--- On Sat, 11/7/09, Victor Mauricio Herrera wrote:
> I am working with a pool of surveys and I want to impute
> missing values in the pooled dataset while keeping the
> design variables and re-calculated weights. Here is my
> question: Is it correct to impute missing values - and used
> them during the analysis - for variables that were not
> originally measured in some of the surveys? For example,
> waist circumference was not measured in all the surveys,
> however, since that variable must be included in the
> imputation model all individuals in the pooled dataset end
> up with a value for that variable.
In general I like this approach; this way you can also use
the information available in surveys that only asked some
of the questions. In practice getting a good imputation
model can take quite a bit of puzzling. In particular
trying to incorporate characteristics of the surveys can
become quite tricky. If you need a reference of someone
who has done this before see (Gelman, King, and Liu 1998),
though their exact imputation model has not been implemented
in Stata.
Hope this helps,
Maarten
Andrew Gelman; Gary King; Chuanhai Liu (1998) Not Asked and
Not Answered: Multiple Imputation for Multiple Surveys.
Journal of the American Statistical Association,
93(443):846-857.
http://www.stat.columbia.edu/~gelman/research/published/gelmankingliu.pdf
-----------------------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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