Cited by 11,638Statistical Methods and Bayesian InferencePsychometric Methodologies and TestingMeta-analysis and systematic reviews

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Missing data: our view of the state of the art

Schafer, Joseph L., Graham, John W.·2002·Psychological Methods

DOI 10.1037/1082-989x.7.2.147

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Abstract

Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missing-data problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random (MAR) concept. They summarize the evidence against older procedures and, with few exceptions, discourage their use. They present, in both technical and practical language, 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI). Newer developments are discussed, including some for dealing with missing data that are not MAR. Although not yet in the mainstream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art.

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Authors: Schafer, J. L., & Graham, J. W.
Affiliations: Pennsylvania State University (US)
Venue: Psychological Methods
Publisher: American Psychological Association (APA)
Published: 2002
Volume: 7
Issue: 2
Pages: 147-177
ISSN: 1082-989X (ISSN-L)
1939-1463
DOI: 10.1037/1082-989x.7.2.147
OpenAlex: W2156267802
Semantic Scholar: f867e56d3a8ac2bbef6bfe5c74ee80ab43239718
Cited by: 11,638
References: 107
Citations by year: 2026: 438 · 2025: 485 · 2024: 449 · 2023: 466 · 2022: 510 · 2021: 635 · 2020: 621 · 2019: 655 · 2018: 614 · 2017: 697 · 2016: 693 · 2015: 712 · 2014: 701 · 2013: 686 · 2012: 604
FWCI: 113.09
Type: journal article
Language: en
Open access: closed
Locations: Psychological Methods (publishedVersion)
PubMed (publishedVersion)
Funders: National Institute on Drug Abuse (P50DA010075, 1-P50-DA10075)
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
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords: missing data, missing at random, maximum likelihood estimation, missing data mechanisms, statistical practice, survey data analysis
MeSH terms: Humans, Models, Theoretical, Research, Software, Databases as Topic

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