R/latentFactoR.R

In latentFactoR: Data Simulation Based on Latent Factors

#' latentFactoR--package
#' 
#' @description Generates data based on latent factor models.
#' Data can be continuous, polytomous, dichotomous, or mixed.
#' Skew, cross-loadings, and population error can be added.
#' All parameters can be manipulated. Data categorization is based on Garrido, Abad, and Ponsoda (2011).
#' 
#' @references
#' Christensen, A. P., Garrido, L. E., & Golino, H. (2022). \cr
#' Unique variable analysis: A network psychometrics method to detect local dependence. \cr
#' \emph{PsyArXiv}
#' 
#' Garrido, L. E., Abad, F. J., & Ponsoda, V. (2011). \cr
#' Performance of Velicer’s minimum average partial factor retention method with categorical variables. \cr
#' \emph{Educational and Psychological Measurement}, \emph{71}(3), 551-570.
#' 
#' Golino, H., Shi, D., Christensen, A. P., Garrido, L. E., Nieto, M. D., Sadana, R., ... & Martinez-Molina, A. (2020).
#' Investigating the performance of exploratory graph analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial.
#' \emph{Psychological Methods}, \emph{25}(3), 292-320.
#'
#' @author
#' Alexander P. Christensen <alexpaulchristensen@gmail.com>,
#' Maria Dolores Nieto Canaveras <mnietoca@nebrija.es>,
#' Hudson Golino <hfg9s@virginia.edu>,
#' Luis Eduardo Garrido <luisgarrido@pucmm.edu>
#' 
#' @importFrom utils packageDescription
#'
"_PACKAGE"
#> [1] "_PACKAGE"