C-Statistics and ROC's counterparts in Bayes approach, is Emax does the job?

I need to assess the effect of a continuous metric obtained from a model on a binary outcome and determine a population-level cut-point(s).
Can anyone kindly guide whether there is a similar approach as ROC in Bayes approach?
Thanks in advance.
I have seen Emax, but not sure if I can interpret it as ROC.
Thanks for your hints and guidance.

You can use C and ROC with Bayesian models, but before doing that, it’s good to read what Frank Harrell who originally proposed C-statistics now says about “Problems with ROC Curves and Cutoff” in

I don’t know what is Emax


Thanks a lot for sharing this and the hints. I agree and concern about misclassification using ROC. It is a common mistake in medical practice, unfortunately, the practitioners usually need to make decisions and without such information would not follow a new metric/tool :(

@avehtari Do you have an alternative suggestion to avoid misclassification?
What about a similar approach as beta-blocker and mortality?

You might get more help if you (cross) post at Data Methods as that is a specialised forum.