mclogit: Mixed Conditional Logit Models

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.

Install the latest version of this package by entering the following in R:
AuthorMartin Elff
Date of publication2016-12-25 23:44:32
MaintainerMartin Elff <>

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AIC.mclogit Man page
anova.mclogit Man page
BIC.mclogit Man page
deviance.mclogit Man page
electors Man page
fitted.mblogit Man page
fitted.mclogit Man page
getSummary.mblogit Man page
getSummary.mclogit Man page
logLik.mclogit Man page
mblogit Man page
mclogit Man page
mclogit.control Man page Man page Man page
predict.mblogit Man page
predict.mclogit Man page
print.mblogit Man page
print.mclogit Man page
print.summary.mblogit Man page
print.summary.mclogit Man page
residuals.mclogit Man page
summary.mblogit Man page
summary.mclogit Man page
Transport Man page
vcov.mclogit Man page

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