I have a couple of questions involving doing a regression (logistic or linear) after principal component analysis.
If I find principal components using Principal component analysis, can I use these components like regular variables to be used in linear and logistic regression?
If not, do I have to perform an extra step like "rotate" the principal components? What is this "rotation", what is it actually doing, and why is it helpful for using in regression? (this is what happens in factor analysis, no?)
If I can use these components, rotated or not, can I simply setup the model and bind it with the outcome data? Do I need to transform the outcome data in any way? Or can I use the original outcome data with the principal components?