If Alice decides to conduct 12 trials, then the sampling distribution of the data is the binomial distribution. If Alice decides to sample until 3 successes are achieved, then the sampling distribution of the data is the negative binomial distribution. These two distributions are proportional when considered as functions of the parameter p (i.e., as likelihood functions). So in this specific case, from a Bayesian point of view the sampling mechanism does not influence the conclusions. (This is in contradistinction to inference based on p-values.)
In general, you are correct to say that biased data collection is not irrelevant; this idea is given a complete treatment in Chapter 6 (or 7, I forget which) of Gelman et al.’s Bayesian Data Analyses, 2nd ed.
If Alice decides to conduct 12 trials, then the sampling distribution of the data is the binomial distribution. If Alice decides to sample until 3 successes are achieved, then the sampling distribution of the data is the negative binomial distribution. These two distributions are proportional when considered as functions of the parameter p (i.e., as likelihood functions). So in this specific case, from a Bayesian point of view the sampling mechanism does not influence the conclusions. (This is in contradistinction to inference based on p-values.)
In general, you are correct to say that biased data collection is not irrelevant; this idea is given a complete treatment in Chapter 6 (or 7, I forget which) of Gelman et al.’s Bayesian Data Analyses, 2nd ed.