Exploratory Graph Analysis – a Framework for Estimating the Number of Dimensions in Multivariate Data using Network Psychometrics
Automatic correlations
Bootstrap Test for the Ergodicity Information Index
Bootstrap Exploratory Graph Analysis
CFA Fit of EGA or hierEGA Structure
EGA Color Palettes
Compares Community Detection Solutions Using Permutation
Applies the Consensus Clustering Method (Louvain only)
Apply a Community Detection Algorithm
Homogenize Community Memberships
Approaches to Detect Unidimensional Communities
Visually Compare Two or More EGAnet plots
Convert networks to igraph
Convert networks to tidygraph
Dimension Stability Statistics from bootEGA
Intra- and Inter-individual dynEGA
Dynamic Exploratory Graph Analysis
EBICglasso from qgraph 1.4.4
Estimates EGA for Multidimensional Structures
EGA Optimal Model Fit using the Total Entropy Fit Index (tefi)
Exploratory Graph Analysis
EGAnet-package
S3 Plot Methods for EGAnet
Time-delay Embedding
Entropy Fit Index
Ergodicity Information Index
Frobenius Norm (Similarity)
Generalized Total Entropy Fit Index using Von Neumman's entropy (Quant...
Generalized Local Linear Approximation
Hierarchical EGA
Convert network to matrix
Information Theoretic Mixture Clustering for dynEGA
Information Theory Metrics
Measurement Invariance of EGA Structure
Item Stability Statistics from bootEGA
Jensen-Shannon Distance
Loadings Comparison Test
Computes the (Signed) Modularity Statistic
Network Loadings
Network Scores
Compares Network Structures Using Permutation
Apply a Network Estimation Method
Predict New Data based on Network
Computes Polychoric Correlations
Random-Intercept EGA
Simulate data following a Dynamic Factor Model
Total Entropy Fit Index using Von Neumman's entropy (Quantum Informati...
Triangulated Maximally Filtered Graph
Total Correlation
Total Correlation Matrix
Unique Variable Analysis
Entropy Fit Index using Von Neumman's entropy (Quantum Information The...
Weighted Topological Overlap
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.