Overview
Availability
- Dr Nathan Evans is:
- Available for supervision
Fields of research
Qualifications
- Doctor of Philosophy, University of Newcastle
Research interests
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Moving beyond response time and choice in models of decision-making
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Methods for efficiently fitting complex cognitive models
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Improving model-based inference in cognitive science
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Selective influence assumptions in models of decision-making
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Applying models of decision-making to practical research questions
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Urgency and the time-course of decision-making
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Identifiability concerns in models of decision-making
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Model-based inference in conflict tasks
Works
Search Professor Nathan Evans’s works on UQ eSpace
2019
Journal Article
Assessing the practical differences between model selection methods in inferences about choice response time tasks
Evans, Nathan J. (2019). Assessing the practical differences between model selection methods in inferences about choice response time tasks. Psychonomic Bulletin and Review, 26 (4), 1070-1098. doi: 10.3758/s13423-018-01563-9
2019
Journal Article
Response-time data provide critical constraints on dynamic models of multi-alternative, multi-attribute choice
Evans, Nathan J., Holmes, William R. and Trueblood, Jennifer S. (2019). Response-time data provide critical constraints on dynamic models of multi-alternative, multi-attribute choice. Psychonomic Bulletin and Review, 26 (3), 901-933. doi: 10.3758/s13423-018-1557-z
2019
Journal Article
Optimal or not; depends on the task
Evans, Nathan J., Bennett, Aimee J. and Brown, Scott D. (2019). Optimal or not; depends on the task. Psychonomic Bulletin and Review, 26 (3), 1027-1034. doi: 10.3758/s13423-018-1536-4
2019
Journal Article
Theoretically meaningful models can answer clinically relevant questions
Evans, Nathan J. and Wagenmakers, Eric-Jan (2019). Theoretically meaningful models can answer clinically relevant questions. Brain, 142, 1172-1175. doi: 10.1093/brain/awz073
2019
Journal Article
Thermodynamic integration via differential evolution: a method for estimating marginal likelihoods
Evans, Nathan J. and Annis, Jeffrey (2019). Thermodynamic integration via differential evolution: a method for estimating marginal likelihoods. Behavior Research Methods, 51 (2), 930-947. doi: 10.3758/s13428-018-1172-y
2019
Journal Article
Thermodynamic integration and steppingstone sampling methods for estimating Bayes factors: a tutorial
Annis, Jeffrey, Evans, Nathan J., Miller, Brent J. and Palmeri, Thomas J. (2019). Thermodynamic integration and steppingstone sampling methods for estimating Bayes factors: a tutorial. Journal of Mathematical Psychology, 89, 67-86. doi: 10.1016/j.jmp.2019.01.005
2019
Journal Article
When humans behave like monkeys: feedback delays and extensive practice increase the efficiency of speeded decisions
Evans, Nathan J. and Hawkins, Guy E. (2019). When humans behave like monkeys: feedback delays and extensive practice increase the efficiency of speeded decisions. Cognition, 184, 11-18. doi: 10.1016/j.cognition.2018.11.014
2019
Journal Article
Some evidence for an association between early life adversity and decision urgency
Knowles, Johanne P., Evans, Nathan J. and Burke, Darren (2019). Some evidence for an association between early life adversity and decision urgency. Frontiers in Psychology, 10. doi: 10.3389/fpsyg.2019.00243
2018
Journal Article
Modeling the covariance structure of complex datasets using cognitive models: an application to individual differences and the heritability of cognitive ability
Evans, Nathan J., Steyvers, Mark and Brown, Scott D. (2018). Modeling the covariance structure of complex datasets using cognitive models: an application to individual differences and the heritability of cognitive ability. Cognitive Science, 42 (6), 1925-1944. doi: 10.1111/cogs.12627
2018
Journal Article
Refining the law of practice
Evans, Nathan J., Brown, Scott D., Mewhort, Douglas J. K. and Heathcote, Andrew (2018). Refining the law of practice. Psychological Review, 125 (4), 592-605. doi: 10.1037/rev0000105
2018
Journal Article
Bayes factors for the linear ballistic accumulator model of decision-making
Evans, Nathan J. and Brown, Scott D. (2018). Bayes factors for the linear ballistic accumulator model of decision-making. Behavior Research Methods, 50 (2), 589-603. doi: 10.3758/s13428-017-0887-5
2017
Journal Article
The computations that support simple decision-making: A comparison between the diffusion and urgency-gating models
Evans, Nathan J., Hawkins, Guy E., Boehm, Udo, Wagenmakers, Eric-Jan and Brown, Scott D. (2017). The computations that support simple decision-making: A comparison between the diffusion and urgency-gating models. Scientific Reports, 7 (1) 16433. doi: 10.1038/s41598-017-16694-7
2017
Journal Article
Need for closure is associated with urgency in perceptual decision-making
Evans, Nathan J., Rae, Babette, Bushmakin, Maxim, Rubin, Mark and Brown, Scott D. (2017). Need for closure is associated with urgency in perceptual decision-making. Memory and Cognition, 45 (7), 1193-1205. doi: 10.3758/s13421-017-0718-z
2017
Journal Article
Model flexibility analysis does not measure the persuasiveness of a fit
Evans, Nathan J., Howard, Zachary L., Heathcote, Andrew and Brown, Scott D. (2017). Model flexibility analysis does not measure the persuasiveness of a fit. Psychological Review, 124 (3), 339-345. doi: 10.1037/rev0000057
2017
Journal Article
People adopt optimal policies in simple decision-making, after practice and guidance
Evans, Nathan J. and Brown, Scott D. (2017). People adopt optimal policies in simple decision-making, after practice and guidance. Psychonomic Bulletin and Review, 24 (2), 597-606. doi: 10.3758/s13423-016-1135-1
Funding
Past funding
Supervision
Availability
- Dr Nathan Evans is:
- Available for supervision
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Available projects
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Beyond Response Time and Choice: Understanding Changes of Mind in Decisions
The project aims to provide novel experimental insight into how people change their minds during decisions, through identifying the cognitive architecture that reflects the behaviour that we observe from people. The project provides a substantially deeper understanding of the cognitive decision process and how it changes over time, as opposed to previous research focusing on only the final response that people make. The expected outcome is a comprehensive understanding of the human decision process through cognitive models that provide an accurate reflection of this mental process.
Note that there is a UQ earmarked PhD scholarship available for this project.
Media
Enquiries
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