The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Multiple imputation for missing data†‡
Abstract
Missing data occur frequently in survey and longitudinal research. Incomplete data are problematic, particularly in the presence of substantial absent information or systematic nonresponse patterns. Listwise deletion and mean imputation are the most common techniques to reconcile missing data. However, more recent techniques may improve parameter estimates, standard errors, and test statistics. The purpose of this article is to review the problems associated with missing data, options for handling missing data, and recent multiple imputation methods. It informs researchers' decisions about whether to delete or impute missing responses and the method best suited to doing so. An empirical investigation of AIDS care data outcomes illustrates the process of multiple imputation. © 2002 John Wiley & Sons, Res Nurs Health 25:76–84, 2002.
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Citations
Cites
Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
RUBIN, D. B. (1976) · Biometrika · doi:10.1093/biomet/63.3.581 · Cited by 9,925
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
Schafer, J. L. (1999) · Statistical Methods in Medical Research · doi:10.1177/096228029900800102 · Cited by 3,949
Cited by
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
Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks
Yoon, J., Zame, W. R., & van der Schaar, M. (2019) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2874712 · Cited by 341
Intention‐to‐treat in randomized controlled trials: Recommendations for a total trial strategy
Polit, D. F., & Gillespie, B. M. (2010) · Research in Nursing & Health · doi:10.1002/nur.20386 · Cited by 129
Heart rate variability and 24-hour minimum heart rate
Burr, R. L., Motzer, S. A., Chen, W., Cowan, M. J., Shulman, R. J., & Heitkemper, M. M. (2006) · Biological Research For Nursing · doi:10.1177/1099800405285268 · Cited by 22
Metadata
- Authors
- Patrician, P. A.
- Venue
- Research in Nursing & Health
- Publisher
- Wiley
- Published
- 2002-01-08
- Volume
- 25
- Issue
- 1
- Pages
- 76-84
- ISSN
- 0160-6891 (ISSN-L)
- 1098-240X
- OpenAlex
- W2094096650
- Cited by
- 207
- References
- 4
- FWCI
- 3.96
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
