Bayesian hierarchical cognitive modeling with the EMC2 package

EMC2 is an R package that provides a comprehensive five-phase workflow for Bayesian hierarchical analysis of cognitive models of choice. In the design phase, EMC2 bridges the gap between standard regression analyses and cognitive modeling through linear-model specifications for cognitive-model parameters. In the Bayesian specification and sampling phases, the package provides flexible priors, hierarchical structures, and efficient sampling algorithms, enabling fast, user-friendly estimation of computationally intensive cognitive models. In the final two phases, EMC2 provides a suite of functions for model criticism and inference. Using two leading evidence-accumulation models for illustration, we provide a tutorial on the EMC2-based workflow that eases and guides the process of specifying, evaluating, refining, comparing, and interpreting Bayesian hierarchical cognitive models.