Description Usage Arguments Value Examples

This function tests for significant differences from the original network statistic as a result of the network manipulation. If non-parametric is chosen, this is done using the Wilcox test, otherwise, t-test.

1 |

`netSampleStatSet` |
Input |

`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. |

A data frame containing original and adjusted p.values, as well as differences, labeled with manipulation name.

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)
diff_test(GlobEff_GroupA_Net)
``` |

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