A latent factor is an unobserved coordinate introduced to explain shared variation among measurements. In an orthogonal factor model, latent factors have variance one and are mutually uncorrelated, with coefficients specified by the factor loadings. They differ from a regression factor, which is a categorical predictor. A fitted covariance alone generally leaves the latent factor orientation undetermined; factor rotation gives equivalent representations.
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