I run a multilevel model with brms (file attached). I kept one main response variable in its native distributions (beta distribution), then transformed covariates to linearize and standardized covariates for two reasons. It improves model fit because it centers at zero and equalizes variance. Second, it equalizes comparisons of variance explained.
The trace plots look good, but I have a warning saying that the pareto is bigger than 0.7. I checked on this forum and people suggest changing the distribution of each response variable. For example, move from gaussian to lognormal or gamma or modify the priors. In my case since I have already scaled the covariates, I have negative values for my covariables and therefore cannot use the lognormal or the gamma distribution. I also used the standard prior.
How could I improve my model so that I don’t have this warning message?
pareto >0.7.pdf (160.4 KB)