Bayesian Design and Analysis of Experiments [Resource Request]

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?

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Since May 13 any luck regarding this topic?

@Elef - Unfortunately, no. I’ve got two theories

  1. Practitioners primarily use Bayesian stats on observational data so the idea of experimentation is a bit alien

  2. Experimentation w/ Bayesian stats is the wild west w/o broad consensus about how it should be done so nobody, even with experience, wants to risk communicating their ad hoc approach as “the way”

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