Open AccessFragility Part I: a guide to understanding statistical power
Author(s) -
Madjarova Sophia J.,
Pareek Ayoosh,
Eckhardt Christina M.,
Khorana Arjun,
Kunze Kyle N.,
Ollivier Mattheu,
Karlsson Jón,
Williams Riley J.,
Nwachukwu Benedict U.
Publication year - 2022
Publication title -
knee surgery, sports traumatology, arthroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.806
H-Index - 125
eISSN - 1433-7347
pISSN - 0942-2056
DOI - 10.1007/s00167-022-07188-9
Subject(s) - fragility , statistical power , sample size determination , variance (accounting) , context (archaeology) , sample (material) , power (physics) , computer science , affect (linguistics) , data science , psychology , statistics , econometrics , mathematics , geography , economics , physics , accounting , archaeology , communication , quantum mechanics , thermodynamics
The aim of this paper is to close the knowledge‐to‐practice gap around statistical power. We demonstrate how four factors affect power: p value, effect size, sample size, and variance. This article further delves into the advantages and disadvantages of a priori versus post hoc power analyses, though we believe only understanding of the former is essential to addressing the present‐day issue of reproducibility in research. Upon reading this paper, physician–scientists should have expanded their arsenal of statistical tools and have the necessary context to understand statistical fragility.