VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data

doi:10.1371/journal.pcbi.1003441

VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data

Figure 12

Random-effect group-BMS.

This figure exemplifies a random-effect group-BMS analysis, which is used to infer on the best model at the group level. The analysis is conducted on two groups of 32 subjects, whose data were simulated under either a ‘full’ (, group 1) or a ‘reduced’ (, group 2) model. Upper left: simulated data (y-axis) plotted against fitted data (x-axis), for a typical simulation. Lower left: histograms of log Bayes factor , for both groups (red: group 1, blue: group 2). Upper middle: model attributions, for group 1. The posterior probability for each subject is coded on a black-and-white colour scale (black = 1, white = 0). Lower middle: same format, group 2. Upper right: exceedance probabilities, for group 1. The red line indicates the usual 95% threshold. Lower right: same format, group 2.

doi: https://doi.org/10.1371/journal.pcbi.1003441.g012