ArticleBehavior research methods2020
Computing Bayes factors for evidence-accumulation models using Warp-III bridge sampling.
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 13 papers.
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Who cites it
13 citing papers in PubMed.
- Disentangling within- and between-subject correlations in cognitive models: The essential role of hierarchical estimation.Behavior research methods · 2026Article
- Reliability, bias, and computational cost of estimating the Bayes factor using bridge sampling and the Savage-Dickey density ratio.Behavior research methods · 2026Article
- Bayesian hierarchical cognitive modeling with the EMC2 package.Behavior research methods · 2026Article
- An EZ Bayesian hierarchical drift diffusion model for response time and accuracy.Psychonomic bulletin & review · 2025Article
- Hierarchical Bayesian estimation for cognitive models using Particle Metropolis within Gibbs (PMwG): A tutorial.Behavior research methods · 2025Article
- A Good check on the Bayes factor.Behavior research methods · 2024Article
- In human-machine trust, humans rely on a simple averaging strategy.Cognitive research: principles and implications · 2024Article
- A tutorial on fitting joint models of M/EEG and behavior to understand cognition.Behavior research methods · 2024Article
- Dopamine Alters the Effect of Brain Stimulation on Decision-Making.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Using cognitive modeling to examine the effects of competition on strategy and effort in races and tournaments.Psychonomic bulletin & review · 2023Article
- Prior information use and response caution in perceptual decision-making: No evidence for a relationship with autistic-like traits.Quarterly journal of experimental psychology (2006) · 2021Article
- Systematic Parameter Reviews in Cognitive Modeling: Towards a Robust and Cumulative Characterization of Psychological Processes in the Diffusion Decision Model.Frontiers in psychology · 2020Article
- Building bridges between brain and behavior: An open-source toolbox for joint modeling with fMRI.Imaging neuroscience (Cambridge, Mass.)Article
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3 authors.
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Abstract
Over the last decade, the Bayesian estimation of evidence-accumulation models has gained popularity, largely due to the advantages afforded by the Bayesian hierarchical framework. Despite recent advances in the Bayesian estimation of evidence-accumulation models, model comparison continues to rely on suboptimal procedures, such as posterior parameter inference and model selection criteria known to favor overly complex models. In this paper, we advocate model comparison for evidence-accumulation models based on the Bayes factor obtained via Warp-III bridge sampling. We demonstrate, using the linear ballistic accumulator (LBA), that Warp-III sampling provides a powerful and flexible approach that can be applied to both nested and non-nested model comparisons, even in complex and high-dimensional hierarchical instantiations of the LBA. We provide an easy-to-use software implementation of the Warp-III sampler and outline a series of recommendations aimed at facilitating the use of Warp-III sampling in practical applications.
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