From the epistemological point of view, criticism of statistical significance here is based on questioning a criterion that is stipulated, i.e., defined arbitrarily.
Doing so gives formalization and modeling a greater importance than advancing understanding. That is unscientific.
A pragmatic approach is more appropriate than a strictly formal one, especially as an institutional norm.
Formal rigor is a necessary condition but not a sufficient one. Don't lose the forest for the trees.
The quest for knowledge is the quest for a consensual world view based on reasoning and evidence. This is based on many inputs and their consilience within the framework. This is an ongoing enterprise and science is not the only contributor to it. But science based on naturalism is a very significant contributor, tethering knowledge to logical pedigree and empirical warrant.
Statistical Modeling, Causal Inference, and Social Science
Alan Sokal’s comments on “Abandon Statistical Significance”
Andrew Gelman | Professor of Statistics and Political Science and Director of the Applied Statistics Center, Columbia University
Also
true economics
Ambiguity Fun: Perceptions of Rationality?Constantin Gurdgiev | chairman of the Ireland-Russia Business Association, contributor and former editor of Business & Finance Magazine, and lecturer in Finance with Trinity College, Dublin
