EMC2; An R Package for cognitive models of choice

Abstract

We introduce EMC2, an R package for the Bayesian hierarchical analysis of cognitive models of choice. EMC2 bridges the gap between standard regression analyses and cognitive modeling through linear-model specifica- tions for each type of cognitive-model parameter. The flexible implemen- tation of the linear modelling language allows users to map model parame- ters directly to complicated designs and hypotheses. EMC2 implements recent developments in Bayesian parameter estimation and hypothesis testing, including powerful and efficient sampling and marginal likelihood estimation algorithms, so it is computationally feasible to estimate many different cognitive models, and perform inference among them. Using two leading evidence-accumulation models, we illustrate how EMC2 provides a workflow that makes it easy to specify diverse parameterisations and in- formative priors, and to evaluate, refine, compare, and interpret models.