% pubman genre = article @article{item_3495666, title = {{Modelling animal network data in R using STRAND}}, author = {Ross, Cody and McElreath, Richard and Redhead, Daniel}, language = {eng}, isbn = {00218790}, doi = {10.1111/1365-2656.14021}, publisher = {Wiley-Blackwell}, year = {2024}, date = {2024-03}, abstract = {{There have been recent calls for wider application of generative modelling approaches in applied social network analysis. At present, however, it remains difficult for typical end users{\textemdash}for example, field researchers{\textemdash}to implement generative network models, as there is a dearth of openly available software packages that make application of such models as simple as other, permutation-based approaches.{\textless}br{\textgreater}Here, we outline the STRAND R package, which provides a suite of generative models for Bayesian analysis of animal social network data that can be implemented using simple, base R syntax.{\textless}br{\textgreater}To facilitate ease of use, we provide a tutorial demonstrating how STRAND can be used to model proportion, count or binary network data using stochastic block models, social relation models or a combination of the two modelling frameworks.{\textless}br{\textgreater}STRAND facilitates the application of generative network models to a broad range of data found in the animal social networks literature.}}, journal = {{Journal of Animal Ecology}}, volume = {93}, number = {3}, pages = {254--266}, }