Plots a transition network of each cluster using qgraph.
# S3 method for group_tna
plot(x, title, which, ...)NULL (invisibly).
A group_model object.
A title for each plot. It can be a single string (the same one will be used for all plots) or a list (one per group)
An optional integer vector of groups to plot. By default, all
groups are plotted.
Arguments passed on to plot.tna
labelsSee qgraph::qgraph().
colorsSee qgraph::qgraph().
pieSee qgraph::qgraph().
cutEdge color and width emphasis cutoff value. The default is
the median of the edge weights. See qgraph::qgraph() for details.
show_prunedA logical value indicating if pruned edges removed by
prune() should be shown in the plot. The default is TRUE, and the
edges are drawn as dashed with a different color to distinguish them.
pruned_edge_colorA character string for the color to use for
pruned edges when show_pruned = TRUE. The default is "pink".
edge.colorSee qgraph::qgraph().
edge.labelsSee qgraph::qgraph().
edge.label.positionSee qgraph::qgraph().
layoutOne of the following:
A character string describing a qgraph layout (e.g., "circle")
or the name of a igraph layout function (e.g., "layout_on_grid").
A matrix of node positions to use, with a row for each node and
x and y columns for the node positions.
A layout function from igraph.
layout_argsA list of arguments to pass to the igraph layout
function when layout is a function or a character string that specifies
a function name.
scale_nodesA character string giving the name of a centrality
measure to scale the node size by. See centralities() for valid names.
If missing (the default), uses default qgraph::qgraph() scaling.
Overrides vsize provided via ....
scaling_factorA numeric value specifying how strongly to scale
the nodes when scale_nodes is provided. Values
between 0 and 1 will result in smaller differences and values larger
than 1 will result in greater differences. The default is 0.5.
marSee qgraph::qgraph().
themeSee qgraph::qgraph().
Basic functions
build_model(),
hist.group_tna(),
hist.tna(),
plot.tna(),
plot_frequencies(),
plot_frequencies.group_tna(),
plot_mosaic(),
plot_mosaic.group_tna(),
plot_mosaic.tna_data(),
print.group_tna(),
print.summary.group_tna(),
print.summary.tna(),
print.tna(),
summary.group_tna(),
summary.tna(),
tna-package
model <- group_model(engagement_mmm)
plot(model, which = 1)
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