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Teacher’s corner: Evaluating informative hypotheses using the Bayes factor in structural equation models

van Lissa,Caspar
; 
Gu,Xin
; 
Mulder,Joris
; 
Rosseel,Y.
; 
van Zundert,Camiel
; 
Hoijtink,Herbert
Abstract
This Teacher’s Corner paper introduces Bayesian evaluation of informative hypotheses for structural equation models, using the free open-source R packages bain, for Bayesian informative hypothesis testing, and lavaan, a widely used SEM package. The introduction provides a brief non-technical explanation of informative hypotheses, the statistical underpinnings of Bayesian hypothesis evaluation, and the bain algorithm. Three tutorial examples demonstrate informative hypothesis evaluation in the context of common types of structural equation models: 1) confirmatory factor analysis, 2) latent variable regression, and 3) multiple group analysis. We discuss hypothesis formulation, the interpretation of Bayes factors and posterior model probabilities, and sensitivity analysis.
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Funding Information: The first author is supported by an NWO Veni grant (NWO grant number VI.Veni.191G.090). The third author is supported by an NWO Vidi Grant (NWO grant number 452-17-006). The last author is supported by a fellowship from the Netherlands Institute for Advanced Studies in the Humanities and Social Sciences, and the Consortium on Individual Development (CID) which is funded through the Gravitation program of the Dutch Ministry of Education, Culture, and Science and the Netherlands Organization for Scientific Research (NWO grant number 024.001.003).
Date
2021
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Tilburg University Research Output Collection
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Bain, INEQUALITY-CONSTRAINED HYPOTHESES, LIKELIHOOD RATIO, bayes factor, informative hypotheses, structural equation modeling
Citation
van Lissa, C, Gu, X, Mulder, J, Rosseel, Y, van Zundert, C & Hoijtink, H 2021, 'Teacher’s corner : Evaluating informative hypotheses using the Bayes factor in structural equation models', Structural Equation Modeling, vol. 28, no. 2, pp. 292-301. https://doi.org/10.1080/10705511.2020.1745644
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https://hdl.handle.net/20.500.14602/74363
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