Permutation tests for hypothesis testing with animal social network data: Problems and potential solutions.

ABSTRACT: Permutation tests are widely used to test null hypotheses with animal social network data, but suffer from high rates of type I and II error when the permutations do not properly simulate the intended null hypothesis.Two common types of permutations each have limitations. Pre-network (or datastream) permutations can be used to control 'nuisance effects' like spatial, temporal or sampling biases, but only when the null hypothesis assumes random social structure. Node (or node-label) permutation tests can test null hypotheses that include nonrandom social structure, but only when nuisance effects do not shape the observed network.We demonstrate one possible solution addressing these limitations: using pre-network permutations to adjust the values for each node or edge before conducting a nod

SUBMITTER: Farine DR 

PROVIDER: S-EPMC9297917 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature