Package: EGAnet
Title: Exploratory Graph Analysis – a Framework for Estimating the
        Number of Dimensions in Multivariate Data using Network
        Psychometrics
Version: 2.2.0
Date: 2025-03-05
Authors@R: c(person("Hudson", "Golino", email = "hfg9s@virginia.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1601-1447")),
	     person("Alexander", "Christensen", email = "alexpaulchristensen@gmail.com", role = "aut", comment = c(ORCID = "0000-0002-9798-7037")),
	     person("Robert", "Moulder", email = "rgm4fd@virginia.edu", role = "ctb", comment = c(ORCID = "0000-0001-7504-9560")),
	     person("Luis", "E. Garrido", email = "garrido.luiseduardo@gmail.com", role = "ctb", comment = c(ORCID = "0000-0001-8932-6063")),
	     person("Laura", "Jamison", email = "lj5yn@virginia.edu", role = "ctb", comment = c(ORCID = "0000-0002-4656-8684")),
	     person("Dingjing", "Shi", email = "dshi@ou.edu", role = "ctb", comment = c(ORCID = "0000-0002-5652-3818")))
Maintainer: Hudson Golino <hfg9s@virginia.edu>
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.
Depends: R (>= 3.5.0)
License: AGPL (>= 3.0)
Encoding: UTF-8
LazyData: true
Imports: dendextend, fungible, future, future.apply, GGally, ggplot2,
        ggpubr, glasso, glassoFast, GPArotation, igraph (>= 1.3.0),
        lavaan, Matrix, methods, network, progressr, qgraph, semPlot,
        sna, stats
Suggests: DEoptim, fitdistrplus, gridExtra, knitr, markdown, pbapply,
        progress, psych, pwr, RColorBrewer
URL: https://r-ega.net
BugReports: https://github.com/hfgolino/EGAnet/issues
RoxygenNote: 7.3.2
NeedsCompilation: yes
Packaged: 2025-03-07 14:20:55 UTC; Hudson
Author: Hudson Golino [aut, cre] (<https://orcid.org/0000-0002-1601-1447>),
  Alexander Christensen [aut] (<https://orcid.org/0000-0002-9798-7037>),
  Robert Moulder [ctb] (<https://orcid.org/0000-0001-7504-9560>),
  Luis E. Garrido [ctb] (<https://orcid.org/0000-0001-8932-6063>),
  Laura Jamison [ctb] (<https://orcid.org/0000-0002-4656-8684>),
  Dingjing Shi [ctb] (<https://orcid.org/0000-0002-5652-3818>)
Repository: CRAN
Date/Publication: 2025-03-07 16:40:07 UTC
Built: R 4.3.3; x86_64-w64-mingw32; 2025-04-07 04:06:12 UTC; windows
Archs: x64
