blavaan: Bayesian structural equation models via parameter expansion

TL;DR

blavaan is an R package that simplifies Bayesian structural equation modeling by integrating with JAGS, introducing a novel parameter expansion method for models with residual covariances, and enabling easy estimation and customization.

Contribution

The paper introduces blavaan, a user-friendly R package for Bayesian SEMs, and presents a new parameter expansion technique to improve estimation of models with residual covariances.

Findings

Effective estimation of Bayesian SEMs using blavaan

Implementation of a novel parameter expansion approach

Compatibility with lavaan syntax and advanced fit measures

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.