Bayesian Generalized Linear Mixed Effects Model with binomial outcome

Hi, I would like to to run an Bayesian Generalized Linear Mixed Effects Model with binomial outcome as an R-side mixed effects model, ie by defining the covariance structure. I have read that the R/brms package and R/rstanarm package can do mixed models. brms seems to be simpler and more flexible, but I could not find how to define the covariance structure, so it seems it does only G-side (random effects) models. The R/rstanarm package has the stan_glmer(…, prior_covariance, …) function and covariance argument, so seems to do what I want, though I would prefer to do this in the brms package.

How can I define an R-side mixed model with thee R/brms package?
Which package should I use?

Kr, Shiny

Yes, brms does have some flexibility for this. Check out the discussion in this GitHub issue: correlation structures for residuals · Issue #403 · paul-buerkner/brms · GitHub.