forget the weighting. that's not important or needed for imputation, the
only purpose of which is to predict. but if the weights or their
components can help you predict, then include them.
on quadratics, if they are strong, then include the squared term. same for
interactions. but amelia won't know about x and x^2 and so after Amelia,
take the x and square it and replace the x^2 that was imputed. same for
the interactions. this is a hack, but it is a reasonable one.
Gary
On Wednesday, September 12, 2012, Andrew Stokes wrote:
Dear Listserve,
I'm not sure whether to include features of survey design (clustering,
stratification, sampling weights) and features of survival analysis
(follow-up times and the failure indicator) in the imputation model.
With regard to features of survey design, the answer seems to be yes,
based on the information in Footnote 18 in King et al. (APSR 2001).
However, the footnote only addresses how to handle strata (using
dummies) and I've not seen this mentioned elsewhere.
Also, I have a quadratic transformation of a variable in my analysis
model as well as an interaction between two variables. The variables
underlying the quadratic transformation and interaction need to be
imputed. Is it correct that the quadratic and interaction terms should
be in the imputation model also?
Thanks very much for your help.
Andrew
Upenn
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