aMNLFA: Automated Moderated Nonlinear Factor Analysis Using 'Mplus'

Automated generation, running, and interpretation of moderated nonlinear factor analysis models for obtaining scores from observed variables, using the method described by Gottfredson and colleagues (2019) <doi:10.1016/j.addbeh.2018.10.031>. This package creates 'Mplus' input files which may be run iteratively to test two different types of covariate effects on items: (1) latent variable impact (both mean and variance); and (2) differential item functioning. After sequentially testing for all effects, it also creates a final model by including all significant effects after adjusting for multiple comparisons. Finally, the package creates a scoring model which uses the final values of parameter estimates to generate latent variable scores.

Version: 1.0.0
Depends: R (≥ 3.1.0)
Imports: grDevices, graphics, stats, utils, ggplot2, MplusAutomation, reshape2, gridExtra, stringr, plyr, devtools, dplyr
Published: 2021-06-25
Author: Veronica Cole [aut, cre], Nisha Gottfredson [aut], Michael Giordano [aut], Tim Janssen [ctb]
Maintainer: Veronica Cole <colev at wfu.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: aMNLFA results

Documentation:

Reference manual: aMNLFA.pdf

Downloads:

Package source: aMNLFA_1.0.0.tar.gz
Windows binaries: r-devel: aMNLFA_1.0.0.zip, r-release: aMNLFA_1.0.0.zip, r-oldrel: aMNLFA_1.0.0.zip
macOS binaries: r-release (arm64): aMNLFA_1.0.0.tgz, r-release (x86_64): aMNLFA_1.0.0.tgz, r-oldrel: aMNLFA_1.0.0.tgz
Old sources: aMNLFA archive

Reverse dependencies:

Reverse enhances: mnlfa

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