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. 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: 0.5.1
Depends: stats, Matrix
Imports: memisc, methods
Published: 2017-07-17
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_0.5.1.tar.gz
Windows binaries: r-devel: mclogit_0.5.1.zip, r-release: mclogit_0.5.1.zip, r-oldrel: mclogit_0.5.1.zip
OS X El Capitan binaries: r-release: mclogit_0.4.4.tgz
OS X Mavericks binaries: r-oldrel: mclogit_0.5.1.tgz
Old sources: mclogit archive

Reverse dependencies:

Reverse imports: mztwinreg
Reverse enhances: prediction, stargazer

Linking:

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