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.

AuthorMartin Elff
Date of publication2016-12-25 23:44:32
MaintainerMartin Elff <mclogit@elff.eu>
LicenseGPL-2
Version0.4.4
http://www.elff.eu/software/mclogit/,http://github.com/melff/mclogit/

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Files in this package

mclogit
mclogit/inst
mclogit/inst/NEWS.Rd
mclogit/inst/ChangeLog
mclogit/NAMESPACE
mclogit/demo
mclogit/demo/mclogit.test.R
mclogit/demo/00Index
mclogit/data
mclogit/data/Transport.rda
mclogit/data/electors.rda
mclogit/R
mclogit/R/mclogit.R mclogit/R/mblogit.R mclogit/R/anova-mclogit.R mclogit/R/getSummary-mblogit.R mclogit/R/getSummary-mclogit.R mclogit/R/AIC-mclogit.R mclogit/R/zzz.R
mclogit/MD5
mclogit/DESCRIPTION
mclogit/man
mclogit/man/mclogit_control.Rd mclogit/man/getSummary-mclogit.Rd mclogit/man/electors.Rd mclogit/man/Transport.Rd mclogit/man/mclogit.Rd mclogit/man/mclogit.fit.Rd mclogit/man/mblogit.Rd

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