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Calculate Summary of Network Metrics for a grouped Transition Network

Source: R/summary.R
summary.group_tna.Rd

This function calculates a variety of network metrics for a tna object. It computes key metrics such as node and edge counts, network density, mean distance, strength measures, degree centrality, and reciprocity.

Usage

# S3 method for class 'group_tna'
summary(object, combined = TRUE, ...)

Arguments

object

A group_tna object.

combined

A logical indicating whether the summary results should be combined into a single data frame for all clusters (defaults to TRUE)

...

Ignored

Value

A summary.group_tna object which is a list of lists or a combined data.frame containing the following network metrics:

  • node_count: The total number of nodes.

  • edge_count: The total number of edges.

  • network_Density: The density of the network.

  • mean_distance: The mean shortest path length.

  • mean_out_strength: The mean out-strength of nodes.

  • sd_out_strength: The standard deviation of out-strength.

  • mean_in_strength: The mean in-strength of nodes.

  • sd_in_strength: The standard deviation of in-strength.

  • mean_out_degree: The mean out-degree of nodes.

  • sd_out_degree: The standard deviation of out-degree.

  • centralization_out_degree: The centralization of out-degree.

  • centralization_in_degree: The centralization of in-degree.

  • reciprocity: The reciprocity of the network.

Details

The function extracts the igraph network for each cluster and computes the following network metrics:

  • Node count: Total number of nodes in the network.

  • Edge count: Total number of edges in the network.

  • Network density: Proportion of possible edges that are present in the network.

  • Mean distance: The average shortest path length between nodes.

  • Mean and standard deviation of out-strength and in-strength: Measures of the total weight of outgoing and incoming edges for each node.

  • Mean and standard deviation of out-degree: The number of outgoing edges from each node.

  • Centralization of out-degree and in-degree: Measures of how centralized the network is based on the degrees of nodes.

  • Reciprocity: The proportion of edges that are reciprocated (i.e., mutual edges between nodes).

See also

Basic functions build_model(), hist.group_tna(), hist.tna(), plot.group_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.tna(), tna-package

Examples

group <- c(rep("High", 1000), rep("Low", 1000))
model <- group_model(group_regulation, group = group)
summary(model)
#> # A tibble: 13 × 3
#>    metric                          High      Low
#>  * <chr>                          <dbl>    <dbl>
#>  1 Node Count                  9   e+ 0 9   e+ 0
#>  2 Edge Count                  7.6 e+ 1 7.5 e+ 1
#>  3 Network Density             1   e+ 0 1   e+ 0
#>  4 Mean Distance               4.23e- 2 5.60e- 2
#>  5 Mean Out-Strength           1   e+ 0 1   e+ 0
#>  6 SD Out-Strength             9.14e- 1 7.19e- 1
#>  7 Mean In-Strength            1   e+ 0 1   e+ 0
#>  8 SD In-Strength              7.85e-17 3.93e-17
#>  9 Mean Out-Degree             8.44e+ 0 8.33e+ 0
#> 10 SD Out-Degree               1.13e+ 0 8.66e- 1
#> 11 Centralization (Out-Degree) 4.69e- 2 6.25e- 2
#> 12 Centralization (In-Degree)  4.69e- 2 6.25e- 2
#> 13 Reciprocity                 9.57e- 1 9.41e- 1