On Wed, 29 May 2002, Paul Warwick wrote:
I'm now able to generate the univariate means,
thanks to some help from
Mike Tomz.
I do have a larger question, though. Amelia doesn't like my data sets.
They consist of elite evaluations of party positions etc. in various
countries, so that each file has a small number of cases (between 10 and
18) and a large number of variables. (Incidentally, in the file I
experimented on, more variables were complete (no missing data) than Amelia
would allow me to specify!). Generally speaking, the files are about
55-70% valid data. Setting a prior as high as 1000 still failed,
apparently due to too much missing data. I can get a solution using SPSS's
MVA routine but, persuaded as always that EMis is better than EM, I'm
wondering if there are any other tricks I should try before giving up on
Amelia?
I'm not sure who to address this to, so I'm sending it to you with a copy
to Mike.
I'm planning to attend the summer meth. meeting in Seattle (just down the
road for me), so I imagine I'll see you there.
Regards,
Paul
Paul,
the best place to address questions like this is the Amelia Listserv
<amelia(a)latte.harvard.edu>du>; we all get copies.
The problem you're having is not specific to EMis. It is fundamental for
any method of imputation. With so few observations, you couldn't really
include many variables at all. This is true for EMis and essentially all
other approaches.
Since you seem to have a number of these small data sets, I would
suggest that you consider stacking them up. You might have to include
dummy variables (fixed effects) for the small data sets, but perhaps you
could get away without them. Its the same problem of a small n that
affects other research too; finding a way to borrow strength statistically
from other related data can greatly increase statistical power. Anyway,
it is worth a shot!
Best of luck and see you in Seattle,
Gary
: Gary King, King(a)Harvard.Edu
http://GKing.Harvard.Edu :
: Center for Basic Research Direct (617) 495-2027 :
: in the Social Sciences Assistant (617) 495-9271 :
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