netjack (version 1.2.0)

group_perc_diff_test: Group percentage difference test

Description

This function implements the group percentage difference test on a network statistic. This test assesses if the percent change in the network statistic due to the network manipulation is significantly different between groups. Percent change is calculated as the difference between the target and original statistic divided by the original statistic.

Usage

group_perc_diff_test(netSampleStatSet, grouping.variable,
  p.adjust = "BH", non.parametric = F)

Arguments

netSampleStatSet

Input NetSampleStatSet

grouping.variable

character name of sample level grouping variable

p.adjust

character string for requested multiple comparisons adjustment. Defaults to Benjamani-Hochberg

non.parametric

Logical. if true, test is performed using Wilcox test. If false, t-test. Defaults to false.

Value

A data frame containing original and adjusted p.values.

Details

If the sample has 2 groups, this test is performed using a t-test or Wilcox test. If the sample has 3 or more groups, the test is performed using a 1-way ANOVA, or Kruskal-Wallis test. Differences are tested at each network manipulation.

Examples

# NOT RUN {
data(GroupA)
GroupA_Net = as_NetSample(GroupA, 1:20, node.variables = list(community = c(rep(1, 10), rep(2,10))),
  sample.variables = list(group = c(rep(1, 10), rep(2,10))))
Jackknife_GroupA_Net = net_apply(GroupA_Net, node_jackknife)
GlobEff_GroupA_Net = net_stat_apply(Jackknife_GroupA_Net, global_efficiency)
group_diff_test(GlobEff_GroupA_Net, grouping.variable = "group")
# }