Hi,
> On the other hand, this sounds like paying very little attention to
> statistics, doesn't it? Transposing this approach to behavioral data,
> it sounds to me like simply looking at histograms and saying "Well,
> guys, this bar seems a little bit different/similar from that one, so
> let's say that there is/isn't a difference".
Thanks for bringing this up - this issue is really central to the
argument. The comparison to behavioral data is apt, because what you
are suggesting is that we simply do not show the (e.g) reaction times
for tests that did not pass the significance level. Let's say we have
two tasks A and B, compared to control. A passes significance at
p=0.05, B doesn't p=0.04. It could very easily be that B has even has
a higher effect size than A. It seems to me very misleading to report
'A is significant' without 'B is very close to A'. The continuous map
provides this information in a rather compact way.
Best,
Matthew
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