centrality and clustering plots: Centrality and Clustering plots and tables

Description

These functions can be used to facilitate interpreting centrality and clustering coefficients. The plot functions use ggplot2 (Wickham, 2009). The table functions create a long format table which can easilly be plotted in ggplot2.

Usage

centralityPlot(..., labels, standardized = TRUE, relative = FALSE, include, 
                theme_bw = TRUE, print = TRUE)
clusteringPlot(..., labels,  standardized = TRUE, relative = FALSE,  include, 
                signed = FALSE, theme_bw = TRUE, print = TRUE)
centralityTable(..., labels, standardized = TRUE,  relative = FALSE)
clusteringTable(..., labels,  standardized = TRUE, relative = FALSE, 
                signed = FALSE)

Arguments

...

Objects usuable in the getWmat generic, such as qgraph objects and weights matrices. Can also be lists containing these objects. Graphs in a list will be plotted in the same panel as different lines and gra

labels

A vector overwriting the labels used

standardized

Logical, should all measures be standardized?

relative

Logical, should all measures be scaled relative to the largest value?

include

A vector of measures to include. if missing all measures available will be included.

signed

Logical indicating if signed clustering coefficients should be plotted.

theme_bw

Adds the ggplot2 black and white theme to the plot

If TRUE, the plot is sent to the print command and returned invisible, if FALSE the plot is returned normally. Needed to include plots in e.g., pdf files.

References

H. Wickham. ggplot2: elegant graphics for data analysis. Springer New York, 2009.