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Analysis of Variance of Multiply Imputed Data
Open accessAbstract
As a procedure for handling missing data, Multiple imputation consists of estimating the missing data multiple times to create several complete versions of an incomplete data set. All these data sets are analyzed by the same statistical procedure, and the results are pooled for interpretation. So far, no explicit rules for pooling F tests of (repeated-measures) analysis of variance have been defined. In this article we outline the appropriate procedure for the results of analysis of variance (ANOVA) for multiply imputed data sets. It involves both reformulation of the ANOVA model as a regression model using effect coding of the predictors and applying already existing combination rules for regression models. The proposed procedure is illustrated using 3 example data sets. The pooled results of these 3 examples provide plausible F and p values.
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“Missing values were handled by multivariate multiple imputation using Rubin’s method.26”
From Aerobic, resistance, or combined exercise training and cardiovascular risk profile in overweight or obese adults: the CardioRACE trial (2024) · cites this paper as [26]
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“as no consensus on how to best pool F statistics was available [34].”
From An Internet-Based Cognitive Behavioral Therapy Program Adapted to Patients With Cardiovascular Disease and Depression: Randomized Controlled Trial (2019) · cites this paper as [34]
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Citations
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Cited by
Sorted by citations
Rebutting Existing Misconceptions About Multiple Imputation as a Method for Handling Missing Data
van Ginkel, J. R., Linting, M., Rippe, R. C. A., & van der Voort, A. (2019) · Journal of Personality Assessment · doi:10.1080/00223891.2018.1530680 · Cited by 553
“…are less user-friendly than the automatic pooling by SPSS. Additionally, the paper promoting the SPSS macro for pooling the results of ANOVA (Van Ginkel & Kroonenberg, 2014a) has been misquoted by many authors, suggesting that combination rules for ANOVA are either not available or too…”
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MethodInfluential
Metadata
- Authors
- van Ginkel, J. R., & Kroonenberg, P. M.
- Affiliations
- Leiden University
- Leiden University (NL)
- Venue
- Multivariate Behavioral Research
- Publisher
- Informa UK Limited
- Published
- 2014-01
- Volume
- 49
- Issue
- 1
- Pages
- 78-91
- ISSN
- 0027-3171 (ISSN-L)
- 1532-7906
- PMC
- PMC4029775
- OpenAlex
- W2155931297
- Cited by
- 152
- References
- 33
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 11 · 2023: 12 · 2022: 12 · 2021: 13 · 2020: 13 · 2019: 17 · 2018: 16 · 2017: 20 · 2016: 12 · 2015: 5 · 2014: 5
- FWCI
- 14.80
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Multivariate Behavioral Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (R01AG008235)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- multiple imputation, analysis of variance, missing data, repeated measures ANOVA
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