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Unravelling factor analysis
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Factor analysis is a broad term that refers to a set of statistical methods used to detect underlying patterns in the relationships among a number of observed variables. Its origins were in the large scale studies defining the dimensions of intelligence pioneered by Thurstone.1 2 Factor analysis can appear complicated to the general reader but the main principle is relatively straightforward: what it aims to do is identify whether the correlations between a set of multiple observed variables are explicable or can be summarised in terms of a smaller number of underlying, latent, unobserved variables, also called factors. It is useful to have a basic understanding of the specific techniques when reading articles about factor analysis. There are two main approaches: exploratory factor analysis and confirmatory factor analysis.
Exploratory factor analysis is used for the preliminary investigation of a set of observed variables, especially where there are multiple variables, such as
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