Hi Stuart,
Probably the most straightforward way to do this would be to apply PCA to
each of the imputed data sets and then use those in whatever analysis
models you want. As an alternative, you could use the stacked dataset of
all imputation (see my earlier email) and run PCA giving each of the rows
of the stacked data (1/m) weight where m is the number of imputed datasets.
This would ensure that all of the imputed data sets use the same factor
loadings.
Cheers,
Matt
~~~~~~~~~~~
Matthew Blackwell
Associate Professor of Government
Harvard University
url:
http://www.mattblackwell.org
On Fri, Oct 9, 2020 at 10:38 PM <stuart.reece(a)bigpond.com> wrote:
Hi Amelia Users.
I was wondering if anyone would advise how I can add principal components
to imputed datasets – and how to correctly combine them from all the
imputations ???
I was not able to find anything on this online….
Thanks so much,
Stuart Reece.