This is a corollary of a phenomenon that has been documented by Daniel Kahneman that he calls, What You See is All There Is (WYSIATI). WYSIATI a cognitive bias that when presented with evidence, especially those that confirm your mental model, you do not question what evidence might be missing and you fill in the missing data with the easiest thing that comes to mind.
It would be more effort for readers of these articles to reason that the effect might be large, or small, and so they should not jump to conclusion, and the obvious conclusion is that the article would not have been written if the effect was small, so they would act as if the effect was large, unless told otherwise.
Also, we should keep in mind that articles written about a small effect, would not attract many readers, so new sources would be biased to no mention that the effect is small in order to get more clicks or readers.
Also, if the news source is biased to encourage the reader to advocate something, leaving out small effect information can be an intentional form of bias.
So for me the bottom line is, unless the article says the effect is large, assume it is small and you will be unlikely to be wrong in two ways. First, authors are unlikely to "forget" to mention that the effect is large, and even if they do, plenty of other people are likely to react anyway.
This is a corollary of a phenomenon that has been documented by Daniel Kahneman that he calls, What You See is All There Is (WYSIATI). WYSIATI a cognitive bias that when presented with evidence, especially those that confirm your mental model, you do not question what evidence might be missing and you fill in the missing data with the easiest thing that comes to mind.
It would be more effort for readers of these articles to reason that the effect might be large, or small, and so they should not jump to conclusion, and the obvious conclusion is that the article would not have been written if the effect was small, so they would act as if the effect was large, unless told otherwise.
Also, we should keep in mind that articles written about a small effect, would not attract many readers, so new sources would be biased to no mention that the effect is small in order to get more clicks or readers.
Also, if the news source is biased to encourage the reader to advocate something, leaving out small effect information can be an intentional form of bias.
Yep, all good points. 👍
So for me the bottom line is, unless the article says the effect is large, assume it is small and you will be unlikely to be wrong in two ways. First, authors are unlikely to "forget" to mention that the effect is large, and even if they do, plenty of other people are likely to react anyway.