The role of hypothesis testing, and especially of p-values, in evaluating the results of scientific experiments has been under debate for a long time. At least since the influential article by Ioannidis (
2005
) awareness is growing in the scientific community that the results of many research experiments are difficult or impossible to replicate. Often, the (mis-)use of hypothesis testing is blamed for the lack of replicability. In 2016, the American Statistical Association (ASA) published a "Statement on Statistical Significance and p-Values" (Wasserstein and Lazar
2016
), which led to continued scientific engagement and discussions. In this editorial, we summarize recent discussions on hypothesis testing, p-values and decision making, particularly in biopharmaceutical research, and share our views on these issues.
Reference Type
Journal Article
Periodical Full
Statistics in biopharmaceutical research
Publication Year
2021
Publication Date
Feb 19,
Volume
13
Issue
1
Start Page
1
Other Pages
5
Publisher
Taylor & Francis
ISSN/ISBN
1946-6315
Document Object Index
10.1080/19466315.2021.1874803
URL
http://www.tandfonline.com/doi/abs/10.1080/19466315.2021.1874803