Specification Perturbation Measures Fragility, Not Robustness: Preserving the p–fr–nb Distinction

Abstract

The fragility index is increasingly recognized as insufficient for evaluating clinical trial evidence, and orthogonal companion metrics have been proposed across methodological traditions. A recent statistics preprint introduces Minimum Specification Perturbation as a robustness metric measuring how many analyst decisions must change to flip a confidence interval across zero. Under the Neutrality Boundary Framework's definitions, however, that construction is a fragility metric — a perturb-and-count algorithm that flips the significance classification, structurally analogous to the fragility index but in specification space rather than outcome space. The actual robustness axis is the geometric distance of the observed effect from the null parameter value, which is the role the Neutrality Boundary Framework occupies. Preserving the distinction between fragility and robustness preserves the orthogonality at the heart of the significance-fragility-robustness framework, the p-fr-nb triplet. This triplet of data analysis remains the foundation for complete statistical evidence in biomedical research.