Abstract
Comparing networks is challenging. Social networks can be shaped by many factors. Failing to adequately consider non-social processes, including sampling artefacts, can lead to spurious conclusions about differences in social networks among groups. Here we demonstrate that incorrect application of statistical testing methods when comparing networks can generate very high rates of false positives. We then show that null models, specifically pre-network permutation tests, can control for non-social differences in networks and substantially reduce rates of false positives.
Footnotes
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.