Description Usage Arguments Details Value Examples

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.

1 2 | ```
group_diff_test(netSampleStatSet, grouping.variable, p.adjust = "BH",
non.parametric = F)
``` |

`netSampleStatSet` |
Input |

`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. |

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.

A data frame containing original and adjusted p.values.

1 2 3 4 5 6 | ```
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")
``` |

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