A guide to choosing and implementing reference models for social network analysis.

ABSTRACT: Analysing social networks is challenging. Key features of relational data require the use of non-standard statistical methods such as developing system-specific null, or reference, models that randomize one or more components of the observed data. Here we review a variety of randomization procedures that generate reference models for social network analysis. Reference models provide an expectation for hypothesis testing when analysing network data. We outline the key stages in producing an effective reference model and detail four approaches for generating reference distributions: permutation, resampling, sampling from a distribution, and generative models. We highlight when each type of approach would be appropriate and note potential pitfalls for researchers to avoid. Throughout, we illu

SUBMITTER: Hobson EA 

PROVIDER: S-EPMC9292850 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature