On Sun, 14 Dec 2003, Douglas Trainor wrote:
Somewhere along the line, you have been confused.
You're in good company though. Factor analysis and PCA are different entities entirely.
Not in SPSS, where the same command is used for both (although we were not told anything like enough about what was done).
*However* I don't know what is meant by `pca in R'. Standard R contains princomp() and prcomp() to do PCA: it appears that pca() is in the orphaned package multiv. Why not use the standard functions? Also, those non-default arguments would appear to be very unusual indeed for PCA, and do not correspond to a *correlation* matrix.
It looks like the original poster might have used the pca() in the pcurve package, which seems to require a data matrix, not a correlation matrix.
Any clues about this diference?
User error looks likely. Please seek out local statistical expertise.
Dear listmates, i've done a pca analisys in R (1.8 v.) with the command
pca(Matrix, cent=FALSE, scle=FALSE)
I have obtained a v matrix very different from the component matrix resulted by a factor analysis in SPSS, unrotated and with a extraction from a correlation matrix. Any clues about this diference?
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