qgraph_centrality_panel: Create a combined panel with qgraph network and centrality...

In InterconectaR: Psychological Network Analysis and Psychometric Insights

Create a combined panel with qgraph network and centrality plot

Description

Create a combined panel with qgraph network and centrality plot

Usage

qgraph_centrality_panel(
  Figura1_Derecha,
  network,
  groups,
  error_Model,
  labels = NULL,
  abbreviate_labels = FALSE,
  ncol = 2,
  widths = c(0.5, 0.6),
  dpi = 600,
  legend.cex = 0.1,
  legend_title = "Métrica",
  keep_centrality_scale = TRUE,
  layoutScale = c(0.9, 0.9),
  GLratio = 2,
  vsize = 18,
  esize = 18,
  node.width = 0.8,
  curveAll = 2,
  palette = "pastel",
  layout = "spring",
  edge.labels = TRUE,
  edge.label.cex = 1
)

Arguments

Figura1_Derecha	A ggplot object for the right panel (centrality plot).
network	A network object with elements graph and labels.
groups	Named list mapping factor names to node indices.
error_Model	Pie values for error model visualization.
labels	Optional character vector of node labels.
abbreviate_labels	Logical; abbreviate labels to 3 characters.
ncol	Number of columns in the layout.
widths	Relative widths of the panels.
dpi	Resolution in DPI for the qgraph rendering.
legend.cex	Legend text size for qgraph.
legend_title	Title for the legend.
keep_centrality_scale	Logical; keep original scale of centrality plot.
layoutScale	Numeric vector of length 2 for layout scaling.
GLratio	Graph-to-legend ratio.
vsize	Node size.
esize	Edge size.
node.width	Node width.
curveAll	Edge curvature.
palette	Color palette name.
layout	Layout algorithm.
edge.labels	Logical; show edge labels.
edge.label.cex	Edge label text size.

Value

A combined patchwork plot object.

Examples

set.seed(123)
n <- 300
f1 <- rnorm(n)
f2 <- 0.3 * f1 + rnorm(n)
items <- data.frame(
  sapply(1:4, function(i) 0.7 * f1 + rnorm(n, 0, 0.7)),
  sapply(1:4, function(i) 0.7 * f2 + rnorm(n, 0, 0.7))
)
names(items) <- c(paste0("A", 1:4), paste0("B", 1:4))

net <- bootnet::estimateNetwork(items, default = "EBICglasso")
g <- qgraph::qgraph(net$graph, DoNotPlot = TRUE)
cent <- centrality_plots2(g, net,
                          groups = rep(c("A", "B"), each = 4),
                          measure1 = "Bridge Expected Influence (1-step)")
r2 <- mgm_error_metrics(items, type = rep("g", 8), level = rep(1, 8))$R2
qgraph_centrality_panel(cent$plot, net, groups = list(A = 1:4, B = 5:8),
                        error_Model = r2, dpi = 100)

InterconectaR documentation built on Oct. 16, 2026, 1:06 a.m.