Hi William,
You can add missingness back into each imputed dataset using the
"transform()" function on the output. See section 4.9 of the Amelia
manual/vignette for more information.
Cheers,
Matt
~~~~~~~~~~~
Matthew Blackwell
Assistant Professor of Government
Harvard University
url:
http://www.mattblackwell.org
On Mon, Jul 27, 2015 at 1:53 PM William Johnston <wrj368(a)mail.harvard.edu>
wrote:
Hello,
Is it possible to tell Amelia to not impute in situations where
information is missing by design? For example, if the youngest cohort of
subjects has missing data for a variable that the older cohorts are
expected to have, is it possible to have Amelia only impute for the older
cohorts?
As an alternative I figure I can just impute the data that is missing by
design and then simply ignore it at the analysis stage, but I worry that
the imputation might be getting thrown off somehow.
Thanks,
WRJ
--
William R. Johnston
Postdoctoral Fellow | Harvard University
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