Rotation Types in Exploratory Factor Analysis
Rotation causes factor loadings to be more clearly differentiated, which is often necessary to facilitate interpretation. Several types of rotation are available for your use.
Orthogonal
Varimax (most common)
- minimizes number of variables with extreme loadings (high or low) on a factor
- makes it possible to identify a variable with a factor
Quartimax
- minimizes the number of factors needed to explain each variable
- tends to generate a general factor on which most variables load with medium to high values
- not very helpful for research
Equimax
- combination of Varimax and Quartimax
Oblique
The variables are assessed for the unique relationship between each factor and the variables (removing relationships that are shared by multiple factors).
Direct oblimin (DO)
- factors are allowed to be correlated
- diminished interpretability
Promax (Use this one if you’re not sure)
- computationally faster than DO
- used for large datasets
