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.
“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]
No consensus was available on how to best pool F statistics.
“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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- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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