I will be leading a workshop on Bayesian analysis, where I need to make all Baysian analyses as simple as possible for the particular audience. Therefore, I've decided to allow participants to choose between R and Stata. I assume that for many researchers, initial use of Bayes might be easier in Stata. (I've never used Stata for Bayesian analysis before myself.)

But when using Stata's convenient bayes: prefix, I'm not able to get the PPP (posterior predictive p-value), which summarises the discrepancies between the model and the data.

Code:
. bayespredict {_ysim1} {_ysim2}, saving(prdata)
bayespredict is supported only after bayesmh
Which would make running Bayesian analyses easier in R (with the blavaan package) than in Stata. Is there no possible way to get Stata to provide the PPP after the bayes: prefix? As data analysists, we always need the PPP after running Bayes.

If PPP is not computed after the bayes: prefix, I would suggest including PPP by default in Stata 18.
I also suggest increasing the default number of chains to (at least) 2, rather than the current 1. I believe Bayesian statisticians will agree that Bayesian analyses should always use at least 2 chains to ensure robust results (some suggest 3 chains).