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Understanding and misunderstanding group mean centering: a commentary on Kelley et al.’s dangerous practice
Sheffield Methods Institute, University of Sheffield.ORCID iD: 0000-0002-8268-5853
School of Geographical Sciences, University of Bristol.
Umeå University, Faculty of Social Sciences, Department of Sociology.ORCID iD: 0000-0002-1400-2141
(English)In: Quality & Quantity, ISSN 0033-5177Article in journal (Refereed) Epub ahead of print
Abstract [en]

Kelley et al. argue that group-mean-centering covariates in multilevel models is dangerous, since—they claim—it generates results that are biased and misleading. We argue instead that what is dangerous is Kelley et al.’s unjustified assault on a simple statistical procedure that is enormously helpful, if not vital, in analyses of multilevel data. Kelley et al.’s arguments appear to be based on a faulty algebraic operation, and on a simplistic argument that parameter estimates from models with mean-centered covariates must be wrong merely because they are different than those from models with uncentered covariates. They also fail to explain why researchers should dispense with mean-centering when it is central to the estimation of fixed effects models—a common alternative approach to the analysis of clustered data, albeit one increasingly incorporated within a random effects framework. Group-mean-centering is, in short, no more dangerous than any other statistical procedure, and should remain a normal part of multilevel data analyses where it can be judiciously employed to good effect.

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Sociology (excluding Social Work, Social Psychology and Social Anthropology)
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URN: urn:nbn:se:umu:diva-142213DOI: 10.1007/s11135-017-0593-5OAI: oai:DiVA.org:umu-142213DiVA, id: diva2:1160281
Available from: 2017-11-25 Created: 2017-11-25 Last updated: 2018-06-09

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Publisher's full texthttps://link.springer.com/article/10.1007/s11135-017-0593-5

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Bell, AndrewFairbrother, Malcolm

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