Applying Bayeisan Optimisation to FACTS trial designs and choosing stopping bound
Автор: Berry Consultants
Загружено: 6 нояб. 2024 г.
Просмотров: 67 просмотров
A look at using machine learning to optimise trial sample sizes, firstly in a trivial 2 arm case, and then in a more complex 6 arm, phase 2 case, where the objective is to have at least 50% probability of selecting the correct MED. We then look at optimizing Bayesian “Goldilocks” two arm design, by processing simulation results in R.

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