Certainly no Nazi. However, his issue is that he is apparently unable to distinguish between main effects of populations and diversity effects (this is an interaction). They are saying the outcome is explained by the main effects, not the interactions.
-
This Tweet is unavailable.
-
-
Replying to @KirkegaardEmil @exigentFacts
So, e.g. areas with lots of blacks are (generally) poor/crime prone/low trust because there's more blacks and blacks are poor/criminal/low trust. It's not the mixture of people per se, but their relative proportions. Different causal mechanism.
0 replies 0 retweets 1 like -
This Tweet is unavailable.
-
Replying to @exigentFacts
It's easy, you just include both the interactions and the main effects and see which predicts what. See here for an example of US counties. Racial diversity is associated with worse outcomes, until one adds the main effects and IQ. http://rpubs.com/EmilOWK/racial_homogeneity_study_2017 …
1 reply 0 retweets 1 like -
Replying to @KirkegaardEmil @exigentFacts
The key to understanding it is that a given area can have high diversity for multiple reasons. An area with a 50-50 White-Asian split has high diversity, but is not expected to perform poorly because composite groups perform well.
1 reply 0 retweets 0 likes
Compare with an area with 50-50-Black-Hispanic mix. This will perform poorly because the constituent groups do so, but it has the exact same amount of diversity as the 50-50 White-Asian one. Statistically, thus, one can work out which predicts what.
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.