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 |
| 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 binaries: | r-release: PLmixed_0.1.2.tgz, r-oldrel: PLmixed_0.1.2.tgz |
| Old sources: | PLmixed archive |
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