tna (version 1.0.0)

permutation_test.group_tna: Compare Networks using a Permutation Test

Description

Test edge weight differences between all pairs or a subset of pairs of a group_tna object. See permutation_test.tna() for more details.

Usage

# S3 method for group_tna
permutation_test(
  x,
  groups,
  adjust = "none",
  iter = 1000,
  paired = FALSE,
  level = 0.05,
  measures = character(0),
  ...
)

Arguments

x

A group_tna object

groups

An integer vector or a character vector of group indices or names, respectively, defining which groups to compare. When not provided, all pairs are compared (the default).

adjust

A character string for the method to adjust p-values with for multiple comparisons. The default is "none" for no adjustment. See stats::p.adjust() for details and available adjustment methods.

iter

An integer giving the number of permutations to perform. The default is 1000.

paired

A logical value. If TRUE, perform paired permutation tests; if FALSE, perform unpaired tests. The default is FALSE.

level

A numeric value giving the significance level for the permutation tests. The default is 0.05.

measures

A character vector of centrality measures to test. See centralities() for a list of available centrality measures.

...

Additional arguments passed to centralities().

See Also

Validation functions bootstrap(), deprune(), estimate_cs(), permutation_test(), plot.group_tna_bootstrap(), plot.group_tna_permutation(), plot.group_tna_stability(), plot.tna_bootstrap(), plot.tna_permutation(), plot.tna_stability(), print.group_tna_bootstrap(), print.group_tna_permutation(), print.group_tna_stability(), print.summary.group_tna_bootstrap(), print.summary.tna_bootstrap(), print.tna_bootstrap(), print.tna_permutation(), print.tna_stability(), prune(), pruning_details(), reprune(), summary.group_tna_bootstrap(), summary.tna_bootstrap()

Examples

model <- group_model(engagement_mmm)
# Small number of iterations for CRAN
permutation_test(model, iter = 20)