Skip to main content
. 2014 Jan 24;9(1):e86850. doi: 10.1371/journal.pone.0086850

Table 4. Model comparison between a null model (one set of model-based and model-free regressors for both stimulation conditions) and more complex models that allow for an effect of tDCS on model-based control, model-free control, or both, which shows the null model is significantly more plausible than any of the models that allow for an effect of tDCS on behavioral control.

Model No. of regressorsper subject BIC ΔBIC AIC ΔAIC Bayes factor in favor of null model based on AIC
null model 13 18553 0 17752 0
separate model-freeregressors for Active and Sham 16 18962 409 17796 44 1.3×1019
separate model-basedregressors for Active and Sham 16 18947 394 17781 29 3.9×1012
full model 19 19453 900 17852 100 2.7×1043

The second column refers to the number of regressors in the hierarchical regression at the individual subject level (cf. Table 1 and 3).

BIC: Bayesian Information Criterion; AIC: Akaike’s Information Criterion.