Abstract
To disconfirm or not to disconfirm: a null prediction vs. no prediction
Highlights
As a researcher who reads journal articles, a journal reviewer, and a journal editor, I have lost track of the countless times I have encountered a particular type of scenario
When factors that are not included in the theory, but are included in the new paradigm, cause a statistically significant effect to occur, it is true that the theory “cannot account for the data.”
Suppose a researcher uses an experimental paradigm where participants are bribed with money to be aggressive in the experimental condition but are not bribed in the control condition
Summary
As a researcher who reads journal articles, a journal reviewer, and a journal editor, I have lost track of the countless times I have encountered a particular type of scenario. An author obtains a statistically significant finding, points out that a particular theory fails to predict that finding, and argues that the finding disconfirms the theory. The first possibility is that the theory contains one or more propositions that, combined with reasonable auxiliary assumptions, really does lead to a particular prediction, whether of a result in a particular direction or a null effect.
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