| pca {sjstats} | R Documentation |
...
pca(x)
pca_rotate(x, nf = NULL, rotation = c("varimax", "oblimin"))
x |
A data frame or a |
nf |
Number of components to extract. If |
rotation |
Rotation of the factor loadings. May be |
The print()-method for pca_rotate() has a
cutoff-argument, which is a scalar between 0 and 1, indicating
which (absolute) values from the loadings should be blank in the
output. By default, all loadings below .1 (or -.1) are not shown.
A tidy data frame with either all loadings of principal components
(for pca()) or a rotated loadings matrix (for pca_rotate()).
data(efc) # recveive first item of COPE-index scale start <- which(colnames(efc) == "c82cop1") # recveive last item of COPE-index scale end <- which(colnames(efc) == "c90cop9") # extract principal components pca(efc[, start:end]) # extract principal components, varimax-rotation. # number of components based on Kaiser-criteria pca_rotate(efc[, start:end])