The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

EGAnet: Exploratory Graph Analysis – a Framework for Estimating the Number of Dimensions in Multivariate Data using Network Psychometrics

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.

Version: 2.1.0
Depends: R (≥ 3.5.0)
Imports: dendextend, fungible, future, future.apply, glasso, GGally, ggplot2, ggpubr, GPArotation, igraph (≥ 1.3.0), lavaan, Matrix, methods, network, progressr, qgraph, semPlot, sna, stats
Suggests: fitdistrplus, gridExtra, knitr, markdown, pbapply, progress, psych, pwr, RColorBrewer
Published: 2024-11-09
DOI: 10.32614/CRAN.package.EGAnet
Author: Hudson Golino ORCID iD [aut, cre], Alexander Christensen ORCID iD [aut], Robert Moulder ORCID iD [ctb], Luis E. Garrido ORCID iD [ctb], Laura Jamison ORCID iD [ctb], Dingjing Shi ORCID iD [ctb]
Maintainer: Hudson Golino <hfg9s at virginia.edu>
BugReports: https://github.com/hfgolino/EGAnet/issues
License: GPL (≥ 3.0)
URL: https://r-ega.net
NeedsCompilation: yes
Citation: EGAnet citation info
Materials: NEWS
In views: Psychometrics
CRAN checks: EGAnet results

Documentation:

Reference manual: EGAnet.pdf

Downloads:

Package source: EGAnet_2.1.0.tar.gz
Windows binaries: r-devel: EGAnet_2.1.0.zip, r-release: EGAnet_2.1.0.zip, r-oldrel: EGAnet_2.1.0.zip
macOS binaries: r-release (arm64): EGAnet_2.1.0.tgz, r-oldrel (arm64): EGAnet_2.1.0.tgz, r-release (x86_64): EGAnet_2.1.0.tgz, r-oldrel (x86_64): EGAnet_2.1.0.tgz
Old sources: EGAnet archive

Reverse dependencies:

Reverse imports: latentFactoR
Reverse suggests: FAfA, parameters

Linking:

Please use the canonical form https://CRAN.R-project.org/package=EGAnet to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.