Lightnews — Scholar-powered news

Reposted by krichard12

Julia M. Rohrer

@dingdingpeng.the100.ci

New paper out with @boryslaw.bsky.social 🥳 In which we sketch out how to rethink measurement invariance causally for applied researchers. And provide a causal definition of measurement invariance!

www.sciencedirect.com/science/arti...

Rethinking measurement invariance causally

Highlights:
It is preferable to work with a causal definition of measurement invariance
A violation of measurement invariance is a potentially substantively interesting observation
Standard tests for measurement invariance rely on strong assumptions
Group differences can be thought of as descriptive results

Conceptual graph illustration the central points of the manuscript. A group variable is potentiall connected to a construct of interest which affects items. Measurement invariance is violated if the group variable directly affects the items, for example by modifying the loadings from the construct to the items, or by directly affecting an item

To make this less abstract, consider a scenario where students take an exam, R, meant to capture some ability, T, and then are admitted to a program, V, depending on their exam results: R → V. This is sufficient to result in a violation of the statistical definition of measurement invariance. Exam results and admission are not independent given ability because exam results have a direct effect on admission. Even if we know somebody’s ability (e.g., we know it’s very high), learning about their admission status (e.g., they were not admitted) can tell us something about their exam result (e.g., it may have been worse than expected). According to the causal definition, this in itself does not constitute measurement bias, which seems a sensible conclusion here. After all, the scenario does not involve any reason to believe that the measurement process varied systematically by admission status. Admission happens after the exams took place, it cannot retroactively influence the measurement process (and, for example, lead to unfair treatment depending on admission status).

September 11, 2025 at 9:11 AM

Reposted by krichard12

Eric Turkheimer

@ent3c.bsky.social

My Dobzhansky lecture at BGA: "Theodosius Dobzhansky and the Origins of Radical Behavior Genetics" is publicly available. I talk about the tensions introduced into the field at the difficult border between science using model organisms and human beings. Thanks to BGA for the opportunity.

Sat_208_Dobzhansky_Lecture

Dobzhansky Lecture by Eric Turkheimer

vimeo.com

August 18, 2025 at 2:14 PM

Reposted by krichard12

John Holbein

@johnholbein1.bsky.social

Look at what happens to student test scores (top panel) and home values (bottom panel) when school bonds are authorized (red line).

August 4, 2025 at 9:45 PM

Reposted by krichard12

Eric Turkheimer

@ent3c.bsky.social

Excellent takedown of Nucleus Embryo by Arthur Caplan and James Tabery. The problem with Nucleus isn't eugenics. It is rescued from its own eugenic intentions by the fact that it won't work. It is bogus science.

No, You Can’t Design Your Baby—And Trying Would Be a Terrible Idea

A genomics firm saying they can help parents with “genetic optimization” of their embryos is tone-deaf Silicon Valley marketing trampling over legitimate science. Parents should be wary

www.scientificamerican.com

July 31, 2025 at 2:57 PM

krichard12

@krichard12.bsky.social

""So, to be clear, using the statistical basis of factor analysis we now conclude “There is not a g factor, there never was a g factor, and we can demonstrate this with anyone’s data”"

(page 16)

krichard12.com/docs/McArdle...

July 25, 2025 at 9:32 PM

Reposted by krichard12

Eric Turkheimer

@ent3c.bsky.social

A few additional interesting points about Jordan Lasker. One, he appled to work as a graduate student in my lab years ago:

bsky.app/profile/ent3...

capitolhunters @capitolhunters.bsky.social · Jul 4

The saga of the NYT's anti-Mamdani story taken from notorious white supremacist Jordan Lasker (they call him an "academic") gets even more amazing: Lasker's only impactful paper, which claimed white people are smarter, is infamous: it misused data so badly it got his tenured co-author fired. 2/

July 4, 2025 at 12:33 PM

Reposted by krichard12

Eric Turkheimer

@ent3c.bsky.social

Took me a while, but here is my response to Michel's challenge regarding their new GWAS of the five factor model. I trust it is sufficiently grumpy....

June 4, 2025 at 3:23 PM