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
Author: Alexander Christensen ORCID iD [aut, cre], Luis Eduardo Garrido ORCID iD [aut], Maria Dolores Nieto Canaveras [aut], Hudson Golino ORCID iD [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-prerel: latentFactoR_0.0.6.zip, r-release: not available, r-oldrel: latentFactoR_0.0.6.zip
macOS binaries: r-prerel (arm64): latentFactoR_0.0.6.tgz, r-release (arm64): latentFactoR_0.0.6.tgz, r-oldrel (arm64): latentFactoR_0.0.6.tgz, r-prerel (x86_64): latentFactoR_0.0.6.tgz, r-release (x86_64): latentFactoR_0.0.6.tgz
Old sources: latentFactoR archive

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