Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies
Fig 7
The sensitivity of parameter estimation to outliers.
30 subjects are simulated using the RL model. A) In scenario 1, a number of outliers are also simulated with the same learning rate but small decision noise parameter. B) In scenario 2, outliers are simulated with small learning rate and small decision noise parameter. Errors in recovering the group-level parameters are plotted (for the learning rate, and decision noise,). HBI performs better than alternatives. The estimation error is defined as the absolute difference between estimated group-level parameters and the true parameters. In all plots, error-bars are standard errors of the mean obtained across simulations 20 times.