@article{ref1,
title="Understanding and misunderstanding group mean centering: a commentary on Kelley et al.'s dangerous practice",
journal="Quality and Quantity",
year="2018",
author="Bell, Andrew and Jones, Kelvyn and Fairbrother, Malcolm",
volume="52",
number="5",
pages="2031-2036",
abstract="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.<p /> <p>Language: en</p>",
language="en",
issn="0033-5177",
doi="10.1007/s11135-017-0593-5",
url="http://dx.doi.org/10.1007/s11135-017-0593-5"
}