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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
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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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