%0 Journal Article
%A Ross, Cody
%A McElreath, Richard
%A Redhead, Daniel
%+ Department of Human Behavior Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Max Planck Society
Department of Human Behavior Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Max Planck Society
Department of Human Behavior Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Max Planck Society
%T Modelling animal network data in R using STRAND : 
%G eng
%U https://hdl.handle.net/21.11116/0000-000C-B018-2
%R 10.1111/1365-2656.14021
%7 2023-11-07
%D 2024
%* Review method: peer-reviewed
%X 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—for example, field researchers—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.<br>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.<br>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.<br>STRAND facilitates the application of generative network models to a broad range of data found in the animal social networks literature.
%K animal networks, generative models, R software, social networks, social relations
%J Journal of Animal Ecology
%V 93
%N 3
%& 254
%P 254 - 266
%I Wiley-Blackwell
%@ 00218790
%U https://www.biorxiv.org/content/10.1101/2022.05.13.491798v1