Bayes Factors for Structural Equation Models with Bridge Sampling and blavaan

Base model diagram I recently completed a very big chunk of my WB fellowship project. The output: A new paper on Bayesian model comparison in structural equation modeling (SEM). The central question is simple: how can we compute Bayes factors for SEMs in a way that is practical, transparent, and flexible enough to incorporate substantive prior information? For the curious: The preprint is available at https://doi.org/10.31234/osf.io/pt2bc_v1.