Quick and simple question about specifying priors for a logistic regression with stan_glm. Can someone explain exactly what is meant by both “scale” and “location”? I thought I got it, then I read this link and talked to my mentor a bit, and now it’s fuzzy. I dug through the documentation in the user’s guide and manual and couldn’t find explicit definitions or references to either.
Specifically, does the location simply mean “expected regression coefficient”? And if so, in the case of a logistic model with stan_glm, do I have to transform my expected coefficient values before putting them in the prior? Lets say I got a posterior beta weight of 1.3 for a coefficient in experiment one and wanted to set that as the prior location for experiment two. Would the location just be 1.3? Or log(1.3)? Etc.
Does scale mean the Standard Deviation? Or is it also a coefficient value, that is equal to 1 Standard Deviation? (e.g. I input 1.5, which means 1.0 Standard Deviations in that distribution=1.5 on the unit scale)