blavaan : Bayesian Structural Equation Models via Parameter Expansion

Merkle, Edgar C.; Rosseel, Yves

doi:10.18637/jss.v085.i04

Cited by 361Statistical Methods and Bayesian InferencePsychometric Methodologies and TestingData Analysis with R

blavaan : Bayesian Structural Equation Models via Parameter Expansion

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Merkle, Edgar C., Rosseel, Yves·2018·Journal of Statistical Software

DOI 10.18637/jss.v085.i04

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Abstract

This article describes blavaan, an R package for estimating Bayesian structural equation models (SEMs) via JAGS and for summarizing the results. It also describes a novel parameter expansion approach for estimating specific types of models with residual covariances, which facilitates estimation of these models in JAGS. The methodology and software are intended to provide users with a general means of estimating Bayesian SEMs, both classical and novel, in a straightforward fashion. Users can estimate Bayesian versions of classical SEMs with lavaan syntax, they can obtain state-of-the-art Bayesian fit measures associated with the models, and they can export JAGS code to modify the SEMs as desired. These features and more are illustrated by example, and the parameter expansion approach is explained in detail.

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Missing data were addressed using the default full information procedure in blavaan.
“Missing data were addressed by utilizing the default full information procedure implemented in blavaan (Merkle & Rosseel, Citation2018).”
From How do care-related beliefs contribute to depression and anxiety in family caregivers of people with dementia? Testing a cognitive vulnerability-stress model. (2025) · cites this paper as Merkle & Rosseel, 2018
The Posterior predictive checks section discusses difficulties calculating a fit statistic when data are missing, but does not describe a default full-information procedure for handling missing data in model estimation. Searches for “full information maximum likelihood,” “FIML,” and missing-observation handling found no passage establishing the claimed default. (LLM, conf=0.72)
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see, e.g., Kass and Raftery (1995) and Rouder, Morey, Verhagen, Province, and Wagenmakers (2016). Affiliation: Edgar C. Merkle Department of Psychological Sciences University of Missouri 28A McAlester Hall Columbia, MO, 65211, United States of America E-mail: merklee@missouri.edu URL: http://faculty.missouri.edu/~merklee/ Journal of Statistical Software http://www.jstatsoft.org/ published by the Foundation for Open Access Statistics http://www.foastat.org/ June 2018, Volume 85, Issue 4 Submitted: 2015-11-17 doi:10.18637/jss.v085.i04 Accepted: 2017-01-31

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Authors: Merkle, E. C., & Rosseel, Y.
Affiliations: University of Missouri (US)
Ghent University (BE)
ORCID: Rosseel, Yves
Venue: Journal of Statistical Software
Publisher: Foundation for Open Access Statistic
Published: 2018
Volume: 85
Issue: 4
ISSN: 1548-7660 (ISSN-L)
DOI: 10.18637/jss.v085.i04
OpenAlex: W2177847511
Cited by: 360
References: 47
Citations by year: 2026: 59 · 2025: 44 · 2024: 25 · 2023: 34 · 2022: 41 · 2021: 53 · 2020: 49 · 2019: 31 · 2018: 14 · 2017: 9 · 2016: 1
FWCI: 30.50
Type: journal article
Language: en
Open access: diamond
doi.org
Licence: cc-by
Locations: Journal of Statistical Software (publishedVersion, cc-by)
arXiv (Cornell University) (submittedVersion)
Ghent University Academic Bibliography (Ghent University) (submittedVersion, other-oa)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
arXiv (Cornell University)
Funders: National Science Foundation (1061334, 1460719)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Physical Sciences › Computer Science › Artificial Intelligence › Data Analysis with R
Keywords: Bayesian structural equation models, parameter expansion, residual covariance, JAGS, R package, model estimation

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