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A comment on When Data Is Missing, Scientists Guess. Then Guess Again. Parent comment

Re:When Data Is Missing, Scientists Guess. Then Guess Again by CrazyStat on Sunday October 06, 2024 @12:28PM (#41758228)
EM can be used to impute data, but that would be single imputation. Multiple imputation as described here would not use EM since the goal is to get samples from a distribution of possible values for the missing data.
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Re:When Data Is Missing, Scientists Guess. Then Guess Again by wdkrnls on Sunday October 06, 2024 @04:53PM (#41760220)
In other words, EM makes more sense. All this imputation stuff seems to me more like an effort to keep using obsolete modeling techniques.
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Re:When Data Is Missing, Scientists Guess. Then Guess Again by CrazyStat on Sunday October 06, 2024 @07:30PM (#41761272)
Absolutely not.

EM imputation (or single imputation in general) fails to account for the uncertainty in imputed data. You end up with artificially inflated confidence in your results (p-values too small, confidence/credible intervals too narrow, etc.).

Multiple imputation is much better.

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