I wish they actually engaged with this issue instead of writing a fluff piece. There are plenty of problems with multiple imputation.
Not the least of which is that it's far too easy to do the equivalent of p hacking and get your data to be significant by playing games with how you do the imputation. Garbage in, garbage out.
I think all of these methods should be abolished from the curriculum entirely. When I review papers in the ML/AI I automatically reject any paper or dataset that uses imputation.
This is all a consequence of the terrible statics used in most fields. Bayesian methods don't need to do this.
Not the least of which is that it's far too easy to do the equivalent of p hacking and get your data to be significant by playing games with how you do the imputation. Garbage in, garbage out.
I think all of these methods should be abolished from the curriculum entirely. When I review papers in the ML/AI I automatically reject any paper or dataset that uses imputation.
This is all a consequence of the terrible statics used in most fields. Bayesian methods don't need to do this.