plot_mds: plot_mds

In corx: Create and Format Correlation Matrices

plot_mds

Description

Perform multidimensional scaling of a corx object and plot results

Usage

plot_mds(corx, k = NULL, abs = TRUE, ...)

Arguments

corx	corx object
k	numeric. The number of clusters. If set to "auto" will be equal to the number of principal components that explain more than 5% of total variance.
abs	logical. If TRUE (the default) negative correlations will be turned positive. This means items with high negative correlations will be treated as highly similar.
...	additional arguments passed to ggpubr::ggscatter

Details

plot_mds performs classic multidimensional scaling on a correlation matrix. The correlation matrix is first converted to a distance matrix using psych::cor2dist. This function employs the following formula:

d = \sqrt(2*(1-r))

These distances are then passed to stats::cmdscale where k = 2. To compute latex, distances are predict from the cmdscale output and correlated with input distances. This correlation is squared. If the value of R^2 is less than 70%, a warning will inform users that two-dimensions may not be sufficient to represent item relationships. The position of variables is then plotted with ggplot2. Clusters of items are identified using stats::kmeans. The number of clusters is determined using principal component analysis unless specified.

References

Carlson, D.L., 2017. Quantitative methods in archaeology using R. Cambridge University Press.

corx documentation built on July 9, 2023, 6:32 p.m.