How do I go about calculating an index/score from principal component analysis?
Here is a reproducible example
set.seed(1)
dat <- data.frame(
Diet = sample(1:2),
Outcome1 = sample(1:10),
Outcome2 = sample(11:20),
Outcome3 = sample(21:30),
Response1 = sample(31:40),
Response2 = sample(41:50),
Response3 = sample(51:60)
)
ir.pca <- prcomp(dat[,3:5], center = TRUE, scale. = TRUE)
summary(ir.pca)
loadings <- ir.pca$rotation
scores <- ir.pca$x
correlations <- t(loadings)*ir.pca$sdev
This generates three principal components. Could I use these to calculate a score or an index called 'Response Index' for each row in the above data?
