Could anyone refer a book or resource on the design and analysis of experiments through Bayesian methodology?
I’m a big fan of ‘Statistical Rethinking’ by Richard McElreath. But the author is upfront that he’s an anthropologist; ancient civilizations simply are not producing any more clay cups. So the idea of a randomized control trial is irrelevant to him.
But in my line of work, we absolutely can randomize units and control treatment exposure. From my research, the Frequentist gospel on this topic (for applied researchers) is Design and Analysis of Experiments with R.
I’m looking for the Bayesian analog to this book or the resources that come closest.
How would a Bayesian choose appropriate priors and likelihoods for block designs, pair-wise assignments, panel data, etc?