Bayesian multiplex network models in R using STRAND: methods for biologists and social scientists

The social networks of interest to biologists, ecologists and social scientists are often multi-layered, with the same set of individuals interacting with one another in complex, multifaceted ways. Each type of interaction can be represented as one layer in a larger multiplex network. Important research questions often hinge on how ties or flows in one network layer impact ties or flows in another layer. Similar questions focus on the relationship between nodal characteristics across layers: for example, is an individual with a high out-degree in one layer more likely to have a high in-degree in another layer? These questions are effectively addressed by multiplex extensions of generative social network models, like the social relations model (SRM). Here, we present a multiplex implementation of the SRM in the STRAND R package and provide tutorials teaching end-users how to run the model on their own data. We provide worked examples of data analysis, parameter visualization and results interpretation, using datasets from experimental economics and animal behaviour. Our software package allows end-users to deploy powerful multiplex models, using only simple base-R model syntax, permitting wider use of generative network modelling approaches across disciplines.