combine_graphs_centrality: Combine Network and Centrality Graphs

In InterconectaR: Psychological Network Analysis and Psychometric Insights

Combine Network and Centrality Graphs

Description

Combines a qgraph network plot with a centrality line plot.

Usage

combine_graphs_centrality(
  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,
  layoutScale = c(1, 1),
  vsize = 18,
  threshold = 0
)

Arguments

Figura1_Derecha	ggplot object with centrality plot.
network	Estimated network object.
groups	List of node communities.
error_Model	Prediction error values for pie chart overlay.
labels	Custom node labels.
abbreviate_labels	Logical; abbreviate labels to 3 characters.
ncol	Number of columns in layout.
widths	Relative widths of panels.
dpi	Resolution in dots per inch.
legend.cex	Legend text size multiplier.
layoutScale	Layout scale vector.
vsize	Node size.
threshold	Minimum edge weight threshold.

Value

A patchwork object with the network on the left and the centrality plot on the right.

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
combine_graphs_centrality(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.