Hi all,

I have a set of variables that have missing values, which I am attempting to impute using MICE. As seems common, it's difficult to get the model to run, particularly because some mlogit models are slow to converge even with the augment option. We've considered a two-step procedure, where in the first step we run mi impute on a subset of variables (say, X1) with missing data, and in the second step we impute values for a second set (X2), using X1 as right had side variables. Intuitively this seems wrong to me, because the X1 values would be treated as known in the second model, but we're wondering if the "add" option would appropriately account for this by, for example, using the initial imputed data sets as a starting place.

Is it valid to impute values for X1 and then use those as right hand side variables in a second imputation? Forgive me if I've missed this in the generally thorough MI documentation. I should also say that I'm far from an MI expert so forgive as well my ignorance on the topic!

Best,
Paul