University Of Tasmania
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Computing Bayes Factors for Evidence-Accumulation Models Using Warp-III Bridge Sampling

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journal contribution
posted on 2023-05-20, 06:11 authored by Gronau, QF, Heathcote, A, Matzke, D
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.


Publication title

Behavior Research Methods




School of Psychological Sciences


Springer New York LLC

Place of publication

United States

Rights statement

Copyright the Author(s) 2019. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

Repository Status

  • Open

Socio-economic Objectives

Expanding knowledge in psychology