I know another one like this, but too much ADHD to write the numbers down. But, fixed effect of gender too large.
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Replying to @KirkegaardEmil @ArtirKel
I mean: what is the male/female d for crying? Definitely not below 0.5, more like 1 to 1.5, no?
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Replying to @KirkegaardEmil
https://books.google.co.uk/books?hl=es&lr=&id=tS1C8Sl5ysEC&oi=fnd&pg=PA143&dq=crying+gender+difference+cohen&ots=gjslxBq397&sig=3BiNYcnbys2rpvzFm34-PQ20O4E&redir_esc=y#v=onepage&q=crying%20gender%20difference%20cohen&f=false … So 1.4(+-0.4) for males 5.3(+-0.4) for females, so even larger
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Replying to @ArtirKel
These may be standard errors or confidence intervals, not SDs.
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Replying to @KirkegaardEmil
I know. But I'm not curious enough to go to the original paper to see and get d's out of it. But I bet d>1.8 here.
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Replying to @ArtirKel @KirkegaardEmil
(Is Cohen's d defined or does it make sense to use when the distribution is obviously non-normal?)
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Replying to @ArtirKel
The general term is SMD: standardized mean difference. Choose any measures of central tendency and dispersion you like.
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Replying to @KirkegaardEmil
I think I'll update my Cohen-d post with that: what to do if the distribution looks suspiciously multimodal
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Replying to @KirkegaardEmil
It's in your github, kirkegaard R package, right?
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Open Science gods will smite you, unless you also make sure it works in Octave. ;) https://github.com/Deleetdk/kirkegaard/blob/master/R/statistics.R#L663 …
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Replying to @KirkegaardEmil
Octave can cope with vectorised operations, substraction and division, I guess.
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