This seems to be the go-to recommendation when considering a prior for a model.
In my case, I am running mixed effects (with random subject and item effects) regressions (both linear and logistic), and am looking for a single weakly informative prior to put on all fixed effects and their interactions.
The prior that seems to be suggested in the resource I linked to is a Cauchy distribution with a mean of 0 and a scale of 2.5. However it assumes that: all binary predictors are centred at 0 and have a difference of 1 between low and high values. It also assumes that all continuous predictors have a mean of 0 and a sd of 0.5
I am hesitant to rescale all of my variables. Is there a well regarded generic weakly informative prior that doesn't require rescaling?