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mclogit (version 0.9.15)

Multinomial Logit Models for Categorical Responses and Discrete Choices

Description

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.

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install.packages('mclogit')

Monthly Downloads

12,599

Version

0.9.15

License

GPL-2

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Maintainer

Martin Elff

Last Published

December 16th, 2025

Functions in mclogit (0.9.15)

simulate.mclogit

Simulating responses from baseline-category and conditional logit models
rebase

Change baseline category of multinomial logit or similar model
dispersion

Overdispersion in Multinomial Logit Models
predict

Predicting responses or linear parts of the baseline-category and conditional logit models
Transport

Choice of Means of Transport
mclogit.control

Control Parameters for the Fitting Process
mblogit

Baseline-Category Logit Models for Categorical and Multinomial Responses
getSummary-methods

`getSummary` Methods
mclogit.fit

Internal functions used for model fit.
electors

Class, Party Position, and Electoral Choice
mclogit

Conditional Logit Models and Mixed Conditional Logit Models