CentralityAndClustering {modnets} | R Documentation |
Create table of centrality values or clustering coefficients
Description
Mimics the output of the
qgraph::centralityTable
and
qgraph::clusteringTable
functions. The
purpose of revising these function was to make them compatible with outputs
from the modnets
package.
Usage
centTable(
Wmats,
scale = TRUE,
which.net = "temporal",
labels = NULL,
relative = FALSE,
weighted = TRUE,
signed = TRUE
)
clustTable(Wmats, scale = TRUE, labels = NULL, relative = FALSE, signed = TRUE)
Arguments
Wmats |
Output from one of the primary |
scale |
Logical. Determines whether to standardize values within each measure (i.e., convert to z-scores). |
which.net |
Only applies to SUR networks, as well as those fit with the
|
labels |
Character vector to input the names of the nodes. If left
|
relative |
Logical. Determines whether to scale values within each measure relative to the largest value within that measure. |
weighted |
Logical. If |
signed |
Logical. Determines whether to ignore the signs of edges or not. Primarily affects the output for expected influence statistics. |
Details
For centTable
, centrality values can be computed for the matrix
of interactions within a temporal network.
Value
A table containing the names of nodes, measures of node centrality, and their corresponding centrality values or clustering coefficients.
See Also
centAuto, clustAuto, centPlot,
clustPlot, plotCentrality,
qgraph::centralityTable,
qgraph::clusteringTable
Examples
x <- fitNetwork(gvarDat, 'M', lags = TRUE)
clustTable(x)
centTable(x, which.net = 'interactions')