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
soehl@ucla.edu




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