Contents
What does Oblimin mean?
Abstract. Oblimin rotation is a general form for obtaining oblique rotations used to transform vectors associated with principal component analysis or factor analysis to simple structure.
Why do we use factor rotation?
Rotations minimize the complexity of the factor loadings to make the structure simpler to interpret. Factor loading matrices are not unique, for any solution involving two or more factors there are an infinite number of orientations of the factors that explain the original data equally well.
What is the difference between varimax and oblimin rotations?
Varimax returns factors that are orthogonal; Oblimin allows the factors to not be orthogonal. Ideally, we would like factors that load “all or nothing” on the original variables as in “Questions 1 – 5 of the survey all relate to attitudes to authority; questions 6-10 all relate to a sense of justice”.
How is varimax rotation used in factor analysis?
Varimax rotation is a statistical technique used at one level of factor analysis as an attempt to clarify the relationship among factors. Generally, the process involves adjusting the coordinates of data that result from a principal components analysis. The adjustment, or rotation, is intended to maximize the variance shared among items.
Equamax (rarely, Equimax) orthogonal rotation can be seen as a method sharpening some properties of varimax. It was invented in attempts to further improve it. Equa lization refers to a special weighting which Saunders (1962) introduced into a working formula of the algorithm. Equamax self-adjusts for the number of the being rotated factors.
What does varimax do to the loading matrix?
Varimax directly “simplifies” columns of the loading matrix and by that it greatly facilitates the interpretability of factors. On the loading plot, points are spread wide along a factor axis and tend to polarize themselves into near-zero and far-from-zero.