Error And The Growth Of Experimental Knowledge

By H. Freud. 2016

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Using Bayes to get the most out of non-significant results (2014, background): “…has no basis in Bayesian inference (a point value always has 0 probability on a standard credibility interval); correspondingly, such a rule is sensitive to factors that are inferentially irrelevant such as the stopping rule and intentions of the experimenter (Mayo, 1996; Dienes, 2008, 2011).”
Responsible Data Science (2017, background): “From an epistemological point of view, data-driven approaches follow the logic of the new experimentalism (Mayo 1996; Chalmers 2013) in which knowledge is derived from experimental observations, not theory.”
When Does HARKing Hurt? Identifying When Different Types of Undisclosed Post Hoc Hypothesizing Harm Scientific Progress (2017, background): “Putting the arguments about relatedness (Leung, 2011) and test severity (Mayo, 1991, 1996) together, it can be concluded that a priori hypotheses may be omitted from a research article without any harm to science when they are (a) unrelated to the final conclusions of that article and (b) the…”