit getSummary.mmblogit getSummary.mmclogit
Baseline-Category Logit Models for Categorical and Multinomial Responsesfitted.mblogit mblogit print.mblogit print.mmblogit print.summary.mblogit print.summary.mmblogit summary.mblogit summary.mmblogit weights.mblogit
Conditional Logit Models and Mixed Conditional Logit ModelsAIC.mclogit anova.mclogit BIC.mclogit deviance.mclogit fitted.mclogit logLik.mclogit mclogit print.mclogit print.summary.mclogit print.summary.mmclogit ranef.mmclogit residuals.mclogit summary.mclogit summary.mmclogit update.mclogit vcov.mclogit weights.mclogit
Control Parameters for the Fitting Processmclogit.control mmclogit.control
Internal functions used for model fit.mclogit.fit mmclogit.fitPQLMQL
Predicting responses or linear parts of the baseline-category and conditional logit modelspredict.mblogit predict.mclogit predict.mmblogit predict.mmclogit
Change baseline category of multinomial logit or similar modelrebase rebase.mblogit
Simulating responses from baseline-category and conditional logit modelssimulate.mblogit simulate.mclogit simulate.mmblogit simulate.mmclogit
Choice of Means of TransportTransport