varimax rotation

The study ultimately yielded results through principal components factor analysis with varimax rotation.

A summary of the use of varimax rotation and of other types of factor rotation is presented in this article on factor analysis.

Only after creating this a priori organization of traits, the researchers performed, "an exploratory factor analysis of scale scores using varimax rotation," (p. 632) from which five factors emerged.

If these conditions hold, the factor loading matrix is said to have "simple structure," and varimax rotation brings the loading matrix closer to such simple structure (as much as the data allow).

In statistics, a varimax rotation is a change of coordinates used in principal component analysis and factor analysis that maximizes the sum of the variances of the squared loadings (squared correlations between variables and factors).

To avoid a loss of spectral properties (Plaut and Vautard 1994), they have introduced a slight modification of the common VARIMAX rotation that does take the spatio-temporal structure of ST-EOFs into account.

Varimax rotation is an orthogonal rotation of the factor axes to maximize the variance of the squared loadings of a factor (column) on all the variables (rows) in a factor matrix, which has the effect of differentiating the original variables by extracted factor.

In order to reduce mixture effects and to improve the physical interpretation, Groth and Ghil (2011) have proposed a subsequent VARIMAX rotation of the spatio-temporal EOFs (ST-EOFs) of the M-SSA.