Multiple imputation of missing data with skip-pattern covariates : a comparison of alternative strategies
Multiple imputation (MI) is a widely used approach to address missing data issues in surveys. Variables included in MI can have various distributional forms with different degrees of missingness. However, when variables with missing data contain skip patterns (i.e. questions not applicable to some s...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | Journal of statistical computation and simulation. - 1999. - 94(2023), 7 vom: 30., Seite 1543-1570
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| 1. Verfasser: |
Zhang, Guangyu
(VerfasserIn) |
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| Weitere Verfasser: |
He, Yulei,
Cai, Bill,
Moriarity, Chris,
Shin, Hee-Choon,
Parsons, Van,
Irimata, Katherine E |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | Journal of statistical computation and simulation
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| Schlagworte: | Journal Article
Multiple imputation
RANDS survey
missing skip-pattern variables |
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