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
preprint Wijnhorst et al. (2025) <doi:10.32942/X2F65M>.
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