Online Program

Visualizing Dichotomous Data Correlations Using Two-Sample Corrgrams (304165)

Keywords: Data Visualization, Exploratory Data Analysis, Graphical Displays

Corrgrams enable visualization of multivariate correlation matrices for a data set by using heatmaps. When a data set includes two groups of interest that are to be compared, use of traditional one-sample corrgrams necessitates the use of two corrgrams in order to display the correlation matrices of both groups. This paper introduces the R package ‘corrarray,’ which streamlines the generation of novel two-sample correlation matrices as an alternative for visualizing a data set stratified into dichotomous groups. The lower and upper triangular correlation matrix of the first and second sample, respectively, are displayed on opposite sides of the principal diagonal in a single correlation matrix. When a data set’s grouping variable has more than two levels, this package provides functionality to visualize a multi-sample array comprising individual correlation matrices for k levels of the grouping variable. Visualizing correlation matrices of a dichotomous data set using a single corrgram reduces the redundancy and white space that would have otherwise resulted from resorting to two one-sample corrgrams.