{ "_id": "6a1d3cca1d7bb097a0a3f85a", "Package": "socialSim", "Type": "Package", "Title": "Simulate and Analyse Social Interaction Data", "Version": "0.1.9", "Authors@R": "person(\ngiven = \"Rori Efrain\",\nfamily = \"Wijnhorst\",\nemail = \"roriwijnhorst@proton.me\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-8902-592X\")\n)", "Description": "Provides tools to simulate and analyse datasets of social\ninteractions between individuals using hierarchical Bayesian\nmodels implemented in Stan. Model fitting is performed via the\n'rstan' package. Users can generate realistic interaction data\nwhere individual phenotypes influence and respond to those of\ntheir partners, with control over sampling design parameters\nsuch as the number of individuals, partners, and repeated\ndyads. The simulation framework allows flexible control over\nvariation and correlation in mean trait values, social\nresponsiveness, and social impact, making it suitable for\nresearch on interacting phenotypes and on direct and indirect\ngenetic effects ('DGEs' and 'IGEs'). The package also includes\nfunctions to fit and compare alternative models of social\neffects, including impact–responsiveness,\nvariance–partitioning, and trait-based models, and to summarise\nmodel performance in terms of bias and dispersion. For a more\ndetailed description of the available models and\nimpact–responsiveness, see the accompanying article Wijnhorst\net al. 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