Factor analysis

Summary

Factor analysis models many observed variables as linear combinations of a few unobserved common factors plus a noise term specific to each variable. It is a latent variable model that explains the correlations between the observed variables through the shared factors. The model implies that the covariance matrix is a low-rank matrix plus a diagonal matrix. It is widely used in psychology and the social sciences.