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g, a Statistical Myth

Cosma Rohilla Shalizi · 18 Oct 2007

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Cosma Rohilla Shalizi did not write this page.

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  1. 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.
  2. Exploratory factor analysis being no good at discovering causal structure, it provides no support for the reality of g.
  3. Since that's about the only case which anyone does advance for g, however, which accords very poorly with other evidence, from neuroscience and cognitive psychology, about the structure of the mind, it is very hard for me to find any reason to believe in the importance of g, and many to reject it.
  4. There are a very narrow set of technical conditions which let you out of this, i.e., which let you combine group differences, measurement unbiasedness and predictive unbiasedness. (See Millsap's papers for details.) That IQ tests satisfy them is highly implausible, and, to say the least, empirically unsupported.

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