Effects of Age and Processing Speed on Tilt Are Primarily Linear and Additive, Not Nonlinear and Multiplicative

IQ Research
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A new article written by Thomas Coyle and published in ICA Journal provides more information about how personal strengths and weaknesses in academic abilities develop.

Article 1
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Using archival data, Coyle examined “tilt,” which is the relative strength someone has in either technical or academic abilities, or in math vs. language. Previous research had already shown that tilt increases through adolescence, meaning that the difference between a person’s strengths and their weaknesses grew larger over time. The question is whether this change is a linear effect, or whether the magnitude of tilt increased with age and processing speed levels (i.e., had nonlinear effects).

The results indicated that effects were mostly linear, indicating that changes in tilt are mostly consistent from one age to another or from one processing speed level to another. However, there were some interesting exceptions:

Processing speed had a non-linear effect on math and verbal tilt (pictured below), indicating that a faster mental speed facilitates building these academic abilities. There was also a weak age non-linear effect, but it is much weaker.

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This paper provides more evidence for the importance of considering test subscores in addition to global scores (like IQ). Because tilt is not related to IQ, it has unique predictive power and can provide insights that overall scores cannot.

Link to original post: https://x.com/RiotIQ/status/1987930214698008879?s=20
Full article (no paywall): https://doi.org/10.65550/001c.146460

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The linear additivity finding is actually reassuring from a developmental perspective - it suggests tilt development follows predictable trajectories rather than chaotic nonlinear patterns. But those quadratic speed effects on academic tilt are genuinely interesting. Faster processing speed disproportionately amplifies academic strengths, which aligns with investment theories about how cognitive resources get allocated. The fact that this survives g controls is notable - it’s not just “smarter people get better at everything,” it’s something specific about speed enabling skill differentiation.

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This is solid evidence for why we need to look beyond full-scale scores. The speed-tilt relationship being nonlinear (especially for academic abilities) suggests processing speed acts as a multiplier for skill acquisition in school-valued domains. The weakness of age effects is surprising though - I’d have expected stronger developmental interactions. The practical implication: faster processors don’t just learn more, they develop more pronounced strengths, which has real consequences for how we think about gifted education and intervention timing.