The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Analyzing longitudinal data with missing values
Abstract
Missing data methodology has improved dramatically in recent years, and popular computer programs now offer a variety of sophisticated options. Despite the widespread availability of theoretically justified methods, researchers in many disciplines still rely on subpar strategies that either eliminate incomplete cases or impute the missing scores with a single set of replacement values. This article provides readers with a nontechnical overview of some key issues from the missing data literature and demonstrates several of the techniques that methodologists currently recommend. This article begins by describing Rubin's missing data mechanisms. After a brief discussion of popular ad hoc approaches, the article provides a more detailed description of five analytic approaches that have received considerable attention in the missing data literature: maximum likelihood estimation, multiple imputation, the selection model, the shared parameter model, and the pattern mixture model. Finally, a series of data analysis examples illustrate the application of these methods.
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“We used full information maximum likelihood with robust standard errors in Mplus. This is a superior strategy to listwise deletion and equivalent to using multiple imputation techniques when data are assumed to be missing at random (Enders, 2011).”
From Influences of victimization and comorbid conditions on latency to illicit drug use among adolescents and young adults (2020) · cites this paper as Enders, 2011
Citations
Cites
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Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
Hierarchical Linear Models: Applications and Data Analysis Methods.
Longford, N. T., Bryk, A. S., & Raudenbush, S. W. (1993) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2075823 · Cited by 18,773
Missing data: our view of the state of the art
Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638
Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence
Singer, J. D., & Willett, J. B. (2003) · doi:10.1093/acprof:oso/9780195152968.001.0001 · Cited by 10,647
RUBIN, D. B. (1976) · Biometrika · doi:10.1093/biomet/63.3.581 · Cited by 9,925
(2010) · Cited by 7,034
Self-citationAnalysis of Incomplete Multivariate Data
Booth, D. E., & Schafer, J. L. (2000) · Technometrics · doi:10.2307/1271466 · Cited by 5,627
(1976) · Annals of Economic and Social Measurement · Cited by 5,035
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Dealing With Missing Data in Developmental Research
Enders, C. K. (2013) · Child Development Perspectives · doi:10.1111/cdep.12008 · Cited by 330
Self-citationHandling Missing Values in Longitudinal Panel Data With Multiple Imputation
Young, R., & Johnson, D. R. (2015) · Journal of Marriage and the Family · doi:10.1111/jomf.12144 · Cited by 246
Hesser, H. (2015) · Internet Interventions · doi:10.1016/j.invent.2015.02.003 · Cited by 192
Kaushal, N., & Rhodes, R. E. (2014) · Preventive Medicine · doi:10.1016/j.ypmed.2014.07.026 · Cited by 175
Forbes, M. K., Fitzpatrick, S., Magson, N. R., & Rapee, R. M. (2018) · Journal of Youth and Adolescence · doi:10.1007/s10964-018-0922-6 · Cited by 179
Metadata
- Authors
- Enders, C. K.
- Affiliations
- Arizona State University (US)
- Corresponding author
- Enders, Craig K.
- ORCID
- Enders, Craig K.
- Venue
- Rehabilitation Psychology
- Published
- 2011
- Volume
- 56
- Issue
- 4
- Pages
- 267-288
- ISSN
- 0090-5550 (ISSN-L)
- 1939-1544
- OpenAlex
- W1970308312
- Cited by
- 321
- References
- 40
- Citations by year
- 2026: 29 · 2025: 17 · 2024: 26 · 2023: 24 · 2022: 23 · 2021: 39 · 2020: 30 · 2019: 22 · 2018: 23 · 2017: 25 · 2016: 15 · 2015: 22 · 2014: 14 · 2013: 10 · 2012: 1
- FWCI
- 7.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Rehabilitation Psychology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- missing data, longitudinal data, maximum likelihood estimation, multiple imputation, selection model, shared parameter models, pattern-mixture models, complete case analysis, missing data methods
- MeSH terms
- Data Interpretation, Statistical, Humans, Longitudinal Studies, Research Design, Likelihood Functions
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