Scaling Bayesian Latent Variable Models to Big Education Data

The goal of the proposed project is to develop user-friendly, free, open-source software for estimating the types of Bayesian latent variable models that are often encountered in education: models with multilevel structure, with ordinal variables, and with large sample sizes. This will provide education researchers with tools that allow them to apply state-of-the-art developments quickly and easily in Bayesian statistics to their own datasets. The software will build on the existing R package blavaan for Bayesian structural equation modeling, which relies on the power of Stan for estimation via Hamiltonian Monte Carlo.