Hello:
I am working with a stratified survey dataset with sampling weights
and I want to use multiple imputation to help with missingness.
1. Is there a way to run an ordered logistic regression using both a
multiply imputed dataset (i.e. from mice) and adjust for the survey
characteristics using the weight variable? The Zelig package is able
to do binary logistic regressions for survey data and handle the
missing data (logit.survey) but I could not find a way to do both for
an ordered logistic model.
2. I assume I should use the weights in the process of creating the
multiply imputed datasets as well. Is there a way to do so in any of
the multiple imputation packages in R?
Thanks so much
Thomas Soehl
---
Department of Sociology - UCLA
Los Angeles, CA 90095
[EMAIL PROTECTED]
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