Handling missing data in single-case studies
Open accessAbstract
Multiple imputation is illustrated for dealing with missing data in a published SCED study. Results were compared to those obtained from available data. Merits and issues of implementation are discussed. Recommendations are offered on primal/advanced readings, statistical software, and future research.
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Missing primary outcome data was handled using a multiple imputation approach.
“Missing primary outcome data was handled in line with recommendations by using a multiple imputation approach (Peng & Chen, 2018).”
From A single-case experimental evaluation of a new group-based intervention to enhance adjustment to life with acquired brain injury: VaLiANT (valued living after neurological trauma) (2022) · cites this paper as Peng & Chen, 2018
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- Authors
- Peng, C.-Y. J., & Chen, L.-T.
- Affiliations
- University of Nevada, Reno (US)
- Venue
- Journal of Modern Applied Statistical Methods
- Publisher
- Scilight Press Pty Ltd
- Published
- 2018-06-07
- Volume
- 17
- Issue
- 1
- ISSN
- 1538-9472 (ISSN-L)
- OpenAlex
- W2805387321
- Cited by
- 22
- References
- 16
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 3 · 2023: 3 · 2022: 4 · 2021: 5 · 2020: 1 · 2019: 3
- FWCI
- 1.87
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Journal of Modern Applied Statistical Methods (publishedVersion)
- Human Biology (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- missing data, single-case experimental design, multiple imputation, missing data imputation, statistical software
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