This is the numerical result the researchers used to make their “ridiculous” assumptions in their paper:

The ANOVA procedure for repeated measurement designs yield significant results for the

• dACC (Wilk’s Λ = 0.33, F = 4.59, p <.027, η2 = 0.67)
• rACC (Wilk’s Λ= 0.19, F = 9.55, p <.003, η2 = 0.81)
• amygdala (Wilk’s Λ = 0.28, F = 5.75, p<.014, η2 = 0.72)

Tests for linear trends were significant in the three ROIs:

• dACC: F = 8.28, p < .014;
• rACC: F = 17.97, p < .001;
• amygdala: F = 30.02, p < .001

but not for higher order trends

The other study they mention does not involve any experiment and is merely a review of other studies.

Whether the significance in the study is significant for science is up to the researchers but, yeah, we can make assumptions with a sample size of just 13. Interestingly, others would regard “too many” people in a sample size as a manipulation to achieve significance. So I guess that when we don’t like something we can always find reasons to complain about it.

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