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Re: st: PCA and rotation


From   "Michael I. Lichter" <mlichter@buffalo.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: PCA and rotation
Date   Wed, 23 Dec 2009 13:46:46 -0500

Thanks Jay and Nick for your helpful comments and references.

If I can continue beating this poor, dead horse just a little longer ... Back in August, Nick described his method of "disposable principal component analysis" (see list of steps below), which he concluded with "discard PC results and proceed with modeling." Clearly, he wouldn't have done the PCA if it didn't guide his modeling in some way. Does he use it to determine which variables to retain in his model and which to discard? Just curious.

-ml
I've found occasional use of PCA in the following way. 1. Plot the data. 2. Calculate correlations, etc. 3. Look at the results: get some ideas. 4. Calculate PCs. 5. Use PCs to help structure understanding of #1 and #2 in terms of
variables that go together, variables that are singletons, etc.
Sometimes, results of #1 and #2 now make more sense in their own terms.
(For example, a reordering of a scatter plot matrix or correlation
matrix makes it easier to see what is going on.) Often it is useful here
to look at a table of correlations between original variables and new
PCs. -cpcorr- from SSC helps with that. 6. Now discard PC results and proceed with modelling.
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