Every story and comment from the Hacker News API, in a layout borrowed from 2001.
A comment on When Data Is Missing, Scientists Guess. Then Guess Again. Parent comment
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).
There are no comments on this comment yet.
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).