Thank you both! I’d say so far the parameter centering and choosing priors was the hardest part for me to figure out.
This final comment is really interesting: Standardizing predictors and outputs in a hierarchical model
Okay so my understanding is that my original model with the non-centered parameters given no divergences would yield appropriate inference as well? The main difference being computational time?
I ask because when I switched to centered I got a cryptic communication error with the sockets. Plan to debug next week. It smells like I blew out memory or something (need to check). If could trust the unscaled version I’d have a nice fallback.