| latentFactoR-package {latentFactoR} | R Documentation |
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).
Author(s)
Alexander P. Christensen <alexpaulchristensen@gmail.com>, Maria Dolores Nieto Canaveras <mnietoca@nebrija.es>, Hudson Golino <hfg9s@virginia.edu>, Luis Eduardo Garrido <luisgarrido@pucmm.edu>
References
Christensen, A. P., Garrido, L. E., & Golino, H. (2022).
Unique variable analysis: A network psychometrics method to detect local dependence.
PsyArXiv
Garrido, L. E., Abad, F. J., & Ponsoda, V. (2011).
Performance of Velicer’s minimum average partial factor retention method with categorical variables.
Educational and Psychological Measurement, 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. Psychological Methods, 25(3), 292-320.