mclogit: Mixed Conditional Logit Models

Specification and estimation of conditional logit models of binary responses and multinomial counts is provided, with or without random effects. 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.

Version: 0.6
Depends: stats, Matrix
Imports: memisc, methods
Published: 2018-05-10
Author: Martin Elff
Maintainer: Martin Elff <mclogit at elff.eu>
BugReports: http://github.com/melff/mclogit/issues
License: GPL-2
URL: http://www.elff.eu/software/mclogit/,http://github.com/melff/mclogit/
NeedsCompilation: no
Materials: NEWS ChangeLog
CRAN checks: mclogit results

Downloads:

Reference manual: mclogit.pdf
Package source: mclogit_0.6.tar.gz
Windows binaries: r-devel: mclogit_0.6.zip, r-release: mclogit_0.6.zip, r-oldrel: mclogit_0.6.zip
OS X binaries: r-release: mclogit_0.6.tgz, r-oldrel: mclogit_0.6.tgz
Old sources: mclogit archive

Reverse dependencies:

Reverse imports: mztwinreg
Reverse enhances: prediction, stargazer

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