Title |
Understanding and misunderstanding group mean centering: a commentary on Kelley et al.’s dangerous practice
|
---|---|
Published in |
Quality & Quantity, November 2017
|
DOI | 10.1007/s11135-017-0593-5 |
Pubmed ID | |
Authors |
Andrew Bell, Kelvyn Jones, Malcolm Fairbrother |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 6 | 29% |
United States | 5 | 24% |
Germany | 2 | 10% |
Australia | 1 | 5% |
Canada | 1 | 5% |
Unknown | 6 | 29% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 13 | 62% |
Scientists | 6 | 29% |
Science communicators (journalists, bloggers, editors) | 2 | 10% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 176 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 39 | 22% |
Researcher | 27 | 15% |
Student > Master | 23 | 13% |
Student > Doctoral Student | 14 | 8% |
Lecturer | 10 | 6% |
Other | 27 | 15% |
Unknown | 36 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Social Sciences | 39 | 22% |
Psychology | 37 | 21% |
Economics, Econometrics and Finance | 10 | 6% |
Environmental Science | 9 | 5% |
Business, Management and Accounting | 8 | 5% |
Other | 28 | 16% |
Unknown | 45 | 26% |