Understanding and misunderstanding group mean centering : a commentary on Kelley et al.'s dangerous practice

• 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.

Subject headings

SAMHÄLLSVETENSKAP  -- Sociologi -- Sociologi (hsv//swe)

SOCIAL SCIENCES  -- Sociology -- Sociology (hsv//eng)

Keyword

Multilevel models

Random effects

Group-mean-centering

Mundlak

Fixed effects

Publication and Content Type

ref (subject category)

art (subject category)