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Bayesian hierarchical cognitive modeling with the EMC2 package.

Niek Stevenson1, Michelle C Donzallaz2, Reilly J Innes2

  • 1Department of Psychology, University of Amsterdam, Amsterdam, Netherlands. niek.stevenson@gmail.com.

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Summary
This summary is machine-generated.

This study introduces EMC2, an R package for Bayesian hierarchical analysis of cognitive choice models. It streamlines model specification, estimation, criticism, and inference, enhancing cognitive modeling workflows.

Keywords:
Cognitive modelsEvidence accumulation modelsHierarchical BayesR package

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Area of Science:

  • Cognitive Science
  • Computational Neuroscience
  • Bayesian Statistics

Background:

  • Cognitive models of choice are crucial for understanding decision-making.
  • Bayesian hierarchical analysis offers a powerful framework for these models.
  • Existing workflows can be complex and computationally intensive.

Purpose of the Study:

  • To introduce EMC2, a novel R package for Bayesian hierarchical analysis of cognitive models.
  • To provide a comprehensive five-phase workflow simplifying cognitive model analysis.
  • To facilitate the specification, estimation, criticism, and inference of complex cognitive models.

Main Methods:

  • Development of the EMC2 R package with a five-phase workflow.
  • Integration of linear-model specifications for cognitive model parameters.
  • Implementation of flexible priors, hierarchical structures, and efficient sampling algorithms.
  • Inclusion of functions for model criticism and inference.

Main Results:

  • EMC2 offers a user-friendly interface for computationally intensive cognitive models.
  • The package bridges standard regression and cognitive modeling.
  • Demonstrated workflow using two evidence-accumulation models.

Conclusions:

  • EMC2 significantly eases and guides the analysis of Bayesian hierarchical cognitive models.
  • The package supports model evaluation, refinement, comparison, and interpretation.
  • EMC2 enhances the accessibility and efficiency of advanced cognitive modeling techniques.