Factor Analysis
Factor analysis is a mathematical and statistical technique for analyzing differences among units of analysis and the structure of relationships among variables assessing those units. The units of analysis may be persons, groups, organizations, ecological units, or any other justifiable basis of aggregation although persons are most often the focus of analysis. The chief purpose of the method is the attainment of scientific parsimony, which is achieved by positing a set of latent common factors that underlie the data. The factor model was developed by Charles Spearman (1904a, 1927) to be used to describe economically the correlations among mental test scores observed for persons. Spearman's famous bi-factor model of intelligence held that measures of mental abilities had two major sources: a factor common to all measures of ability, which he called the g-factor (factor of general ability), and a specific component of variation (an s-factor) unique to the test. For example, a test of numerical ability may be affected in part by a general factor of intelligence as well as a factor specific to numerical aptitude. This model, although never the predominant psychological theory of mental tests, has persisted in the culture in the sense that people often believe there is a general factor of intelligence underlying performance across different domains (see Gould 1981 for a critique of this view).
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