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The area under the curve (AUC) for each ROC was computed for each centrality metric and compared in all subjects using multiple pairwise t-tests with Bonferoni correction to test for differences between the centrality metrics.
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This difference between the Centrality and Variability condition was statistically significant (Χ 2 (1, N = 100) = 4.59, p = 0.032).
We used Fisher's Exact Test (Fisher 1970) to measure the significance level of the differences in performances between the centrality methods and the baseline method.
However, the plots also indicate the enormous sensitivity of the degree centrality to the threshold level, as significant differences in the centrality values are observed between different thresholds.
To investigate the differences between graph centrality based gene signatures and that reported in previous literature, topological size of sub-network consisted by the genes in these gene signatures are calculated and presented in this table.
But this measure does not account for differences in the centrality of one's friends.
In general, there was a weak difference in the centrality scores between the genes of selection and nonselection.
This further suggests that participants did not base vaccination decisions on their centrality and that differences between the vaccinated and non-vaccinated correlations in Table 1 are not due to a selection bias of high or low centrality participants opting for or against vaccination.
Table 5 shows correlation between the centrality metrics averaged across diseases and processes.
The differences between the groups were remarkable.
Describe the differences between the two.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com