I think we can also add an #aspredicted to this. ;) https://twitter.com/KirkegaardEmil/status/901943018760134660 … Predicted a total ~15 mins in advance it took me to write code!
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@fsnole1 Which way does causality run? Are dumber ppl more discriminated against, thus leading to more self reported discrimination?
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I.e. that ppl of lower IQ perhaps confirm negative stereotypes, and this results in worse treatment?
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It seems reasonable to explore IQ*race interaction, to this end.
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A reasonable counter-proposal. Results, however, are not very sensible.pic.twitter.com/shRuKbXdON
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The beta for IQ is somewhat stronger here, but p>a due the model having too little free variation to estimate precisely (large SEs).
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Ok, fair. But Im not sure this settles the question of direction of causality. That will perhaps require an additional study.
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It could be done using an experimental setup where subjects are given ambivalent info and asked whether they were discriminated against.
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Please note, "Asian" is such a wide range, and Hispanic is also. Why do these studies follow these arbitrary groupings?
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Old dataset.
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But you published it a week ago...?
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You seem unable to distinguish between a study and a dataset.
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Neuroticism, I think. Unfortunately, AH does not supply a quick measure of that. One has to build it from their items. Annoying.
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Also known as low GFP. ;)
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how was the data collected?
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thank you.
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Pseudo r², but yes. Not easy to predict this outcome using these predictors. Methinks neuroticism will be the stronger predictor.
Thanks. Twitter will use this to make your timeline better. UndoUndo
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