Single imputation is garbage for accurate inference, as it reduces variance and thus confidence intervals as P(missing) increases.
MI is a useful method for alleviating this bias (though at the cost of a lot more compute).
That's why it gets used, and it's performed extremely well in real world analyses for basically my entire life (and I'm middle-aged now).
> especially in the unsupervised context.
I wouldn't use MI in an unsupervised context (but maybe some people do).
Single imputation is garbage for accurate inference, as it reduces variance and thus confidence intervals as P(missing) increases.
MI is a useful method for alleviating this bias (though at the cost of a lot more compute).
That's why it gets used, and it's performed extremely well in real world analyses for basically my entire life (and I'm middle-aged now).
> especially in the unsupervised context.
I wouldn't use MI in an unsupervised context (but maybe some people do).