The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Working With Missing Values
Open accessAbstract
Less than optimum strategies for missing values can produce biased estimates, distorted statistical power, and invalid conclusions. After reviewing traditional approaches (listwise, pairwise, and mean substitution), selected alternatives are covered including single imputation, multiple imputation, and full information maximum likelihood estimation. The effects of missing values are illustrated for a linear model, and a series of recommendations is provided. When missing values cannot be avoided, multiple imputation and full information methods offer substantial improvements over traditional approaches. Selected results using SPSS, NORM, Stata (mvis/micombine), and M plus are included as is a table of available software and an appendix with examples of programs for Stata and M plus.
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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
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
Cohen, P., Cohen, P., West, S. G., & Aiken, L. S. (2014) · Psychology Press eBooks · doi:10.4324/9781410606266 · Cited by 20,737
Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
Statistical Analysis With Missing Data
Lahiff, M., Little, R. J. A., & Rubin, D. B. (1989) · Journal of the American Statistical Association · doi:10.2307/2289883 · Cited by 17,265
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
Kemp, F. (2003) · Journal of the Royal Statistical Society: Series D (The Statistician) · doi:10.1046/j.1467-9884.2003.t01-2-00383_4.x · Cited by 9,293
Statistical Analysis with Missing Data
Little, R. J. A., & Rubin, D. B. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/9781119013563 · Cited by 8,473
Analysis of Incomplete Multivariate Data
Schafer, J. L. (1997) · doi:10.1201/9781439821862 · Cited by 6,012
Analysis of Incomplete Multivariate Data
Booth, D. E. (2000) · Technometrics · doi:10.1080/00401706.2000.10486013 · Cited by 5,627
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences.
Fong, G. T., Cohen, J., & Cohen, P. (1985) · Journal of the American Statistical Association · doi:10.2307/2287930 · Cited by 4,475
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
Cited by
Best practices for missing data management in counseling psychology
Schlomer, G. L., Bauman, S., & Card, N. A. (2010) · Journal of Counseling Psychology · doi:10.1037/a0018082 · Cited by 1,835
The prevention and handling of the missing data
Kang, H. (2013) · Korean Journal of Anesthesiology · doi:10.4097/kjae.2013.64.5.402 · Cited by 1,728
Ponitz, C. C., McClelland, M. M., Matthews, J. S., & Morrison, F. J. (2009) · Developmental Psychology · doi:10.1037/a0015365 · Cited by 934
Touch your toes! Developing a direct measure of behavioral regulation in early childhood.
Cameron Ponitz, C. E., McClelland, M. M., Jewkes, A. M., Connor, C. M., Farris, C. L., & Morrison, F. J. (2008) · Early Childhood Research Quarterly · doi:10.1016/j.ecresq.2007.01.004 · Cited by 635
Leerkes, E. M., Blankson, A. N., & O’Brien, M. (2009) · Child Development · doi:10.1111/j.1467-8624.2009.01296.x · Cited by 471
Metadata
- Authors
- Acock, A. C.
- Venue
- Journal of Marriage and Family
- Publisher
- Wiley
- Published
- 2005-09-20
- Volume
- 67
- Issue
- 4
- Pages
- 1012-1028
- ISSN
- 0022-2445 (ISSN-L)
- 1741-3737
- OpenAlex
- W2164788271
- Cited by
- 1,766
- References
- 31
- FWCI
- 33.71
- Type
- journal article
- Language
- en
- Open access
- bronze
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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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