Estimate Grouped Networks — estimate_grouped

Estimates networks for different groups within a data frame, using `estimate_single_network` internally. Produces separate network visualizations and metrics for each group.

Usage

estimate_grouped_networks(
  df,
  Vars = NULL,
  GroupVar,
  layout = "circle",
  color = DEFAULT_NODE_COLOR,
  default = "EBICglasso",
  var_types = NULL,
  qgraph_args = list(),
  network_args = list(),
  verbose = TRUE,
  min_group_size = 30
)

Arguments

df: A data frame containing the variables and group variable.
Vars: Character vector of variable names to include in the network. If NULL (default), all columns except GroupVar are used.
GroupVar: Character string specifying the grouping variable name.
layout: Layout algorithm for network plots. Defaults to "circle".
color: Node color(s). Defaults to "#EEEEEE".
default: Network estimation method. Defaults to "EBICglasso".
var_types: Variable types for MGM. If NULL, auto-detected.
qgraph_args: Additional arguments for qgraph.
network_args: Additional arguments for bootnet::estimateNetwork.
verbose: Print progress messages. Defaults to TRUE.
min_group_size: Minimum group size required. Groups with fewer observations are skipped. Defaults to 30.

Value

A list of class "grouped_network_analysis" containing:

networks: List of network objects per group
network_matrices: List of adjacency matrices per group
predictions: List of prediction results per group
centralities: List of centrality measures per group
qgraphs: List of qgraph plot objects per group
group_sizes: Sample sizes per group
failed_groups: Groups that failed estimation

Examples

if (FALSE) { # \dontrun{
# Estimate networks by group
results <- estimate_grouped_networks(
  df = my_data,
  Vars = c("var1", "var2", "var3", "var4"),
  GroupVar = "group"
)

# Access results for specific group
results$networks$GroupA
results$predictions$GroupA

# Compare networks
compare_networks(results, groups = c("GroupA", "GroupB"))
} # }