Reframing the fragility index as bias analysis: sensitivity analysis, P-values, parameterizations, and confidence...

Area of Science:

• Biostatistics
• Epidemiology
• Statistical Significance

Background:

• The fragility index is commonly used to assess the sensitivity of p-values to changes in event counts.
• Statistical significance derived from p-values can often be unreliable or 'fragile'.

Purpose of the Study:

• To propose an alternative interpretation of the fragility index.
• To reframe the fragility index as a sensitivity or bias analysis for misclassification.
• To clarify the relevance of fragility index analogues for survival data.

Main Methods:

• Conceptual reframing of the fragility index.
• Comparative analysis of fragility index analogues for survival data.

Main Results:

• The fragility index can be interpreted as a bias analysis for specific types of misclassification.
• This reframing clarifies the comparative relevance of different fragility index versions for survival data.
• The proposed interpretation moves beyond dichotomous interpretations of p-value thresholds.

Conclusions:

• The fragility index offers valuable insights into the robustness of statistical significance.
• Reframing the fragility index as bias analysis enhances its utility in epidemiological research.
• This approach supports a more nuanced understanding of statistical findings, particularly in survival analysis.