The genetics of g and specific cognitive #CHC abilites. A must read. Includes a commentary rant directed at my fellow #schoolpsychologist #IQ test researchers

https://www.biorxiv.org/content/10.1101/2022.02.05.479237v1

The genetics of specific cognitive abilities
Francesca ProcopioQuan ZhouZiye WangAgnieska Gidziela 
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Kaili Rimfeld 
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Margherita MalanchiniRobert Plomin
doi: https://doi.org/10.1101/2022.02.05.479237 
This article is a preprint and has not been certified by peer review [what does this mean?].
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Abstract
Most research on individual differences in performance on tests of cognitive ability focuses on general cognitive ability (g), the highest level in the three-level Cattell-Horn-Carroll (CHC) hierarchical model of intelligence. About 50% of the variance of g is due to inherited DNA differences (heritability) which increases across development. Much less is known about the genetics of the middle level of the CHC model, which includes 16 broad factors such as fluid reasoning, processing speed, and quantitative knowledge. We provide a meta-analytic review of 863,041 monozygotic-dizygotic twin comparisons from 80 publications for these middle-level factors, which we refer to as specific cognitive abilities (SCA). Twin comparisons were available for 11 of the 16 CHC domains. The average heritability across all SCA is 55%, similar to the heritability of g. However, there is substantial differential heritability and the SCA do not show the dramatic developmental increase in heritability seen for g. We also investigated SCA independent of g (g-corrected SCA, which we refer to as SCA.g). A surprising finding is that SCA.g remain substantially heritable (53% on average), even though 25% of the variance of SCA that covaries with g has been removed. Our review frames expectations for genomic research that will use polygenic scores to predict SCA and SCA.g. Genome-wide association studies of SCA.g are needed to create polygenic scores that can predict SCA profiles of cognitive abilities and disabilities independent of g. These could be used to foster children’s cognitive strengths and minimise their weaknesses.

Blog masters comment.  Although there are constant critical battles re the relevance of intelligence testing and CHC theory in school psychology (my professional roots), many of the critics fail to recognize that intelligence theory and research is not owned by the small applied sandbox of school psychology.  Mainstream psychological researchers (i.e., serious scholars of intelligence research, cognitive psychologists, neuropsychologists, genetic psychologists, etc.) are finding tremendous value in using the CHC taxonomy to organize research, meta-analysis, and commentaries.  The use of the CHC taxonomy to organize research and literature reviews is one of the most important contributions of CHC theory.  I have repeatedly articulated the importance of this contribution in many publications since 1997…the most recent being my chapter with Joel Schneider in Contemporary Intellectual Assessment (4th edition).  I was pleased to see our contribution reflected in this current paper by the authors using one of our taxonomic organizations to ground their research.  The image is below, which is from our prior 2012 chapter.

What I find interesting is that many CHC specific cognitive abilities demonstrated significant heritabilities after g-heritability variance is statistically removed, and, the specific cognitive abilities do NOT show the same developmental heritability trend as g.  These findings, in part, are consistent with John Horn’s long standing arguement that psychometric g is just a statistical abstraction and that differential developmentalheritability, neurocognitive, and outcome relations evidence provides strong support for the validity of the broad CHC factors…with Horn going as far as saying g does not really exist as a real brain or biological based mechanism.  And, recent psychometric network-based theories (dynamic mutualism, wired intelligence, process overlap; brain network research) can account for the positive definite nature of correlation matrices (without involving a latent g variable), which, along with the failure to find a brain or biological based theoretical or psychological g despite over 100 years of research (“g is the Loch Ness Monster of Psychology”, McGrew, 2021) suggests that psychometric g is just that…a statistical abstraction.  The findings in this paper need to be “chewed on” by those SP IQ test structural researchers who seem to be “stuck on psychometric g”….I call them “g-centrists” (McGrew et al., 2022 manuscript in preparation).  

Yes, my fellow SP’s, our strong “staticism” dust-bowel empirical factor studies of IQ test batteries (often with the same blunt hammer every time…….bi-factor or EFA with SL orthogonalization; I was guilty of being similarly enamored with CFA as the ultimate “truth test” early in my career before I learned better, through my ongoing consultation and guidance by two important mentors—John Horn and especially Jack McArdle, who unfortunately passed away last week) are almost completely devoid of the integration of substantive mainstream research and theory.  Much of our structural research may be statistically strong….but it is substantively very weak and nearly void of substantive research and theory.  We are contributing to the theory crises in psychology (Fried, 2020), especially via the conflation of psychometric/statistical g with theoretical/psychological g.  Intelligence and IQ tests are not the sole property of SP…research on CHC and other theories of intelligence, and providing valid psychometric measures of these constructs, is important for moving all of psychologies (and related fields) intelligence-related theoretical research forward.  Thanks for letting me vent.  Click on images to enlarge.




Some findings.


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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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