title: Hypothesis testing in animal social networks.
abstract: Behavioural ecologists are increasingly using social network analysis to describe the social organisation of animal populations and to test hypotheses. However, the statistical analysis of network data presents a number of challenges. In particular the non-independent nature of the data violates the assumptions of many common statistical approaches. In our opinion there is currently confusion and uncertainty amongst behavioural ecologists concerning the potential pitfalls when hypotheses testing using social network data. Here we review what we consider to be key considerations associated with the analysis of animal social networks and provide a practical guide to the use of null models based on randomisation to control for structure and non-independence in the data.
authors.affiliation: Centre for Research in Animal Behaviour, College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4QG, UK. d.p.croft@exeter.ac.uk
authors.forename: Darren P
authors.initials: DP
authors.lastname: Croft
authors.forename: Joah R
authors.initials: JR
authors.lastname: Madden
authors.forename: Daniel W
authors.initials: DW
authors.lastname: Franks
authors.forename: Richard
authors.initials: R
authors.lastname: James
mesh_terms: D000818:Animals; D001522:Behavior, Animal; D003627:Data Interpretation, Statistical; D004463:Ecology; D012107:Research Design; D012919:Social Behavior; D035503:Sociobiology