The general formula for the estimand based on MI is not rational for
categorical variables. The average of multiply imputed categories provides
usually a decimal, not any particular category (if gender is missing, the
result may be between female and male). Hence, you have again to decide which
of these several imputed values to use as the finally imputed value. Or
otherwise, you have to build a new extended file with all imputed data sets
(pooled data set so that each sampling weight has been divided by the number of
imputations), and to estimate your final distribution from this data set. Or
are there other solutions? I really want to look various parameters (or their
estimates) including maximum values, minimum values, ... frequency
distributions, ..., not totals or means or regression coefficients.
Seppo
