g, a Statistical Myth

From Three-Toed Sloth: Slow Takes from the Canopy (My Very Own Internet Tradition)

Anyone who wanders into the bleak and monotonous desert of IQ and the nature-vs-nurture dispute eventually gets trapped in the especially arid question of what, if anything, g, the supposed general factor of intelligence, tells us about these matters. By calling g a “statistical myth” before, I made clear my conclusion, but none of my reasoning. This topic being what it is, I hardly expect this will change anyone’s mind, but I feel a duty to explain myself.

To summarize what follows below (“shorter sloth”, as it were), the case for g rests on a statistical technique, factor analysis, which works solely on correlations between tests. Factor analysis is handy for summarizing data, but can’t tell us where the correlations came from; it always says that there is a general factor whenever there are only positive correlations. The appearance of g is a trivial reflection of that correlation structure. A clear example, known since 1916, shows that factor analysis can give the appearance of a general factor when there are actually many thousands of completely independent and equally strong causes at work. Heritability doesn’t distinguish these alternatives either. Exploratory factor analysis being no good at discovering causal structure, it provides no support for the reality of g.

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