Thanks for the insights. I will see how it does imputing all at once
first.
Regards,
James
On Tue, Sep 14, 2010 at 08:36:55AM -0400, Matt Blackwell wrote:
Hi James,
A few thoughts. If the truck length variables changes over time, then
you can impute it along with the counts in the same Amelia run. If
there is no empirical time dependence, then Amelia will not use time
to impute the truck lengths.
As for the truly missing truck lengths. You can always go back into
your imputed data and manually code those as missing. R code would
look something like:
a.out <- amelia(***your call here***)
for (i in 1:length(a.out$imputations)) {
mask <- a.out$imputations[[i]]$count == 0
is.na(a.out$imputations[[i]]) <- mask
}
You'll want to double check that it works (I haven't tested it). The
reason why this will work is that the imputed cell has not added any
information to the data itself, it has only added the information from
the observed values of the cell. Thus, omitting that observation from
the imputation entirely would bias the imputation.
I hope that helps.
Cheers,
matt.