Robust Modeling in Cognitive Science

Michael D. Lee, Amy H. Criss, Berna Devezer, Christopher Donkin, Alexander Etz, Fábio P. Leite, Dora Matzke, Jeffrey N. Rouder, Jennifer S. Trueblood, Corey N. White, Joachim Vandekerckhove

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

In an attempt to increase the reliability of empirical findings, psychological scientists have recently proposed a number of changes in the practice of experimental psychology. Most current reform efforts have focused on the analysis of data and the reporting of findings for empirical studies. However, a large contingent of psychologists build models that explain psychological processes and test psychological theories using formal psychological models. Some, but not all, recommendations borne out of the broader reform movement bear upon the practice of behavioral or cognitive modeling. In this article, we consider which aspects of the current reform movement are relevant to psychological modelers, and we propose a number of techniques and practices aimed at making psychological modeling more transparent, trusted, and robust.

Original languageEnglish (US)
Pages (from-to)141-153
Number of pages13
JournalComputational Brain and Behavior
Volume2
Issue number3-4
DOIs
StatePublished - Dec 2019

Keywords

  • Cognitive Modeling
  • Open Science
  • Reproducibility
  • Robustness

ASJC Scopus subject areas

  • Developmental and Educational Psychology
  • Neuropsychology and Physiological Psychology

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