This tutorial provides the reader with a basic tutorial how to perform a Bayesian regression in Blavaanm using Jags instead of Stan as a MCMC sampler. You can find the Blavaan Jags tutorial here. We will not delve into the the differences between Stan and Jags here (a technical explanation can be found here and a more accessible blog post here). For now it suffices to say that Stan is more efficient, especially for complex models. While using Blavaan the biggest difference is how you specify the priors. Instead of using a variance, as in Jags, Stan uses standard deviations.
Throughout this tutorial, the reader will be guided through importing data files, exploring summary statistics and regression analyses. Here, we will exclusively focus on Bayesian statistics.
In this tutorial, we start by using the default prior settings of the software. In a second step, we will apply user-specified priors, and if you really want to use Bayes for your own data, we recommend to follow the WAMBS-checklist, also available in other software.
You can find the whole tutorial here