Journal of Statistical Software· 2012Q1
<b>qgraph</b>: Network Visualizations of Relationships in Psychometric Data
- 4,809citations
- Q1SCImago
- 2012year
Short summary
The qgraph R package offers a novel way to visualize complex statistical relationships, such as correlation matrices, as networks where variables are nodes and correlations are edges.
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Key points
- Visualizes statistical matrices (correlations, covariances, factor loadings) as networks.
- Edge width in the network represents the magnitude of the statistical relationship.
- Integrates with R packages sem and lavaan for automatic visualization of factor analysis outputs.
- Demonstrates application using data from the NEO-PI-R personality questionnaire.
AI-generated from the title and abstract; the full text is not read.
Abstract
We present the qgraph package for R, which provides an interface to visualize data through network modeling techniques. For instance, a correlation matrix can be represented as a network in which each variable is a node and each correlation an edge; by varying the width of the edges according to the magnitude of the correlation, the structure of the correlation matrix can be visualized. A wide variety of matrices that are used in statistics can be represented in this fashion, for example matrices that contain (implied) covariances, factor loadings, regression parameters and p values. qgraph can also be used as a psychometric tool, as it performs exploratory and confirmatory factor analysis, using sem and lavaan; the output of these packages is automatically visualized in qgraph, which may aid the interpretation of results. In this article, we introduce qgraph by applying the package functions to data from the NEO-PI-R, a widely used personality questionnaire.
The authors' abstract, as published at the source. Journal of Statistical Software, 2012 · DOI ↗
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Field: Experimental and Cognitive Psychology
Experimental and Cognitive PsychologyPsychology