Explained variance measures for multilevel models
Open accessAbstract
One challenge in using multilevel models is determining how to report the amount of explained variance. In multilevel models, explained variance can be reported for each level or for the total model. Existing measures have been based primarily on the reduction of variance components across models. However, these measures have not been reported consistently because they have some undesirable properties. The present study is one of the first to evaluate the accuracy of these measures using Monte Carlo simulations. In addition, a measure based on the full partitioning of variance in multilevel models was examined. With the exception of the Level 2 explained variance measure, all other measures performed well across our simulated conditions.
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There are issues quantifying explained variance in multilevel models.
“Given the issues quantifying explained variance in multilevel models (86, 87)”
From Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data (2021) · cites this paper as [87]
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- Authors
- LaHuis, D. M., Hartman, M. J., Hakoyama, S., & Clark, P. C.
- Affiliations
- Wright State University (US)
- Corresponding author
- LaHuis, David M.
- ORCID
- LaHuis, David M.
- Venue
- Organizational Research Methods
- Publisher
- SAGE Publications
- Published
- 2014-07-24
- Volume
- 17
- Issue
- 4
- Pages
- 433-451
- ISSN
- 1094-4281 (ISSN-L)
- 1552-7425
- OpenAlex
- W2155655748
- Cited by
- 239
- References
- 32
- Citations by year
- 2026: 16 · 2025: 18 · 2024: 20 · 2023: 30 · 2022: 30 · 2021: 23 · 2020: 18 · 2019: 20 · 2018: 21 · 2017: 21 · 2016: 12 · 2015: 9 · 2014: 1
- FWCI
- 15.13
- Type
- journal article
- Language
- en
- Open access
- Locations
- Organizational Research Methods (publishedVersion)
- Journal of Bioresource Management (submittedVersion, cc-by)
- 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 › Reliability and Agreement in Measurement
- Keywords
- explained variance, multilevel models, variance partitioning, variance components, measurement accuracy, Monte Carlo simulation
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