ArticleCureus2023
The Robustness Index: Going Beyond Statistical Significance by Quantifying Fragility.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Enhancing Preclinical Rigor: Evaluating Robustness and Numerical Stability in a Chronic Pancreatitis Mouse Model.Annals of the New York Academy of Sciences · 2026Article
- Robustness Assessment of Oncology Dose-Finding Trials Using the Modified Fragility Index.Cancers · 2024Article
- Online haemodiafiltration and all-cause mortality: how fragile are the results of the studies published so far?Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.