Proposed method evaluates operating characteristics and sample sizes for bayesian platform trials, highlighting computational efficiency.
Key Points
The proposed method improves efficiency in evaluating the operating characteristics of bayesian platform trials, and is adaptable to real-world constraints.
By modeling joint sampling distributions of posterior probabilities, the method simplifies assessments across multiple endpoints and trial stages.
Monte carlo simulation is used to estimate posterior probabilities, reducing computational burden compared to traditional approaches.
The design is motivated by the complexities observed in the sstarlet trial, focused on tuberculosis preventive therapies.