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“Thus, listwise deletion was used, because it is a reasonable choice for handling missing data under such circumstances, and other approaches such as imputation are only appropriate when data are reasonably assumed to be missing at random (MAR) or missing completely at random (MCAR) (Allison, 2002;Manly & Wells, 2015).”
From Competing hypotheses about online versus face-to-face course outcomes: Analysis leveraging the unique circumstances of the COVID-19 pandemic (2025) · cites this paper as Allison, 2002
In the citing paper
“The FIML-estimated models produced results that are highly similar to those produced by models estimated using listwise deletion, which suggests that listwise deletion does not produce substantially more biased estimates when the data are missing for predictor variables [51].”
From Poverty, Material Hardship, and Children’s Outcomes: A Nuanced Understanding of Material Hardship in Childhood (2022) · cites this paper as [51]
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Metadata
- Authors
- Allison, P.
- Corresponding author
- Allison, Paul
- Venue
- Sage eBooks
- Publisher
- SAGE Publications, Inc.
- Published
- 2002
- OpenAlex
- W4205701142
- Cited by
- 2,050
- References
- 0
- Citations by year
- 2026: 81 · 2025: 79 · 2024: 72 · 2023: 101 · 2022: 122 · 2021: 122 · 2020: 120 · 2019: 91 · 2018: 97 · 2017: 103 · 2016: 88 · 2015: 90 · 2014: 109 · 2013: 110 · 2012: 107
- FWCI
- 8.09
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Sage eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Keywords
- missing data
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