I'm trying to run overimputation as a diagnostic on a large data set with
20 multiple imputations from Amelia. The overimputation diagnostic on one
variable takes a long time to complete (more than 2 weeks). Is there any
way to expedite the overimputation procedure? For example, would using the
subset argument to select a subset of cases expedite the procedure? If so,
how would one use the subset argument? I tried using a vector of
TRUEs/FALSEs to indicate whether to keep a row, but I received an error.
Any suggestions for expediting overimpute and/or using the subset argument
of overimpute() would be very helpful.
Thanks!
-Isaac
I have a question about the appropriateness of using Amelia to impute
some data for items that were not asked in earlier years of a survey.
I'm working with a governmental survey collection that started in 1975
and continues up to the present day. The data are in long form arranged
by state and year. My question is that certain items were not asked in
the earlier years that are asked now. Is appropriate to impute the data
for these earlier years? Initially, I planned to develop multiple
datasets to maximize years and states, but I started thinking this may
be an imputation issue as well.
Best regards,
Matthew
