Essential Documentation for the EGAnet Package in R

R Package Documentation

Explore valuable documentation and insights to make the most of the EGAnet package in R. Get ready to unlock the full potential of the EGAnet package!

Basic details of the EGAnet package

At R Basics, our goal is to make it easy for you to find documentation about the EGAnet package. That’s why we’ve compiled all the key information in one place. Dive into the details below to understand how this package can improve your work.

Title: Exploratory Graph Analysis – a Framework for Estimating the Number of Dimensions in Multivariate Data using Network Psychometrics
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.
Author: Hudson Golino [aut, cre] (), Alexander Christensen [aut] (), Robert Moulder [ctb] (), Luis E. Garrido [ctb] (), Laura Jamison [ctb] (), Dingjing Shi [ctb] ()
Maintainer: Hudson Golino (For contact information, visit our R community directory.)
License type: GPL (>= 3.0) (For information about this license, visit the Open Source Initiative website.)
Package website: The EGAnet package has a dedicated website. You can visit: https://r-ega.net.

Technical details of the EGAnet package

R documentation also provides technical details of a package, including its dependencies, enhancements, and compilation requirements. Learning this information will help you master the EGAnet package.

Version: In R, a version refers to a specific release of a package and can be used to track changes. To find the version number of the EGAnet package in the R console, you can use the packageVersion("EGAnet") function.
Compilation requirements: Some R packages include internal code that must be compiled for them to function correctly. The EGAnet package has compilation requirements.
Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The EGAnet package has the following required dependencies: R (>= 3.5.0).
Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The EGAnet package has the following suggested dependencies: fitdistrplus, fungible, gridExtra, knitr, markdown, pbapply, progress, psych, pwr, RColorBrewer.
External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The EGAnet package does not use any external sources.
Imported packages: Importing packages allows developers to leverage existing code and functionalities without having to reinvent the wheel. The EGAnet package has the following imported packages: dendextend, future, future.apply, glasso, GGally, ggplot2, ggpubr, GPArotation, igraph (>= 1.3.0), lavaan, Matrix, methods, network, progressr, qgraph, semPlot, sna, stats.
Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The EGAnet package has no enhancements.

Capabilities of the EGAnet package

R documentation provides comprehensive information about a package, including its functions, datasets, and vignettes. Exploring this information will help you make the most of the EGAnet package’s functionalities.

Functions: Functions play a crucial role in R packages. They allow you to perform specific tasks and computations efficiently. To identify the functions in the EGAnet package, you can use the ls("package:EGAnet") function.
Datasets: Many R packages include built-in datasets that you can use to familiarize yourself with their functionalities. To identify any built-in datasets in the EGAnet package, you can use the data(package = "EGAnet") function.
Vignettes: R vignettes are documents that include examples for using a package. To view the list of available vignettes you can use the vignette(package = "EGAnet") function. This code will display a list of available vignettes you can read.
Citation information: Citing R packages in your publications is important as it recognizes the contributions of the developers. To find the citation information for the EGAnet package in the R console, you can use the citation("EGAnet") function.

Getting help with the EGAnet package

If you have trouble using the EGAnet package in R, there are several ways to get help.

The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("EGAnet") function to retrieve detailed information, examples, and usage instructions.
The ? operator: The ? operator is a shortcut for the help() function. You can simply type ?EGAnet to quickly find documentation.
Discussion forums: Online forums are excellent platforms to ask questions, share knowledge, and troubleshoot issues. The most popular forums for R programmers are StackOverflow and Posit Community.

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Code snippet for getting EGAnet package documentation in R

Use R Basics’ code generator tool to effortlessly access essential documentation for the EGAnet package within your R environment.

### Install the {Package} package if not already installed.
if (!require("{Package}")) {
install.packages("{Package}")
}
### Load the {Package} package.
library("{Package}")

### Find details of the {Package} package.
packageDescription("{Package}")

### Explore the capabilities of the {Package} package.

# List of functions
ls("package:{Package}")

# List of datasets
data(package = "{Package}")

# List of vignettes
vignette(package = "{Package}")

# Citation information
citation("{Package}")

### Get help with the {Package} package.
help(package = "{Package}")

Additional R package documentation resources

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