Hi, I am also doing PCA. Is the following right for extracting the scores? library(psych) pca<-principal(data,nfactors=,rotate="varimax",scores=T) pca$loadings pca$score Best regards, He
On Tue, Nov 30, 2010 at 10:22 AM, Liviu Andronic <landronimirc at gmail.com> wrote:
Dear all
I'm unable to find an example of extracting the rotated scores of a
principal components analysis. I can do this easily for the un-rotated
version.
data(mtcars)
.PC <- princomp(~am+carb+cyl+disp+drat+gear+hp+mpg, cor=TRUE, data=mtcars)
unclass(loadings(.PC)) ?# component loadings
summary(.PC) # proportions of variance
mtcars$PC1 <- .PC$scores[,1] # extract un-rotated scores of 1st
principal component
mtcars$PC2 <- .PC$scores[,2] # extract un-rotated scores of 2nd
principal component
head(mtcars[, c('PC1', 'PC2')])
However, I no longer understand how to do so if I want to use
?principal in 'psych' and any of the GPArotation methods. For example,
require(psych)
r <- cor(mtcars[,c("am","carb","cyl","disp","drat","gear","hp","mpg")])
pca <- principal(r, nfactors = 8, residuals = T, rotate="none") # or
'varimax' or any other GPArotation supported rotation
pca
I've turned the 'pca' object and ?principal help page upside down and
I still cannot find anything that would resemble a 'scores' value. I'm
pretty sure it's one matrix computation away, but I cannot find which
one.
Ideas? Thank you
Liviu
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