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A Bayesian hierarchical model of trial-to-trial fluctuations in decision criterion

Fig 3

An overview of the estimated posteriors distributions for the group-level (global) parameters when varying the number of subjects per dataset, with 500 trials per subject.

A) The posterior distributions become more narrow as the number of subjects increases. The true parameter values are indicated by the red dashed line. B) Each row shows the overlaid posteriors for all 50 simulated datasets with a varying number of subjects per dataset. The estimated posteriors are corrected and centered on the true value (denoted by an asterisk). For and the true value is defined as the mean or standard deviation of the true per-subject parameters within each dataset. Due to boundaries in the parameter space, with , , , and being strictly positive, the posterior distributions can be skewed. It should be noted that there is a slight underestimation for , , and . This is presumably due to the true being so close to the upper boundary of 1, which causes the posterior distribution of this parameter to be asymmetric and possibly leading to compensatory effects for the other parameter estimates. Overall, we see an excellent recovery of the group-level (global) parameters.

doi: https://doi.org/10.1371/journal.pcbi.1013291.g003