hfgolino/EGA: Exploratory Graph Analysis: Estimating the number of dimensions in psychological data

An implementation of the Exploratory Graph Analysis (EGA). EGA is part of a new area called network psychometrics that focuses on the estimation of undirected network models in psychological datasets. EGA estimates the number of dimensions or factors using graphical lasso or TMFG and a weighted network community analysis. A bootstrap method for verifying the stability of the estimation is also available. The fit of the structure suggested by EGA can be verified using confirmatory factor analysis and a direct way to convert the EGA structure to CFA is also implemented. Documentation and examples are available.

Getting started

Package details

AuthorHudson F. Golino
MaintainerHudson F. Golino <[email protected]>
LicenseGPL (>= 3.0)
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
hfgolino/EGA documentation built on Feb. 28, 2019, 9:12 a.m.