A simple method for comparing complex models: Bayesian model comparison for hierarchical multinomial processing tree models using Warp-III bridge sampling

Gronau, Quentin F. ; Wagenmakers, Eric-Jan ; Heck, Daniel W. ; Matzke, Dora

DOI: https://doi.org/10.1007/s11336-018-9648-3
URL: https://link.springer.com/article/10.1007%2Fs11336...
Additional URL: https://www.researchgate.net/publication/329224895...
Document Type: Article
Year of publication: 2019
The title of a journal, publication series: Psychometrika
Volume: 84
Issue number: 1
Page range: 261-284
Place of publication: New York, NY
Publishing house: Springer Science + Business Media
ISSN: 0033-3123 , 1860-0980
Publication language: English
Institution: Außerfakultäre Einrichtungen > Graduate School of Economic and Social Sciences- CDSS (Social Sciences)
School of Social Sciences > Kognitive Psychologie (Seniorprofessur) (Erdfelder 2019-)
Subject: 150 Psychology
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.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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