There are people who desperately want this to be untrue🧵
One example of this came up earlier this year, when a "Professor of Public Policy and Governance" accused other people of being ignorant about SAT scores because, he alleged, high schools predicted college grades better.
The thread in question was, ironically, full of irrelevant points that seemed intended to mislead, accompanied by very obvious statistical errors.
For example, one post in it received a Community Note for conditioning on a collider.
But let's ignore the obvious things. I want to focus on this one: the idea that high schools explain more of student achievement than SATs
The evidence for this? The increase in R^2 going from a model without to a model with high school fixed effects
This interpretation is bad.
The R^2 of the overall model did not increase because high schools are more important determinants of student achievement. This result cannot be interpreted to mean that your zip code is more important than your gumption and effort in school.
If we open the report, we see this:
Students from elite high schools and from disadvantaged ones receive similar results when it comes to SATs predicting achievement. If high schools really explained a lot, this wouldn't be the case.
What we're seeing is a case where R^2 was misinterpreted.
The reason the model R^2 blew up was because there's a fixed effect for every high school mentioned in this national-level dataset
That means that all the little differences between high schools are controlled—a lot of variation!—so the model is overfit, explaining the high R^2
This professor should've known better for many reasons.
For example, we know there's more variation between classrooms than between school districts when it comes to student achievement.
At every age, the incidence of dementia is down. As a society, people are no longer suffering dementia nearly as often!
The world over, child mortality is way down. It's unusual for parents to experience the death of a child these days, where even a century ago, it was the global norm.
Each year, novel gene therapies are approved.
The number of gene therapies in the pipeline is also rapidly increasing. There is tons of progress to be made here, and the main issue is regulatory.
We have lots of low-hanging fruit in curing disease!
There's a common type of misunderstanding that sounds like this:
"If taller people tend to be more educated, and women tend to be shorter than men, how do you explain women tending to be more educated?"
The issue has to do with intercepts. Consider this plot:
You can see that, among Whites, women tend to be shorter than men, and they tend to have lower earnings.
But at the same time, to similar degrees in both sexes, taller people tend to have higher earnings.
Perplexed? You shouldn't be.
The fact is that there's more to this that differentiates men and women than height, so the intercept for women is shifted down, even though the slopes of the height * income relationship are fairly comparable.
Debate about the value of essays in college admissions missed a key point:
Essays are biased, so should not be used.
Here's an example: High-income people know 'what to write' to look good to raters, so they outperform on essays relative to their other qualifications.
This shows up by race, too, and that's why admissions departments use essays to infer race for the express purpose of discriminating.
Write that you're Black; that you grew up as a poor immigrant; that you're gay or a cripple.
The reason essays do not have a role to play in the admissions process is because they're biased. It's plain, it's simple, it doesn't need to be discussed any further.
And here's some good policy: Use tools that are not biased or lose public funding.
Happy Autism Awareness Day! I think too many people are 'aware' of autism.
Have you ever met someone who claims to be autistic, but they've never been diagnosed?
Self-reported autism spectrum disorder (ASD) is practically uncorrelated with real, clinician-diagnosed autism🧵
Sort self-reporters into those with high and low ASD scores, and you get the bars on the left. The "high-trait" self-reporters look like people with diagnosed autism (ASD column).
But they're more socially anxious (middle) and avoidant (right).
So far, the means of distinguishing diagnosed from self-reported autistics have been crude.
To get a more nuanced understanding of their differences, we have to look at behavior.
For that, we'll start with the social control task.