Is Meta Analysis the Future of Bayesian Statistics?
To summarize these two concepts:
Bayesian Statistics involve using historical information about the distribution of model parameters to supplement directly observed information. This historical information is referred to as "Bayesian Priors".
Meta Analysis is a form of "statistical analysis that combines the results of multiple scientific studies, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived."
All in all, these two concepts (Bayesian Statistics and Meta Analysis) seem to naturally complement each other. They both aim at using "prior" available information for the purpose of augmenting statistical models in order to derive more "truth" within the environment.
However, for some reason this does not seem to be directly addressed within Meta Analysis.
My Question: In the future, is it reasonable to expect that Bayesian Statistics and Meta Analysis will become more closely related and be almost synonymous with one another?