@bdyetton Thanks for the PR!
Just for clarification: I didn’t mean a log transform, but a logit transform.
I’m not sure what “accurate” means in this context, a logit-normal model is a bit different from the beta distribution, but unless you have a good reason why the beta would somehow be the right one, I don’t see a clear advantage to using it. They are in fact quite similar, a normal distribution and the logit of a beta aren’t that different, the beta has a bit longer tails. But the interpretation of mean and std in the logit-normal case are I think a bit more natural.