Incomplete data hinders statistical analysis
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missing dataQuanta Magazine
•When Data Is Missing, Scientists Guess. Then Guess Again. | Quanta Magazine
85% Informative
When data goes missing, standard statistical tools, like taking averages, are no longer useful.
In the 1970s , a statistician named Donald Rubin proposed a general technique to deal with missing data.
Rubin ’s approach, called multiple imputation, takes that chance of picking one of the best guesses into account.
Multiple imputation became the go-to technique in medicine in 2010 .
New software that uses machine learning has been able to impute more complicated data.
Some researchers still worry about the mathematical rigor of these new techniques and are more hesitant to adopt them.
For now, it seems that multiple imputation is here to stay.
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