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Evaluate Bayesian SEM goodness of fit blavaan

Cross Validated Asked by L.sicilis on December 13, 2020

I’m currently trying to identify how to evaluate model fit with Bayesian SEM. I’ve been reading that the posterior predictive p-value can be used, with a p-value of approximately 0.5 indicating good model fit (Song and Lee 2012). This source also suggests residual analysis can be used for BSEMs.

I had two questions regarding this:

1.) Are there any additional fit indices or methods used to evaluate BSEMs?

2.) Does anyone know how to perform residual analysis with the blavaan package in R?

Source:
Song, X. and S. Lee. 2012. Basic and Advanced Bayesian Structural Equation Modeling. ISBN 978-0-470-66952-5.

One Answer

1 - I would start with this article:

Garnier-Villarreal, M., & Jorgensen, T. D. (2019). Adapting fit indices for Bayesian structural equation modeling: Comparison to maximum likelihood. Psychological Methods. https://doi.org/10.1037/met0000224

If you need more:

Cain, M. K., & Zhang, Z. (2019). Fit for a Bayesian: An evaluation of PPP and DIC for structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 26(1), 39–50. https://doi.org/10.1080/10705511.2018.1490648

Asparouhov, T., & Muthén, B. O. (2019). Advances in Bayesian model fit evaluation for structural equation models. Statmodel. http://www.statmodel.com/download/BayesFit.pdf

Hoofs, H., van de Schoot, R., Jansen, N. W. H., & Kant, Ij. (2018). Evaluating model fit in Bayesian confirmatory factor analysis with large samples: Simulation study introducing the BRMSEA. Educational and Psychological Measurement, 78(4), 537–568. https://doi.org/10.1177/0013164417709314

2 - You can use lavaan's lavResiduals function, see an example using:

library(blavaan)    
example(ppmc)

Answered by Sinval on December 13, 2020

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