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. 2019 Jun 13;15(6):e1006989. doi: 10.1371/journal.pcbi.1006989

Fig 2. Model comparison.

Fig 2

(A) Model comparison treating model attribution as a fixed effect showed that the VSE model outperformed all other models, independently of the penalization for complexity implemented by the different estimators (BIC, AIC or Free Energy). The least difference, observed with the VPP model using Free Energy, still reflected decisive evidence in favor of the VSE model (Bayes Factor > 100)[19]. (B) Bayesian model comparison treating model attribution as a random effect also showed that the VSE model outperformed all other models on the 3 estimators (exceedance probability superior to >0.99 in every case). (C) The VSE model was also the best model for predicting single decision, both for fitted and simulated choice data. For fitted choice data, accuracy refers to choice probabilities as produced by the best-fitting parameters. For simulated choice data, accuracy refers to choice probabilities as produced by the best-fitting parameters based on simulated data (in both cases, accuracy equals 1 if the actual choice corresponds to the highest probability under the model, 0 otherwise).