Convenience function for converting a qgraph object to a layout determined by principal components analysis
PCAnet(qgraph_net, cormat, varTxt = F, repulse = F, repulsion = 1,
principalArgs = list(), ...)an object of type qgraph
the correlation matrix of the relevant data. If this argument is missing,
the function will assume that the adjacency matrix from qgraph_net is a correlation matrix
logical. Print the variance accounted for by the PCA in the lower left corner of the plot
logical. Add a small repulsion force with wordcloud package to avoid node overlap?
scalar for the repulsion force (if repulse=T). Larger values add more repulsion
additional arguments in list format passed to psych::principal
additional arguments passed to qgraph
A network plotted with PCA can be interpreted based on coordinate placement of each node. A node in the top right corner scored high on both the first and second principal components
Jones, P. J., Mair, P., & McNally, R. J. (2017). Scaling networks for two-dimensional visualization: a tutorial. Retrieved from osf.io/eugsz