there's 2 perspectives on this: one yes, and one no. Over time, some of the same people have taken each of the two positions!
If we think of the data as drawn from a given joint distribution, then its best to impute all the variables together. If instead, we're focused on a causal inference then some think that its best to not impute the outcome variable with the others. The first is more efficient; the latter is not biased, but its conceivable that a researcher could fool themselves by tweaking the imputation model to (perhaps inadvertently) favor themselves.
Gary--
Gary King - Albert
J. Weatherhead III University Professor - Director, IQSS -
Harvard University