ArticleBehavior research methods2020
Quantifying the benefits of using decision models with response time and accuracy data.
Article in Behavior research methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
- A Quadratic Bifactor Hierarchical Model for Jointly Modelling the Nonlinear Relationship Between Response Accuracy and Response Time in Cognitive Testing.Journal of Intelligence · 2026Article
- Cognitive Process Models Reveal Meaningful Brain-Behavior Associations in the Adolescent Brain Cognitive Development Study Stop-signal Task.Journal of cognitive neuroscience · 2026Article
- Childhood Material Hardship Linked to Adolescent Neurocognition: A Computational Modeling Approach.Developmental science · 2026Article
- Mindfulness training enhances face working memory: evidence from the drift-diffusion model.NPJ science of learning · 2025Article
- An EZ Bayesian hierarchical drift diffusion model for response time and accuracy.Psychonomic bulletin & review · 2025Article
- Leveraging bifactor modeling to test prospective direct and indirect effects of adolescent alcohol use and externalizing symptoms on the development of task-general executive functioning.Development and psychopathology · 2025Article
- Optimizing the Color Shapes Task for Ambulatory Assessment and Drift Diffusion Modeling: A Factorial Experiment.JMIR formative research · 2025Article
- Diminished reactivity effect of confidence rating on perceptual decision-making in depression.Frontiers in neuroscience · 2025Article
- The forced-response method: A new chronometric approach to measure conflict processing.Behavior research methods · 2024Article
- When 2 become 1: Autistic simultaneity judgements about asynchronous audiovisual speech.Quarterly journal of experimental psychology (2006) · 2024Article
- Confidence ratings increase response thresholds in decision making.Psychonomic bulletin & review · 2024Article
- Information processing style and institutional trust as factors of COVID vaccine hesitancy.Scientific reports · 2024Article
- What can evidence accumulation modelling tell us about human social cognition?Quarterly journal of experimental psychology (2006) · 2024Article
- To see or not to see: the parallel processing of self-relevance and facial expressions.Cognitive research: principles and implications · 2023Article
- Dopamine Alters the Effect of Brain Stimulation on Decision-Making.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Mechanisms of Training-Related Change in Processing Speed: A Drift-Diffusion Model Approach.Journal of cognition · 2023Article
- Problems when fixing the response bias parameter z in drift diffusion analysis : A Commentary on Stafford et al. (2020).Behavior research methods · 2023Article
- Listening efficiency in adult cochlear-implant users compared with normally-hearing controls at ecologically relevant signal-to-noise ratios.Frontiers in human neuroscience · 2023Article
- Integration of visual motion and orientation signals in dyslexic children: an equivalent noise approach.Royal Society open science · 2022Article
- Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks.Scientific reports · 2022Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Response time and accuracy are fundamental measures of behavioral science, but discerning participants' underlying abilities can be masked by speed-accuracy trade-offs (SATOs). SATOs are often inadequately addressed in experiment analyses which focus on a single variable or which involve a suboptimal analytic correction. Models of decision-making, such as the drift diffusion model (DDM), provide a principled account of the decision-making process, allowing the recovery of SATO-unconfounded decision parameters from observed behavioral variables. For plausible parameters of a typical between-groups experiment, we simulate experimental data, for both real and null group differences in participants' ability to discriminate stimuli (represented by differences in the drift rate parameter of the DDM used to generate the simulated data), for both systematic and null SATOs. We then use the DDM to fit the generated data. This allows the direct comparison of the specificity and sensitivity for testing of group differences of different measures (accuracy, reaction time, and the drift rate from the model fitting). Our purpose here is not to make a theoretical innovation in decision modeling, but to use established decision models to demonstrate and quantify the benefits of decision modeling for experimentalists. We show, in terms of reduction of required sample size, how decision modeling can allow dramatically more efficient data collection for set statistical power; we confirm and depict the non-linear speed-accuracy relation; and we show how accuracy can be a more sensitive measure than response time given decision parameters which reasonably reflect a typical experiment.
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