hegemonicon comments on Open Thread: July 2010 - Less Wrong

6 Post author: komponisto 01 July 2010 09:20PM

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Comment author: hegemonicon 06 July 2010 05:14:17PM 5 points [-]

Poking around on Cosma Shalizi's website, I found this long, somewhat technical argument for why the general intelligence factor, g, doesn't exist.

The main thrust is that g is an artifact of hierarchal factor analysis, and that whenever you have groups of variables that have positive correlations between them, a general factor will always appear that explains a fair amount of the variance, whether it a actually exists or not.

I'm not convinced, mainly because it strikes me as unlikely that an error of this type would persist for so long, and that even his conception of intelligence as a large number of separate abilities would need some sort of high level selection and sequencing function. But neither of those are particularly compelling reasons for disagreement - can anyone more familiar with the psychological/statistical territory shed some light?

Comment author: hegemonicon 07 July 2010 02:54:46PM 10 points [-]

I pointed this out to my buddy who's a psychology doctoral student, his reply is below:

I don't know enough about g to say whether the people talking about it are falling prey to the general correlation between tests, but this phenomenon is pretty well-known to social science researchers.

I do know enough about CFA and EFA to tell you that this guy has an unreasonable boner for CFA. CFA doesn't test against truth, it tests against other models. Which means it only tells you whether the model you're looking at fits better than a comparator model. If that's a null model, that's not a particularly great line of analysis.

He pretty blatantly misrepresents this. And his criticisms of things like Big Five are pretty wild. Big Five, by its very nature, fits the correlations extremely well. The largest criticism of Big Five is that it's not theory-driven, but data-driven!

But my biggest beef has got to be him arguing that EFA is not a technique for determining causality. No shit. That is the very nature of EFA -- it's a technique for loading factors (which have no inherent "truth" to them by loading alone, and are highly subject to reification) in order to maximize variance explained. He doesn't need to argue this point for a million words. It's definitional.

So regardless of whether g exists or not, which I'm not really qualified to speak on, this guy is kind of a hugely misleading writer. MINUS FIVE SCIENCE POINTS TO HIM.

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