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Cited by 1,123

The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.

The simplest complete model of choice response time: Linear ballistic accumulation

Open access
Brown, Scott D., Heathcote, Andrew·2008·Cognitive Psychology
DOI 10.1016/j.cogpsych.2007.12.002
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Abstract

We propose a linear ballistic accumulator (LBA) model of decision making and reaction time. The LBA is simpler than other models of choice response time, with independent accumulators that race towards a common response threshold. Activity in the accumulators increases in a linear and deterministic manner. The simplicity of the model allows complete analytic solutions for choices between any number of alternatives. These solutions (and freely-available computer code) make the model easy to apply to both binary and multiple choice situations. Using data from five previously published experiments, we demonstrate that the LBA model successfully accommodates empirical phenomena from binary and multiple choice tasks that have proven difficult for other theoretical accounts. Our results are encouraging in a field beset by the tradeoff between complexity and completeness.

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Metadata

Authors
Brown, S. D., & Heathcote, A.
Venue
Cognitive Psychology
Publisher
Elsevier BV
Published
2008-11
Volume
57
Issue
3
Pages
153-178
ISSN
0010-0285 (ISSN-L)
DOI
10.1016/j.cogpsych.2007.12.002
OpenAlex
W2059511681
Cited by
1,123
References
60
FWCI
11.53
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The simplest complete model of choice response time: Linear ballistic accumulation. https://app.cochat.ai/papers/10.1016/j.cogpsych.2007.12.002
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Brown, S. D., & Heathcote, A. (2008). The simplest complete model of choice response time: Linear ballistic accumulation. Cognitive Psychology. https://doi.org/10.1016/j.cogpsych.2007.12.002

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.