Hi Stuart,
Unfortunately, we don't have any code for implementing PCA with Amelia
output. I was more providing a high-level idea for how one could implement
this. If separate PCA analyses don't work, then maybe combine the data
first and then run PCA on the stacked data (weighting each row by 1/64).
Cheers,
Matt
~~~~~~~~~~~
Matthew Blackwell
Associate Professor of Government
Harvard University
url:
http://www.mattblackwell.org
On Mon, Oct 12, 2020 at 10:18 PM Dr Stuart Reece <asreece(a)bigpond.net.au>
wrote:
Thanks Matt.
Can you please provide code to work out the PCA in each imputed dataset???
Actually I went through and did this by hand in all 64 imputed datasets
(for 50% missing data) – and then the code for analyzing it would not work
at all….
Extremely frustrating….
I tried this with missMDA and factoMineR and PCA – but it only gave one
dataset at the end and the results were not robust….
But I really liked the Amelia framework and wanted to use it – but could
not make the code run after constructing PCA’s in each dataset as noted
earlier.
Thanks for your advice,
Stuart.
*From:* Matt Blackwell [mailto:mblackwell@gov.harvard.edu]
*Sent:* Tuesday, 13 October 2020 11:59 AM
*To:* stuart.reece(a)bigpond.com
*Cc:* amelia(a)lists.gking.harvard.edu; Gary King; James Honaker; Stuart
Reece
*Subject:* Re: Principal Components of Amelia Datasets
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
<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.mattblackwell.org&d=DwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=EwICq0J5pL8CwgEJz8qkmauGonk0XmiLpxcYOEgk2a0&m=HRfEfRt0wCg3vsJ-6lLyJ-lvGDIrVuuwI6qVFMJfB1Y&s=Hqrm_485evyxMzl6Z793owtmjs_6P9xc5EbAiTVZC4s&e=>
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.