group_diff_test: Group difference test

In trh3/netjack: Tools for Working with Samples of Networks

Description

This function implements the group difference test on a network statistic. This test assesses if the change in the network statistic due to the network manipulation is significantly different between groups.

Usage

group_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.

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.

Value

A data frame containing original and adjusted p.values.

Examples

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")

trh3/netjack documentation built on Aug. 21, 2019, 4:04 a.m.