I’m once again having to fit and compare hundreds of categorical multilevel models using brms with the cmdstanr backend, and the computational cost is enormous. Due to that cost, I need to minimize computation time by using as few iterations (and as low an adapt_delta) as possible. These minimization needs make it imperative that I have some quick and simple metric for checking whether the fit is healthy.

What’s the simplest and quickest way for an inexpert to verify that the model has converged properly?

**Can I rest assured that whenever brms does not produce automatic warnings, it is safe to proceed?** This would be the most convenient approach.

Or should I rather do something like `all(rhat(model)) < 1.05`

and if the answer is TRUE, consider it safe to proceed?

Or would it be better to call `rstan::check_hmc_diagnostics(model$fit)`

, and assume it’s safe to proceed whenever this check reports zero divergences, zero iterations saturating the maximum treedepth, and zero “pathological” E-BFMI behaviors?