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Linear deterministic accumulator models of simple choice

Citation

Heathcote, A and Love, J, Linear deterministic accumulator models of simple choice, Frontiers in psychology, 23, (3) pp. 292. ISSN 1664-1078 (2012) [Refereed Article]


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Copyright Statement

Copyright: 2012 Heathcote and Love.

DOI: doi:10.3389/fpsyg.2012.00292

Abstract

We examine theories of simple choice as a race among evidence accumulation processes. We focus on the class of deterministic race models, which assume that the effects of fluctuations in the parameters of the accumulation processes between-choice trials (between-choice noise) dominate the effects of fluctuations occurring while making a choice (within-choice noise) in behavioral data (i.e., response times and choices). The latter deterministic approximation, when combined with the assumption that accumulation is linear, leads to a class of models that can be readily applied to simple-choice behavior because they are computationally tractable. We develop a new and mathematically simple exemplar within the class of linear deterministic models, the Lognormal race (LNR). We then examine how the LNR, and another widely applied linear deterministic model, Brown and Heathcote's (2008) LBA, account for a range of benchmark simple-choice effects in lexical-decision task data reported by Wagenmakers et al. (2008). Our results indicate that the LNR provides an accurate description of this data. Although the LBA model provides a slightly better account, both models support similar psychological conclusions.

Item Details

Item Type:Refereed Article
Research Division:Psychology and Cognitive Sciences
Research Group:Cognitive Sciences
Research Field:Decision Making
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Psychology and Cognitive Sciences
Author:Heathcote, A (Professor Andrew Heathcote)
ID Code:98921
Year Published:2012
Web of Science® Times Cited:23
Deposited By:Medicine (Discipline)
Deposited On:2015-03-06
Last Modified:2017-10-31
Downloads:212 View Download Statistics

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