mclogit: Mixed Conditional Logit Models

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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 variants of the model uses a Laplace approximation (or PQL) approach and thus should be used only if groups sizes are large.

Author
Martin Elff
Date of publication
2016-01-16 21:50:53
Maintainer
Martin Elff <mclogit@elff.eu>
License
GPL-2
Version
0.4.3
URLs

View on R-Forge

Man pages

electors
Class, Party Position, and Electoral Choice
getSummary-mclogit
'getSummary' Methods
mblogit
Multinomial (Baseline) Logit Models for Categorical and...
mclogit
Conditional Logit Models and Mixed Conditional Logit Models
mclogit_control
Control Parameters for the Fitting Process
mclogit.fit
Internal functions used for model fit.
Transport
Choice of Means of Transport

Files in this package

mclogit/DESCRIPTION
mclogit/NAMESPACE
mclogit/R
mclogit/R/AIC-mclogit.R
mclogit/R/anova-mclogit.R
mclogit/R/getSummary-mblogit.R
mclogit/R/getSummary-mclogit.R
mclogit/R/mblogit.R
mclogit/R/mclogit.R
mclogit/R/zzz.R
mclogit/data
mclogit/data/Transport.rda
mclogit/data/electors.rda
mclogit/demo
mclogit/demo/00Index
mclogit/demo/mclogit.test.R
mclogit/inst
mclogit/inst/ChangeLog
mclogit/man
mclogit/man/Transport.Rd
mclogit/man/electors.Rd
mclogit/man/getSummary-mclogit.Rd
mclogit/man/mblogit.Rd
mclogit/man/mclogit.Rd
mclogit/man/mclogit.fit.Rd
mclogit/man/mclogit_control.Rd