I am a clinician who is more adept than average at interpreting clinical trials in a frequentist manner. At this point, interpreting a trial as a frequentist has kind of become a procedure: check internal validity, check null and alternative hypotheses, check power assumptions, look at effect size and confidence intervals, look at p value, etc.
The Bayesian philosophy appeals more to me intuitively, though. I understand what the philosophy of Bayesian inference is because I've taken clinical epidemiology (pre-test probability of disease is updated with test results and likelihood ratio to produce a post-test probability). What I don't know yet is whether there's a similar "procedure" for interpreting a clinical trial the way there is for a frequentist.
What numbers/assumptions/figures do I need from the authors to interpret a study as a Bayesian (e.g. for a frequentist that would be p-value, confidence intervals, etc)? Is there a good "procedure" for interpreting a study as a Bayesian, much like there is for a frequentist interpretation? Are there good publications you know of that explain the process I'm asking for, with clinicians as the intended audience?
I appreciate your help!