Problems with the method of correlated vectors

The method of correlated vectors has been used widely to identify variables that are associated with general intelligence (g). Briefly, this method involves finding the correlation between the vector of intelligence subtests' g-loadings and the vector of those subtests' correlations with the variable in question. We describe two major problems with this method: first, associations of a variable with non-g sources of variance can produce a vector correlation of zero even when the variable is strongly associated with g; second, the g-loadings of subtests are highly sensitive to the nature of the other subtests in a battery, and a biased sample of subtests can cause a spurious correlation between the vectors.