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Accumulating advantages: a new conceptualization of rapid multiple choice
Citation
van Ravenzwaaij, D and Brown, SD and Marley, AAJ and Heathcote, A, Accumulating advantages: a new conceptualization of rapid multiple choice, Psychological Review, 127, (2) pp. 186-215. ISSN 0033-295X (2020) [Refereed Article]
Copyright Statement
Copyright 2019 American Psychological Association
Abstract
Independent racing evidence-accumulator models have proven fruitful in advancing
understanding of rapid decisions, mainly in the case of binary choice, where they
can be relatively easily estimated and are known to account for a range of benchmark
phenomena. Typically, such models assume a one-to-one mapping between
accumulators and responses. We explore an alternative independent-race framework
where more than one accumulator can be associated with each response, and
where a response is triggered when a sufficient number of accumulators associated
with that response reach their thresholds. Each accumulator is primarily driven by
the difference in evidence supporting one vs. another response (i.e., that response’s
"advantage"), with secondary inputs corresponding to the total evidence for both
responses and a constant term. We use Brown and Heathcote’s (2008) LBA to
instantiate the framework in a mathematically tractable measurement model (i.e.,
a model whose parameters can be successfully recovered from data). We show
this "Advantage LBA" model provides a detailed quantitative account of a variety
of benchmark binary and multiple choice phenomena that traditional independent
accumulator models struggle with; in binary choice the effects of additive versus
multiplicative changes to input values, and in multiple choice the effects of manipulations
of the strength of lure (i.e., non-target) stimuli and Hick’s Law. We conclude
that the Advantage LBA provides a tractable new avenue for understanding the dynamics
of decisions among multiple choices.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | evidence accumulation models, RT tasks, Hick’s Law, lateral inhibition, max-next |
| Research Division: | Psychology |
| Research Group: | Cognitive and computational psychology |
| Research Field: | Decision making |
| Objective Division: | Expanding Knowledge |
| Objective Group: | Expanding knowledge |
| Objective Field: | Expanding knowledge in psychology |
| UTAS Author: | Heathcote, A (Professor Andrew Heathcote) |
| ID Code: | 134799 |
| Year Published: | 2020 |
| Web of Science® Times Cited: | 6 |
| Deposited By: | Psychology |
| Deposited On: | 2019-09-05 |
| Last Modified: | 2021-09-07 |
| Downloads: | 0 |
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