what is the difference between principal component analysis and principal axis factoring?
Both are data reduction techniques—they allow you to capture the variance in variables in a smaller set. ... Despite all these similarities, there is a fundamental difference between them: PCA is a linear combination of variables; Factor Analysis is a measurement model of a latent variable.