Charlie Williams writes:
As I get interested in Bayesian approaches to statistics, I have one question I wondered if you would find interesting to address at some point on the blog.
What does Bayesian work look like in action across a field? From experience, I have some feeling for how ongoing debates evolve (or not) with subsequent studies in response to earlier findings. I wonder if you know how this happens in practice when multiple researchers are using Bayesian approaches. How much are previous findings built into priors? How much advance comes from model improvement? And in a social science field where self-selection and self-interest play a role, how are improved “treatment” effects incorporated and evaluated?
I thought you might know of a field where actual back and forth has been carried out mostly in the context of Bayesian analysis or inference, and I thought it would be interesting to take a look at an example as I think about my own field.
My reply: I’ve seen Bayesian methods used for individual studies, and I’ve seen Bayesian meta-analysis (of course), but I can’t recall seeing an entire field of inquiry placed in a Bayesian perspective, with the posterior inference from an earlier study used as the prior for the next.