Dear all,
I've got a bit of a challenge on my hands. I've got survey data produced by
a government agency for which I want to use the person-weights in my
analyses. This is best accomplished by specifying weights in {survey} and
then calculating descriptive statistics/models through functions in that
package.
However, there is also missingness in this data that I'd like to handle
with imputation via {mi}. To properly use imputed datasets in regression,
they need to be pooled using the lm.mi function in {mi}. However, I can't
figure out how to carry out a regression on data that is properly weighted
that has also had its missing values imputed, because both packages use
their own mutually incompatible data objects. Does anyone have any thoughts
on this? I've done a lot of reading and I'm not really seeing anything on
point.
Thanks in advance!
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