The other options for the method here is “Principal axis factoring” (which is closer to traditional factor analysis) and “Maximum likelihood” ( source for screenshot and SPSS interface). To put the (apparent) PCA method as a sub-section of factor analysis is misleading at best, and straight-up erronious at worst.
This screen shows up when you click Analyze -> Dimension Reduction -> Factor, which then opens a window called “Factor Analysis: Extraction” which lets you pick “Principal components” as a method. A few of my colleagues who use SPSS showed me the following screen:
I was inspired to write some of this down through some confusion caused in the lab by SPSS’ apparent dual usage of the term “factor analysis” and “principal components”.
This is just a very quick blog post outlining some of the commonalities and differences between factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA).
