I'm trying to program sample size for a bayesian adaptive design, with a binary performance goal of say, AE rate less than 20%. Data will be analyzed after X subjects, and if needed after each subsequent Y subjects. There are three possible outcomes after each stage until success, futility or max sample size of N is reached. So I need to program simulations and probability required for determining study success at each analysis stage.
Note that success decision can be something like: "Termination of enrollment for success if the posterior probability using observed data was sufficient to meet the performance goal (99% probability or greater for 50 and 75 subject interim checks, 97.5% thereafter)"
Continued accrual due to reasonable predictive probability (10% or greater) that performance goal can be met with more subjects.
Futility if predictive probability the performance goal could be met with enrollment of more subjects was less than 10%
Thank you for any insight....
