What is the difference between orthogonal rotation and oblique rotation?

What is the difference between orthogonal rotation and oblique rotation?

Orthogonal and oblique are two different types of rotation methods used to analyze information from a factor analysis. Rotations where factors are not correlated are orthogonal. So rotation methods that are correlated are oblique while rotation of uncorrelated factors is orthogonal.

Which rotation should I use in factor analysis?

Promax Rotation . An oblique rotation, which allows factors to be correlated. This rotation can be calculated more quickly than a direct oblimin rotation, so it is useful for large datasets.

What is an oblique rotation?

Oblique rotations consist of successive arcs of longitude and latitude, which project as slopes (the tangent to a point on a curve).

What are oblique factors?

a transformational system used in factor analysis when two or more factors (i.e., latent variables) are correlated. Oblique rotation reorients the factors so that they fall closer to clusters of vectors representing manifest variables, thereby simplifying the mathematical description of the manifest variables.

How to use oblique rotation in EFA with SPSS?

Oblique Rotation in Exploratory Factor Analysis (EFA) with SPSS. The orthogonal factor model looks nice. However, many people (psychologists) believe that factors should correlate with each other. For example, several factors are extracted from a personality test. It would make more sense to assume that those factors are correlated.

What happens to factor loadings after oblique rotation?

If doing an orthogonal rotation, the rotated factor loadings will be collected in a matrix called Rotated Factor Matrix. But after an oblique rotation, we suddenly have as many as THREE matrices.

Is the assumption of orthogonality discarded in oblique rotation?

Here we mentioned that the assumption of orthogonality would be discarded when doing the oblique rotation. I’ll go with the direct oblimin method in the following example. Select the variables and do some mouse clicking. I highlighted some changes made to the default setting.

Why is orthogonal rotation used in exploratory factor analysis?

Conventional wisdom in the literature and many texts advise researchers to use orthogonal rotation because it produces more easily interpretable results, but this might be a flawed argument.