Multiple imputation of missing data under missing at random: including a collider as an auxiliary variable in the imputation model can induce bias
Epidemiological studies often have missing data, which are commonly handled by multiple imputation (MI). In MI, in addition to those required for the substantive analysis, imputation models often include other variables (“auxiliary variables”). Auxiliary variables that predict the partially observed...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Epidemiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fepid.2023.1237447/full |