Need help evaluating a PCA

[dairfaron]

So I did a principal component analysis with Promax rotation on questionnaire data (4-step likert-type scale) and now have my rotated component matrix (5 components). KMO is >.7 and Bartlett is 0.

I want to compare my results to another study (that used the same questionnaire) in which they somehow calculated a mean value and standard deviation for each of the factors, but didn't say how they did it.
Ths may be a dumb question, but how do I calculate that factor mean and standard deviation from my factor loadings? I know that factor loadings are somewhat of an estimate for the individual factor-item-corellation, but I really don't know what to do with that information. I have been searching an answer to that for several hours but can't find a satisfying solution.

As a bonus question: I have some cross-loadings in my rotated component matrix, but those have a difference of >.2. Do I need to take those cross-loadings into account when doing whatever calculation is needed (see above)?

 

[staassis]

how do I calculate that factor mean and standard deviation from my factor loadings?

You do not. Factor loadings (if using the traditional definition) tell you how to represent the original variables in terms of factors. They do not tell you the reverse: how to calculate factors in terms of the original variables. The easiest approach is saving the factor scores (in SPSS, R, wherever) and calculating various statistics on those.

I know, some literature references use "factor loadings" in an unconventional sense. But this cannot be said about most statistical packages.