I am a bit unsure about how to quantify how informative a prior is.
For a current fit I want to use informative normal distributed priors.
In total I have 15 parameters, which range from values close to 0 (the closest is 0.0001) to 3.
I want all 15 priors to be roughly as informative as each other.
Regarding this I wanted to ask if the position of the peak/mean for the normal distributions affects how informative the prior is.
As an example I would like to ask if normal(0.01, 3) is less informative than normal(3, 3) and if that is less informative than normal(10, 3).
If possible I would appreciate an explanation on why the position of the distribution affects how informative the prior is.
I would greatly appreciate any answers and would like to thank you for reading this this far.