bayesian-reanalysis

What problem does it solve?

This Skill addresses the challenge of interpreting clinical trial results when prior evidence exists, providing a probabilistic assessment of a meaningful treatment effect beyond traditional frequentist methods.

Core Features & Use Cases

• Bayesian Monte Carlo Re-analysis: Integrates literature-derived priors with trial data to estimate the probability of a clinically meaningful effect.
• Prior Sensitivity Analysis: Assesses the robustness of conclusions across skeptical, evidence-based, and enthusiastic prior specifications.
• Use Case: Evaluating an underpowered trial where prior studies suggest a potential effect, this Skill can quantify the probability that the observed data, combined with existing knowledge, supports a meaningful treatment benefit.

Quick Start

Use the bayesian-reanalysis skill to perform a Bayesian analysis on the current trial data using the provided prior evidence report.