The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Missing-Data Adjustments in Large Surveys
Abstract
Useful properties of a general-purpose imputation method for numerical data are suggested and discussed in the context of several large government surveys. Imputation based on predictive mean matching is proposed as a useful extension of methods in existing practice, and versions of the method are presented for unit nonresponse and item nonresponse with a general pattern of missingness. Extensions of the method to provide multiple imputations are also considered. Pros and cons of weighting adjustments are discussed, and weighting-based analogs to predictive mean matching are outlined.
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Citations
Cites
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
Cited by
mice: Multivariate Imputation by Chained Equations in R
Buuren, S. V., & Groothuis-Oudshoorn, K. (2011) · Journal of Statistical Software · doi:10.18637/jss.v045.i03 · Cited by 13,870
“pmm() implements predictive mean matching (Little 1988), a general purpose semi-parametric imputation method.”
BackgroundMethodInfluentialMultiple imputation using chained equations: Issues and guidance for practice
White, I. R., Royston, P., & Wood, A. M. (2011) · Statistics in Medicine · doi:10.1002/sim.4067 · Cited by 9,792
Multiple imputation after 18+ years
Rubin, D. B. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476908 · Cited by 4,072
Multiple imputation of discrete and continuous data by fully conditional specification
van Buuren, S. (2007) · Statistical Methods in Medical Research · doi:10.1177/0962280206074463 · Cited by 2,827
Unützer, J., Katon, W., Callahan, C. M., Williams, Jr., Hunkeler, E., Harpole, L., Hoffing, M., Della Penna, R. D., Noël, P. H., Lin, E. H. B., et al. (2002) · JAMA · doi:10.1001/jama.288.22.2836 · Cited by 2,405
Metadata
- Authors
- Little, R. J. A.
- Venue
- Journal of Business & Economic Statistics
- Publisher
- Informa UK Limited
- Published
- 1988-07
- Volume
- 6
- Issue
- 3
- Pages
- 287-296
- ISSN
- 0735-0015 (ISSN-L)
- 1537-2707
- OpenAlex
- W1972851018
- Cited by
- 1,101
- References
- 2
- FWCI
- 2.19
- Type
- journal article
- Language
- en
- Open access
- closed
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- Little, R. J. A. (1988). Missing-Data Adjustments in Large Surveys. Journal of Business & Economic Statistics. https://doi.org/10.1080/07350015.1988.10509663
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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