Two-stage dynamic signal detection: A theory of choice, decision time, and confidence.
Abstract
The 3 most often-used performance measures in the cognitive and decision sciences are choice, response or decision time, and confidence. We develop a random walk/diffusion theory-2-stage dynamic signal detection (2DSD) theory-that accounts for all 3 measures using a common underlying process. The model uses a drift diffusion process to account for choice and decision time. To estimate confidence, we assume that evidence continues to accumulate after the choice. Judges then interrupt the process to categorize the accumulated evidence into a confidence rating. The model explains all known interrelationships between the 3 indices of performance. Furthermore, the model also accounts for the distributions of each variable in both a perceptual and general knowledge task. The dynamic nature of the model also reveals the moderating effects of time pressure on the accuracy of choice and confidence. Finally, the model specifies the optimal solution for giving the fastest choice and confidence rating for a given level of choice and confidence accuracy. Judges are found to act in a manner consistent with the optimal solution when making confidence judgments.
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Evidence accumulation may continue after a decision has been made, informing estimates of decision confidence and potentially leading to changes of mind.
“Pleskac & Busemeyer (2010) additionally proposed that this evidence accumulation process may continue after a decision has been made, informing estimates of decision confidence and potentially leading to changes of mind (Resulaj et al. 2009, van den Berg et al. 2016a).”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Pleskac & Busemeyer 2010
Constraints on postdecisional evidence accumulation may affect the extent to which confidence estimates faithfully track performance.
“In turn, constraints on postdecisional evidence accumulation may affect the extent to which confidence estimates faithfully track performance (Desender et al. 2022, Pleskac & Busemeyer 2010).”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Pleskac & Busemeyer 2010
Longer latencies of confidence judgments are related to lower confidence ratings.
“This assumption is supported by the finding that longer latencies of CJ are related to lower confidence ratings (Kälin & Roebers, 2020;Pleskac & Busemeyer, 2010).”
From Longitudinal associations between executive functions and metacognitive monitoring in 5- to 8-year-olds (2022) · cites this paper as Pleskac & Busemeyer, 2010
Confidence can be measured independently of the choice process and is conceptualized as a second-order metacognitive evaluation.
“In contrast, the field of perceptual decision-making has highlighted the fact that confidence can be measured independently of the choice process itself9,10, where it is conceptualized as reflecting a “second-order” metacognitive evaluation.”
From Confidence in value-based choice (2013) · cites this paper as [10]
A single process can explain confidence in choices made in perceptual and cognitive tasks.
“Pleskac and collaborators have shown that a single process can explain confidence in choices made in perceptual (line discrimination and random dot motion) and cognitive (city size inference) tasks (Pleskac & Busemeyer, 2010;Yu, Pleskac, & Zeigenfuse, 2015).”
From Individual consistency in the accuracy and distribution of confidence judgments (2016) · cites this paper as Pleskac & Busemeyer, 2010
A model based on a single process to compute confidence in different domains can explain what factors control the degree of correlation between tasks.
“Moreover, they show that a model based on a single process to compute confidence in different domains can explain what factors control the degree of correlation between tasks.”
From Individual consistency in the accuracy and distribution of confidence judgments (2016) · cites this paper as Pleskac & Busemeyer, 2010
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Collins, A. G. E., & Shenhav, A. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01126-y · Cited by 104 · see citing works
Wise or mad crowds? The cognitive mechanisms underlying information cascades
Tump, A. N., Pleskac, T. J., & Kurvers, R. H. J. M. (2020) · Science Advances · doi:10.1126/sciadv.abb0266 · Cited by 99 · see citing works
Self-citationKausel, E. E., Culbertson, S. S., & Madrid, H. P. (2016) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2016.07.005 · Cited by 98 · see citing works
Confidence predicts speed-accuracy tradeoff for subsequent decisions
Desender, K., Boldt, A., Verguts, T., & Donner, T. H. (2019) · eLife · doi:10.7554/elife.43499 · Cited by 99 · see citing works
Visual Decision-Making in an Uncertain and Dynamic World
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Inferring subjective states through the observation of actions
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Curiosity as a Metacognitive Feeling
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- Authors
- Pleskac, T. J., & Busemeyer, J. R.
- Affiliations
- Michigan State University (US)
- Venue
- Psychological Review
- Published
- 2010
- Volume
- 117
- Issue
- 3
- Pages
- 864-901
- ISSN
- 0033-295X (ISSN-L)
- 1939-1471
- OpenAlex
- W2158389550
- Cited by
- 722
- References
- 163
- Citations by year
- 2026: 50 · 2025: 48 · 2024: 52 · 2023: 66 · 2022: 49 · 2021: 57 · 2020: 61 · 2019: 43 · 2018: 45 · 2017: 45 · 2016: 51 · 2015: 35 · 2014: 55 · 2013: 19 · 2012: 27
- FWCI
- 14.52
- Type
- journal article
- Language
- en
- Update notices
- correction (2011-01-17)
- Open access
- closed
- Locations
- Psychological Review (publishedVersion)
- PubMed (publishedVersion)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Funders
- National Institute of Mental Health (MH019879)
- National Science Foundation (0817965)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- drift-diffusion model, confidence judgments, decision time, choice, random walks, evidence accumulation, time pressure, perceptual decision making, knowledge-based decision making, optimal decision strategies
- MeSH terms
- Choice Behavior, Decision Making, Humans, Judgment, Reaction Time, Time Factors, Signal Detection, Psychological
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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