Contact: [email protected]
Contact: [email protected]
The EGAnet package is currently supported by two University of Virginia grants, one from the STAR - Support Transformative Autism Research initiative and one from the Democracy Initiative.
The old EGA package is now EGAnet, and is now available in The Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/EGAnet/index.html
Christensen, A. P., & Golino, H. (under review). On the equivalency of factor and network loadings. PsyArXiv. doi:10.31234/osf.io/xakez
Christensen, A. P., Golino, H., & Silvia, P. J. (in press). A psychometric network perspective on the validity and validation of personality trait questionnaires. European Journal of Personality. doi:10.1002/per.2265
Golino, H., Christensen, A. P., Moulder, R. G., Kim, S., & Boker, S. M. (under review). Modeling latent topics in social media using Dynamic Exploratory Graph Analysis: The case of the right-wing and left-wing trolls in the 2016 US elections. PsyArXiv. doi:10.31234/osf.io/tfs7c.
Golino, H., & Demetriou, A. (2017). Estimating the dimensionality of intelligence like data using Exploratory Graph Analysis. Intelligence, 62, 54-70. doi:j.intell.2017.02.007
Golino, H., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PLoS ONE, 12, e0174035. doi:10.1371/journal.pone.0174035
Golino, H., Moulder, R. G., Shi, D., Christensen, A. P., Garrido, L. E., Neito, M. D., Nesselroade, J., Sadana, R., Thiyagarajan, J. A., & Boker, S. M. (in press). Entropy fit indices: New fit measures for assessing the structure and dimensionality of multiple latent variables. Multivariate Behavioral Research. doi:10.31234/osf.io/mtka2
Golino, H., Shi, D., Christensen, A. P., Garrido, L. E., Nieto, M. D., Sadana, R., Thiyagarajan, J. A., & 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, 292-320. doi:10.1037/met0000255