Factor analysis

The statistical technique used to identify latent variables (factors) that account for shared variance across observed measures. The mathematical foundation of all modern intelligence research. Applied to a battery of cognitive tests, factor analysis reliably extracts a single dominant factor (g) plus several secondary factors corresponding to broad abilities.

This term appears throughout the cognitive ability literature and across this site's articles. Understanding it is essential for interpreting any IQ score or cognitive subtest result. Modern psychometric textbooks (such as those by Anne Anastasi or Susan Embretson) cover the term in significant additional depth and document the empirical findings that justify its prominence in the field.

In the context of online IQ testing, the implications of this term are usually that the test-taker should be cautious about over-interpreting brief screener results. Most of the published precision claims for major IQ batteries do not transfer directly to short online instruments, and the relevant adjustments — wider confidence intervals, more conservative band assignments — are best made explicitly rather than ignored.

For further reading on this term, consult the related entries in this glossary and the deep-dive articles linked in the Related Reading section. The American Psychological Association's task force report 'Intelligence: Knowns and Unknowns' (1995) and its follow-ups remain the most authoritative summary at an accessible technical level.