socialSim - Simulate and Analyse Social Interaction Data

Provides tools to simulate and analyse datasets of social interactions between individuals using hierarchical Bayesian models implemented in Stan. Model fitting is performed via the 'rstan' package. Users can generate realistic interaction data where individual phenotypes influence and respond to those of their partners, with control over sampling design parameters such as the number of individuals, partners, and repeated dyads. The simulation framework allows flexible control over variation and correlation in mean trait values, social responsiveness, and social impact, making it suitable for research on interacting phenotypes and on direct and indirect genetic effects ('DGEs' and 'IGEs'). The package also includes functions to fit and compare alternative models of social effects, including impact–responsiveness, variance–partitioning, and trait-based models, and to summarise model performance in terms of bias and dispersion. For a more detailed description of the available models and impact–responsiveness, see the accompanying article Wijnhorst et al. (2026) <doi:10.1093/jeb/voag013>.