In this episode, Professor Konstantin Slavin reads aloud an article by Garston Liang, Alexander Thorpe, and Quentin F. Gronau, which delves into the Fragility Index (FI) and its significance in evaluating the robustness of p-value-based conclusions in clinical trials.
Fragility Index (FI): Measures how many participant outcomes need to change to alter the statistical significance of results (e.g., from p < 0.05 to p > 0.05).
Higher FI is Better: A higher FI indicates more robust conclusions, less dependent on a small number of participant changes.
Key Considerations: Includes the alpha criterion (e.g., p < 0.05), what counts as a clinical event, and the overall sample size.The article also addresses the importance of understanding the fragility of study results and provide insights into how FI can be used to assess the reliability of clinical trial outcomes.
Tune in to learn more about the Fragility Index and its application in medical research.
Biostatistics articles on the INS website
The Fragility Index article