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Missing Observations in Multivariate Statistics I. Review of the Literature
Abstract
In this paper we review the literature on the problem of handling multivariate data with observations missing on some or all of the variables under study. We examine the ways that statisticians have devised to estimate means, variances, correlations and linear regression functions from such data and refer to specific computer programs for carrying out the estimation. We show how the estimation problems can be simplified if the missing data follows certain patterns. Finally, we outline the statistical properties of the various estimators.
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Citations
Cites
Robust estimation of a location parameter
Huber, P. J. (1964) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177703732 · Cited by 7,228
Cited by
RUBIN, D. B. (1976) · Biometrika · doi:10.1093/biomet/63.3.581 · Cited by 9,925
Niehaves, B., & Plattfaut, R. (2014) · European Journal of Information Systems · doi:10.1057/ejis.2013.19 · Cited by 347
Incomplete Data in Generalized Linear Models
Ibrahim, J. G. (1990) · Journal of the American Statistical Association · doi:10.1080/01621459.1990.10474938 · Cited by 344
Structural Factor Analysis Experiments with Incomplete Data
McArdle, J. J. (1994) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr2904_5 · Cited by 198
Handling Missing Data in the Modeling of Intensive Longitudinal Data
Ji, L., Chow, S.-M., Schermerhorn, A. C., Jacobson, N. C., & Cummings, E. M. (2018) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1080/10705511.2017.1417046 · Cited by 74
Metadata
- Authors
- Afifi, A. A., & Elashoff, R. M.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1966-09
- Volume
- 61
- Issue
- 315
- Pages
- 595-604
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2017464775
- Cited by
- 306
- References
- 1
- FWCI
- 8.35
- Type
- journal article
- Language
- en
- Open access
- closed
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- Afifi, A. A., & Elashoff, R. M. (1966). Missing Observations in Multivariate Statistics I. Review of the Literature. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1966.10480891
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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.
