Article

An expert guide to planning experimental tasks for evidence accumulation modelling

2024-07-02

Abstract excerpt

<p>Evidence accumulation models (EAMs) are powerful tools for making sense of human and animal decision-making behaviour. EAMs have generated significant theoretical advances in psychology, behavioural economics, and cognitive neuroscience, and are increasingly used as a measurement tool in clinical research and other applied settings. Obtaining valid and reliable inferences from EAMs depends on knowing how to est...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 932cfc8d-96cf-534e-9eb7-0930d8561a6f
DOI: 10.31234/osf.io/snqgp

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

An expert guide to planning experimental tasks for evidence accumulation modellingDOI 10.31234/osf.io/snqgpRead

Emerging Insights into Cognitive Control from Computational Models of ChoiceSemantic proximity Read

DfE-DB: A systematic database of 3.8 million human decisions across experience-based tasksSemantic proximity Read

Guideline for Reporting Standards of Eye-tracking Research in Decision SciencesSemantic proximity Read

A low-dimensional approximation of optimal confidenceSemantic proximity Read

Cohen’s Convention, the Seriousness of Errors, and the Body of Knowledge in Behavioral ScienceSemantic proximity Read

AI-assisted discovery of unknown cognitive biases: Humans systematically undervalue information under complexitySemantic proximity Read

Closed-Loop Scientific Discovery in the Behavioral SciencesSemantic proximity Read

Closed-Loop Scientific Discovery in the Behavioral SciencesSemantic proximity Read

Widely used bandit tasks elicit diverging belief updating phenotypes in healthy adultsSemantic proximity Read

Estimation and validation of a single model parameter governing compensatory and non-compensatory cue use in decision makingSemantic proximity Read

Predicting human prediction error empowers reward learning task designSemantic proximity Read

Disagreement as a signal: an auditable dual-LLM and human-arbitrated workflow for methodological quality assessment in preclinical complex-intervention evidenceSemantic proximity Read