A Simple Method for Comparing Complex Models: Bayesian Model Comparison for Hierarchical Multinomial Processing Tree Models Using Warp-III Bridge Sampling
Open Access
- 27 November 2018
- journal article
- research article
- Published by Springer Science and Business Media LLC in Psychometrika
- Vol. 84 (1), 261-284
- https://doi.org/10.1007/s11336-018-9648-3
Abstract
Multinomial processing trees (MPTs) are a popular class of cognitive models for categorical data. Typically, researchers compare several MPTs, each equipped with many parameters, especially when the models are implemented in a hierarchical framework. A Bayesian solution is to compute posterior model probabilities and Bayes factors. Both quantities, however, rely on the marginal likelihood, a high-dimensional integral that cannot be evaluated analytically. In this case study, we show how Warp-III bridge sampling can be used to compute the marginal likelihood for hierarchical MPTs. We illustrate the procedure with two published data sets and demonstrate how Warp-III facilitates Bayesian model averaging.Keywords
Funding Information
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (406.16.528)
- H2020 European Research Council (283876)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (451-15-010)
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