The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
Understanding and estimating the power to detect cross-level interaction effects in multilevel modeling.
Abstract
Cross-level interaction effects lie at the heart of multilevel contingency and interactionism theories. Researchers have often lamented the difficulty of finding hypothesized cross-level interactions, and to date there has been no means by which the statistical power of such tests can be evaluated. We develop such a method and report results of a large-scale simulation study, verify its accuracy, and provide evidence regarding the relative importance of factors that affect the power to detect cross-level interactions. Our results indicate that the statistical power to detect cross-level interactions is determined primarily by the magnitude of the cross-level interaction, the standard deviation of lower level slopes, and the lower and upper level sample sizes. We provide a Monte Carlo tool that enables researchers to a priori design more efficient multilevel studies and provides a means by which they can better interpret potential explanations for nonsignificant results. We conclude with recommendations for how scholars might design future multilevel studies that will lead to more accurate inferences regarding the presence of cross-level interactions.
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Best-practice recommendations for defining, identifying, and handling outliers
Aguinis, H., Gottfredson, R. K., & Joo, H. (2013) · Organizational Research Methods · doi:10.1177/1094428112470848 · Cited by 1,341
Self-citationCorrelational effect size benchmarks
Bosco, F. A., Aguinis, H., Singh, K., Field, J. G., & Pierce, C. A. (2015) · Journal of Applied Psychology · doi:10.1037/a0038047 · Cited by 768
Self-citationGabriel, A. S., Podsakoff, N. P., Beal, D. J., Scott, B. A., Sonnentag, S., Trougakos, J. P., & Butts, M. M. (2019) · Organizational Research Methods · doi:10.1177/1094428118802626 · Cited by 755
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Metadata
- Authors
- Mathieu, J. E., Aguinis, H., Culpepper, S. A., & Chen, G.
- Venue
- Journal of Applied Psychology
- Published
- 2012
- Volume
- 97
- Issue
- 5
- Pages
- 951-966
- ISSN
- 0021-9010 (ISSN-L)
- 1939-1854
- OpenAlex
- W2045313662
- Cited by
- 543
- References
- 56
- FWCI
- 22.47
- Type
- journal article
- Language
- en
- Open access
- closed
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- Mathieu, J. E., Aguinis, H., Culpepper, S. A., & Chen, G. (2012). Understanding and estimating the power to detect cross-level interaction effects in multilevel modeling. Journal of Applied Psychology. https://doi.org/10.1037/a0028380
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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