Eigenvalues or Explained Variance of Rotated Principal Components

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Hi, looking for a way of determining the explained variance of principal components following rotation (i.e. after appying rotatefactors function).
I have a dataset where the first 3 PCs explain >98% of the variance (approx 70, 20, and 8% per PC). To make them easier to interpret it is necessary to apply a varimax rotation (to first 3 PCs only). Clearly the total amount of explained variance across the 3 PCs will remain the same after rotation but it will be distributed very differently amongst them. In other programs (e.g. SPSS) the eigenvalues and explained variance of the rotated components is provided but in Matlab they are not.
Is there an easy way of extracting these values? Can the rotation matrix output from rotatefactors somehow be applied to the vector of unrotated eigenvalues to get the rotated eigenvalues?
Thanks for any help
  1 Comment
isiegler on 20 Nov 2017
Hi, I have exactly the same question! Does anyone have the answer?

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