This discussion was extremely useful https://github.com/stan-dev/rstanarm/issues/88

and clarified some questions I had about the priors for the diagonal of the covariance matrix.

However, I wonder if it’s possible to visualise what the decov prior implies for each of the variance parameters?

Also, in a multilevel model is it possible to encode prior information about the proportions of variance explained at different levels? For example, let’s say I have a model: `y~(1|class)+(1|school)`

if I thought that 20% of the variance was explained by class and 10% by school, can I include that in the prior?