The Robustness Index: Going Beyond Statistical Significance by Quantifying Fragility

Statistical significance is widely used to evaluate research findings but has limitations around reproducibility. Measures of statistical fragility aim to quantify robustness against violations of assumptions. However, dependence on sample size and single unit changes restricts indices like the unit fragility index and the fragility quotient. The Robustness Index (RI) is proposed to overcome these limitations and quantify fragility independently of the research study's sample size. The RI measures how altering sample size affects significance. For insignificant findings, the sample size is multiplied until significance is reached; the multiplicand is the RI. The sample size is divided for significant research findings until insignificance is reached; the divisor is the RI. Thus, higher RIs indicate greater robustness of insignificant and significant research findings. The RI provides a simple, interpretable metric of fragility. It facilitates comparisons across studies and can potentially increase trust in biomedical research