Extended Data Table 2 Summary of model fits

From: Individual differences in autism-like traits are associated with reduced goal emulation in a computational model of observational learning

  1. Each of the five models (non-learning, imitation, emulation, fixed mixture, and dynamic arbitration) was fit to participants’ data with both non-hierarchical and hierarchical Bayesian inference using MATLAB’s cbm toolbox. The number of parameters (Nparameters), the group average Akaike Information Criteria (AIC, non-hierarchical), Bayesian Information Criteria (BIC, non-hierarchical), model frequency (hierarchical), and model exceedance probability (hierarchical) are shown for both studies.
Back to article page