PLmixed: Estimate (Generalized) Linear Mixed Models with Factor Structures

Utilizes the 'lme4' package and the optim() function from 'stats' to estimate (generalized) linear mixed models (GLMM) with factor structures using a profile likelihood approach, as outlined in Jeon and Rabe-Hesketh (2012) <doi:10.3102/1076998611417628>. Factor analysis and item response models can be extended to allow for an arbitrary number of nested and crossed random effects, making it useful for multilevel and cross-classified models.

Version: 0.1.2
Depends: R (≥ 3.2.2)
Imports: lme4, Matrix (≥ 1.1.1), numDeriv, stats
Suggests: knitr, rmarkdown, irtoys
Published: 2017-10-13
Author: Minjeong Jeon [aut], Nicholas Rockwood [aut, cre]
Maintainer: Nicholas Rockwood <rockwood.19 at osu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README
In views: Psychometrics
CRAN checks: PLmixed results

Downloads:

Reference manual: PLmixed.pdf
Vignettes: PLmixed: An Introduction
Package source: PLmixed_0.1.2.tar.gz
Windows binaries: r-devel: PLmixed_0.1.2.zip, r-release: PLmixed_0.1.2.zip, r-oldrel: PLmixed_0.1.2.zip
OS X El Capitan binaries: r-release: PLmixed_0.1.2.tgz
OS X Mavericks binaries: r-oldrel: PLmixed_0.1.2.tgz
Old sources: PLmixed archive

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