Editorial: Roles of Hypothesis Testing, p-Values and Decision Making in Biopharmaceutical Research

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.