blavaan: Bayesian Structural Equation Models via Parameter Expansion

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 t...

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Bibliographic Details
Main Authors: Edgar C. Merkle, Yves Rosseel
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2018-06-01
Series:Journal of Statistical Software
Subjects:
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/2441
Description
Summary: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.
ISSN:1548-7660