Synthetic Multiple-Imputation Procedure for Multistage Compl…
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- DOI 10.1515/jos-2016-0011
- PMID https://pubmed.ncbi.nlm.nih.gov/28781418
- PMCID https://www.ncbi.nlm.nih.gov/pmc/articles/5542708
- OpenAlex ID W2317956608
- Type Article
- Language EN
- Published 01 Mar 2016
- Volume 32 (1)
- Pages 231–256
- Source Journal of Official Statistics
- Publisher De Gruyter Open
- FWCI 2.36
- Countries 1
- Institutions 3
- Added 24 Jun 2016
- Updated 28 Oct 2026
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Synthetic Multiple-Imputation Procedure for Multistage Complex Samples
Article 2016 EN Diamond
Abstract Multiple imputation (MI) is commonly used when item-level missing data are present. However, MI requires that survey design information be built into the imputation models. For multistage stratified clustered designs, this requires dummy variables to represent strata as well as primary sampling units (PSUs) nested within each stratum in the imputation model. Such a modeling strategy is no…
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3
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3 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Hanzhi Zhou | Mathematica Policy Research (US) | — |
| 2 | Michael R. Elliott | University of Michigan (US) Institute for Social Research (US) | |
| 3 | Trivellore E. Raghunathan | University of Michigan (US) Institute for Social Research (US) |
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