CentralityAndClusteringPlots function

Plots for node centrality values or clustering coefficients

Mimics the qgraph::centralityPlot and qgraph::clusteringPlot functions. The purpose of revising this function was to make it compatible with outputs from the modnets package.

centPlot(
  Wmats,
  scale = c("z-scores", "raw", "raw0", "relative"),
  which.net = "temporal",
  include = "all",
  labels = NULL,
  orderBy = NULL,
  decreasing = FALSE,
  plot = TRUE,
  verbose = TRUE,
  weighted = TRUE,
  signed = TRUE
)

clustPlot(
  Wmats,
  scale = c("z-scores", "raw", "raw0", "relative"),
  include = "all",
  labels = NULL,
  orderBy = NULL,
  decreasing = FALSE,
  plot = TRUE,
  signed = TRUE,
  verbose = TRUE
)

plotCentrality(
  Wmats,
  which.net = "temporal",
  scale = TRUE,
  labels = NULL,
  plot = TRUE,
  centrality = "all",
  clustering = "Zhang"
)

Arguments

• Wmats: Output from one of the primary modnets functions.
• scale: If "z-scores", then standardized values will be plotted. If "relative", then values will be scaled relative to the largest value on each measure. "raw" can be used to plot raw values.
• which.net: Only applies to SUR networks, as well as those fit with the mlGVAR function. Character string to indicate which type of network to compute centrality values for. Options are "temporal" for the temporal network, "contemporaneous" for the contemporaneous network, "PDC" for the partial directed correlation network, and "interactions" for the temporal interaction network.
• include: Character vector of which centrality measures to plot. "Betweenness" and "Closeness" are available for all types of network. "Strength" and "ExpectedInfluence" are only available for GGMs. And "InStrength", "OutStrength", "InExpectedInfluence","OutExpectedInfluence" are only available for SUR networks. Defaults to "all"
• labels: Character vector listing the node names. If NULL, then the names specified by the model are used.
• orderBy: Character string specifying which measure to order values by.
• decreasing: Logical. Only relevant if orderBy is specified. Determines whether values are organized from highest to lowest, or vice versa.
• plot: Logical. Determines whether to plot the output or not.
• verbose: Logical. Determines whether to return a message about the plot (messages are only shown if values are scaled).
• weighted: See centTable or clustTable.
• signed: See centTable or clustTable.
• centrality: Character vector of centrality measures to plot. Defaults to "all".
• clustering: Character vector of clustering measures to plot. Defaults to "Zhang".

Returns

A plot of centrality values or clustering coefficients for several measures.

Details

The only utility of the plotCentrality function is as an easy way to combine centrality measures and clustering coefficients into a single plot.

Examples

x <- fitNetwork(ggmDat)

centPlot(x)
clustPlot(x)
plotCentrality(x)

See Also

centTable, clustTable, centAuto, clustAuto, qgraph::centralityPlot,qgraph::clusteringPlot