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

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.

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

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

ORCID: Gronau, Quentin F., Wagenmakers, Eric-Jan, Heck, Daniel W.

and Matzke, Dora

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