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

Utilizes the 'lme4' and 'optimx' packages (previously 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> and Rockwood and Jeon (2019) <doi:10.1080/00273171.2018.1516541>. 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: 0.1.4
Depends: R (≥ 3.2.2)
Imports: lme4, Matrix (≥ 1.1.1), numDeriv, stats, optimx
Suggests: knitr, rmarkdown, irtoys
Published: 2019-08-19
Author: Minjeong Jeon [aut], Nicholas Rockwood [aut, cre]
Maintainer: Nicholas Rockwood <nrockwood at llu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: PLmixed citation info
Materials: README
In views: Psychometrics
CRAN checks: PLmixed results

Downloads:

Reference manual: PLmixed.pdf
Vignettes: PLmixed: An Introduction
Package source: PLmixed_0.1.4.tar.gz
Windows binaries: r-devel: PLmixed_0.1.4.zip, r-devel-gcc8: PLmixed_0.1.4.zip, r-release: PLmixed_0.1.4.zip, r-oldrel: PLmixed_0.1.4.zip
OS X binaries: r-release: PLmixed_0.1.4.tgz, r-oldrel: PLmixed_0.1.4.tgz
Old sources: PLmixed archive

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