varimax rotation
varimax rotation
VARIMAX(loadings, normalize = TRUE, verbose)
loadings |
A loading matrix. |
normalize |
Should Kaiser normalization be performed? If so the rows of x are re-scaled to unit length before rotation, and scaled back afterwards. Default = TRUE. |
verbose |
Should detailed results be displayed in console? TRUE (default) or FALSE |
This function uses the R built-in varimax function and provides additional output.
A list with the following elements:
loadingsNOROT |
The unrotated loadings |
loadingsV |
The varimax-rotated loadings |
rotmatV |
The rotation matrix |
eigenvar |
Eigenvalues and factor proportions of variance |
cormat_reproduced |
The reproduced correlation matrix, based on the rotated loadings |
Brian P. O'Connor
# the Harman (1967) correlation matrix PCAoutput <- PCA(data_Harman, Nfactors = 2, Ncases=305, rotate='none', verbose=TRUE) VARIMAX(PCAoutput$loadingsNOROT, verbose=TRUE) # Rosenberg Self-Esteem scale items PCAoutput <- PCA(data_RSE, corkind='polychoric', Nfactors = 2, rotate='none', verbose=TRUE) VARIMAX(PCAoutput$loadingsNOROT, verbose=TRUE) # NEO-PI-R scales PCAoutput <- PCA(data_NEOPIR, Nfactors = 5, rotate='none', verbose=TRUE) VARIMAX(PCAoutput$loadingsNOROT, verbose=TRUE)
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