latentFactoR: Data Simulation Based on Latent Factors

Generates data based on latent factor models. Data can be continuous, polytomous, dichotomous, or mixed. Skews, cross-loadings, wording effects, population errors, and local dependencies can be added. All parameters can be manipulated. Data categorization is based on Garrido, Abad, and Ponsoda (2011) <doi:10.1177/0013164410389489>.

Version:	0.0.6
Depends:	R (≥ 3.6.0)
Imports:	BBmisc, EGAnet, fspe, googledrive, ineq, lavaan, Matrix, methods, mlr, mvtnorm, psych, rstudioapi, xgboost
Suggests:	ggplot2
Published:	2024-04-18
DOI:	10.32614/CRAN.package.latentFactoR
Author:	Alexander Christensen [aut, cre], Luis Eduardo Garrido [aut], Maria Dolores Nieto Canaveras [aut], Hudson Golino [aut], Marcos Jimenez [aut], Francisco Abad [ctb], Eduardo Garcia-Garzon [ctb], Vithor Franco [aut]
Maintainer:	Alexander Christensen <alexpaulchristensen at gmail.com>
License:	GPL (≥ 3.0)
NeedsCompilation:	no
Citation:	latentFactoR citation info
Materials:	NEWS
CRAN checks:	latentFactoR results

Documentation:

Reference manual:

latentFactoR.pdf

Downloads:

Package source:	latentFactoR_0.0.6.tar.gz
Windows binaries:	r-devel: latentFactoR_0.0.6.zip, r-release: latentFactoR_0.0.6.zip, r-oldrel: latentFactoR_0.0.6.zip
macOS binaries:	r-release (arm64): latentFactoR_0.0.6.tgz, r-oldrel (arm64): latentFactoR_0.0.6.tgz, r-release (x86_64): latentFactoR_0.0.6.tgz, r-oldrel (x86_64): latentFactoR_0.0.6.tgz
Old sources:	latentFactoR archive

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