Hi Matt,
Basically what I want to do is a post estimation type command. I want to
first impute all the missing values and then use the model to calculate
theoretical 'imputed' values for the complete cases. However, I only want
m imputed values for each complete case - not hundreds or thousands of
values.
What does *overimp *do exactly? How is it different from the *overimpute*
command? There is also something in the documentation called
*overvalues. *Could
you clarify each of these?
So far I have found Amelia very fast and easy to use - looking forward to
the updated version :)
Rgds,
On Sat, Nov 15, 2014 at 3:53 AM, Matt Blackwell <mblackwell(a)gov.harvard.edu>
wrote:
Hi Mil,
I'm not sure I know what you want to do. Do you want to do a leave-one-out
approach and overimpute each individual cell at a time? Or do you want to
overimpute all the data at the same time. The latter isn't possible since
there wouldn't be any data to impute.
A overimputation one-at-a-time strategy could be done, but you'd have to
rerun Amelia each time with overimp set differently each time. Note that
there is a bug in amelia on CRAN right now that makes overimp sometimes not
work. This should be fixed in the next version of Amelia, to be sent to
CRAN in the next few days.
Hope that helps!
Cheers,
Matt
On Thu Nov 13 2014 at 10:13:47 PM Mil Jacobs <mil(a)miljacobs.com.au> wrote:
I would like to calculate imputed values for the
cases that are complete
in my data set but I am not sure how to do this.
I do not want thousands of overimputations, just one imputed value for
each complete case in each imputed data set (in the same way as for the
missing cases). How do I do this? I have tried using 'overimp' with the
'amelia' command but it is not working.
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