RMS Titanic Binary Logistic Case Study

This has been address on the Stan discourse forum, I seem to remember, where an approximate technique was used for the marginalization over the random effects. I hope someone will respond who is more experienced about random effect Bayesian models. My sense is that for estimates on the link function scale (e.g., predicted log odds, odds ratios) setting random effects to their mean (zero) is OK, but for probability-scale estimates we need to marginalize. That would include calibration curves. I took the easy way out.