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.