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EGAnet (version 2.0.7)

EGAnet-package: EGAnet-package

Description

Implements the Exploratory Graph Analysis (EGA) framework for dimensionality and psychometric assessment. EGA estimates the number of dimensions in psychological data using network estimation methods and community detection algorithms. A bootstrap method is provided to assess the stability of dimensions and items. Fit is evaluated using the Entropy Fit family of indices. Unique Variable Analysis evaluates the extent to which items are locally dependent (or redundant). Network loadings provide similar information to factor loadings and can be used to compute network scores. A bootstrap and permutation approach are available to assess configural and metric invariance. Hierarchical structures can be detected using Hierarchical EGA. Time series and intensive longitudinal data can be analyzed using Dynamic EGA, supporting individual, group, and population level assessments.

Arguments

Author

Hudson Golino <hfg9s@virginia.edu> and Alexander P. Christensen <alexpaulchristensen@gmail.com>

References

Christensen, A. P. (2023). Unidimensional community detection: A Monte Carlo simulation, grid search, and comparison. PsyArXiv.
# Related functions: community.unidimensional

Christensen, A. P., Garrido, L. E., & Golino, H. (2023). Unique variable analysis: A network psychometrics method to detect local dependence. Multivariate Behavioral Research.
# Related functions: UVA

Christensen, A. P., Garrido, L. E., Guerra-Pena, K., & Golino, H. (2023). Comparing community detection algorithms in psychometric networks: A Monte Carlo simulation. Behavior Research Methods.
# Related functions: EGA

Christensen, A. P., & Golino, H. (2021a). Estimating the stability of the number of factors via Bootstrap Exploratory Graph Analysis: A tutorial. Psych, 3(3), 479-500.
# Related functions: bootEGA, dimensionStability, # and itemStability

Christensen, A. P., & Golino, H. (2021b). Factor or network model? Predictions from neural networks. Journal of Behavioral Data Science, 1(1), 85-126.
# Related functions: LCT

Christensen, A. P., & Golino, H. (2021c). On the equivalency of factor and network loadings. Behavior Research Methods, 53, 1563-1580.
# Related functions: LCT and net.loads

Christensen, A. P., Golino, H., & Silvia, P. J. (2020). A psychometric network perspective on the validity and validation of personality trait questionnaires. European Journal of Personality, 34, 1095-1108.
# Related functions: bootEGA, dimensionStability, # EGA, itemStability, and UVA

Christensen, A. P., Gross, G. M., Golino, H., Silvia, P. J., & Kwapil, T. R. (2019). Exploratory graph analysis of the Multidimensional Schizotypy Scale. Schizophrenia Research, 206, 43-51. # Related functions: CFA and EGA

Golino, H., Christensen, A. P., Moulder, R., Kim, S., & Boker, S. M. (2021). 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. Psychometrika.
# Related functions: dynEGA and simDFM

Golino, H., & Demetriou, A. (2017). Estimating the dimensionality of intelligence like data using Exploratory Graph Analysis. Intelligence, 62, 54-70.
# Related functions: EGA

Golino, H., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PLoS ONE, 12, e0174035.
# Related functions: CFA, EGA, and bootEGA

Golino, H., Moulder, R., Shi, D., Christensen, A. P., Garrido, L. E., Nieto, M. D., Nesselroade, J., Sadana, R., Thiyagarajan, J. A., & Boker, S. M. (2020). Entropy fit indices: New fit measures for assessing the structure and dimensionality of multiple latent variables. Multivariate Behavioral Research.
# Related functions: entropyFit, tefi, and vn.entropy

Golino, H., Nesselroade, J. R., & Christensen, A. P. (2022). Towards a psychology of individuals: The ergodicity information index and a bottom-up approach for finding generalizations. PsyArXiv.
# Related functions: boot.ergoInfo, ergoInfo, jsd, and infoCluster

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.
# Related functions: EGA

Golino, H., Thiyagarajan, J. A., Sadana, M., Teles, M., Christensen, A. P., & Boker, S. M. (2020). Investigating the broad domains of intrinsic capacity, functional ability, and environment: An exploratory graph analysis approach for improving analytical methodologies for measuring healthy aging. PsyArXiv.
# Related functions: EGA.fit and tefi

Jamison, L., Christensen, A. P., & Golino, H. (2021). Optimizing Walktrap's community detection in networks using the Total Entropy Fit Index. PsyArXiv.
# Related functions: EGA.fit and tefi

Jamison, L., Golino, H., & Christensen, A. P. (2023). Metric invariance in exploratory graph analysis via permutation testing. PsyArXiv.
# Related functions: invariance

Shi, D., Christensen, A. P., Day, E., Golino, H., & Garrido, L. E. (2023). A Bayesian approach for dimensionality assessment in psychological networks. PsyArXiv
# Related functions: EGA

See Also