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mclogit (version 0.4.4)

Mixed Conditional Logit Models

Description

Specification and estimation of conditional logit models of binary responses and multinomial counts is provided, with or without alternative-specific random effects (random intercepts only, no random slopes yet). The current implementation of the estimator for random effects variances uses a Laplace approximation (or PQL) approach and thus should be used only if groups sizes are large.

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Install

install.packages('mclogit')

Monthly Downloads

5,917

Version

0.4.4

License

GPL-2

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Maintainer

Martin Elff

Last Published

December 25th, 2016

Functions in mclogit (0.4.4)

getSummary-methods

`getSummary` Methods
mblogit

Multinomial (Baseline) Logit Models for Categorical and Multinommial Responses
mclogit.control

Control Parameters for the Fitting Process
mclogit.fit

Internal functions used for model fit.
electors

Class, Party Position, and Electoral Choice
mclogit

Conditional Logit Models and Mixed Conditional Logit Models
Transport

Choice of Means of Transport