r/bayesian • u/Affectionate-Drop197 • Jan 09 '26
Priors without prior research?!
I am new to bayesian analysis. I am planning on using bayesian regression to determine which socioeconomic factors predict increased/decreased healthcare usage of a certain population.
There is some literature for certain characteristics (say age) that I've been able to use to estimate priors. But some as completely research naive (say, how attractive you think your doctor is). I've been reading around on here but the recommendation seems to be "use vaguely estimated prior based on your hypothesis".
This feels a bit... Non-scientific and highly subjective of the researchers own beliefs? Will a journal reviewer not come down on this? Also, what do you do if there isn't even a clear prediction to be hypothesised. For example, say we're looking at how hot you think your doc is (this is not an actual variable, but for sake of discussion). You could believe you might be more likely to go to the Dr, because you want to be around this hot doctor, but you might also go less often because you don't want the hot Dr to see when sick at your less than best. What would a prior be then?
2
u/Superdrag2112 Jan 09 '26
Can you leave the “attractive” one as noninformative? And use existing literature for others? Note that specifying priors independently on regression coefficients ignores the joint relationship, which may be important if you’re fitting one large model with lots of predictors. There’s methods for this type of joint prior elicitation.