Some governments are using the pandemic as a smokescreen to eviscerate regulations. Meanwhile, deforestation is spiking along with COVID-19.
New Research In
Physical Sciences
Featured Portals
Articles by Topic
Biological Sciences
Featured Portals
Articles by Topic
Edited by Adrian E. Raftery, University of Washington, Seattle, WA, and approved October 9, 2013 (received for review July 18, 2013)
See related content:
Significance
The lack of reproducibility of scientific research undermines public confidence in science and leads to the misuse of resources when researchers attempt to replicate and extend fallacious research findings. Using recent developments in Bayesian hypothesis testing, a root cause of nonreproducibility is traced to the conduct of significance tests at inappropriately high levels of significance. Modifications of common standards of evidence are proposed to reduce the rate of nonreproducibility of scientific research by a factor of 5 or greater.
Abstract
Recent advances in Bayesian hypothesis testing have led to the development of uniformly most powerful Bayesian tests, which represent an objective, default class of Bayesian hypothesis tests that have the same rejection regions as classical significance tests. Based on the correspondence between these two classes of tests, it is possible to equate the size of classical hypothesis tests with evidence thresholds in Bayesian tests, and to equate P values with Bayes factors. An examination of these connections suggest that recent concerns over the lack of reproducibility of scientific studies can be attributed largely to the conduct of significance tests at unjustifiably high levels of significance. To correct this problem, evidence thresholds required for the declaration of a significant finding should be increased to 25–50:1, and to 100–200:1 for the declaration of a highly significant finding. In terms of classical hypothesis tests, these evidence standards mandate the conduct of tests at the 0.005 or 0.001 level of significance.
Footnotes
- ↵1E-mail: vjohnson{at}stat.tamu.edu.
Author contributions: V.E.J. designed research, performed research, contributed new reagents/analytic tools, analyzed data, and wrote the paper.
The author declares no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1313476110/-/DCSupplemental.
Freely available online through the PNAS open access option.
Revised standards for statistical evidence
Sign up for Article Alerts
Article Classifications
- Physical Sciences
- Statistics
Jump to section
You May Also be Interested in
Along with bragging rights, the nations that achieve exascale computing early will have a leg up in the scientific revolutions of the future.
Image credit: Flickr/Oak Ridge National Laboratory, licensed under CC BY 2.0.
NAS member Dalton Conley explains how the Vietnam War draft lotteries are a natural experiment for studying how military service affects life outcomes.
A study examines the demographic and evolutionary history of extinct and living lions.
Image credit: Pixabay/Sponchia.
Researchers examine how Atacama Desert microbes have adapted to parched environments and use rocks as a water source.
Image credit: Jocelyne DiRuggiero.