Methodology & Meta-science

Variance Constraints for Hierarchical Signal Detection Models

Bayesian models typically place uninformative or weakly informative priors on parameters. Using a well-known data set on inductive and deductive reasoning, it is illustrated how incorporating variance constraints can help to estimate critical parameters and compare signal detection models with equal and unequal variance.