The Fragility of Statistically Significant Findings From Randomized Trials in Sports Surgery: A Systematic Survey
Moin Khan; Nathan Evaniew; Mark Gichuru; Anthony Habib; Olufemi R. Ayeni; Asheesh Bedi; Michael Walsh; P.J. Devereaux · 2016 · The American Journal of Sports Medicine
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
BACKGROUND: High-quality, evidence-based orthopaedic care relies on the generation and translation of robust research evidence. The Fragility Index is a novel method for evaluating the robustness of statistically significant findings from…
Excerpt shown for reference under fair use — read the full paper at the publisher.
Hosted by the publisher — may require access.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Estimating the reproducibility of psychological science
Negative / Null Result ReportWillingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results
Methods Dead-EndComparing multiple comparisons: practical guidance for choosing the best multiple comparisons test
Replication FailureInferential Statistics as Descriptive Statistics: There Is No Replication Crisis if We Don’t Expect Replication
Negative / Null Result ReportMOBILE BANKING ADOPTION: APPLICATION OF DIFFUSION OF INNOVATION THEORY
Negative / Null Result ReportEnjoyment and social influence: predicting mobile payment adoption
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.1177/0363546516674469
