A tutorial on centering in cross-sectional two-level models

Nicholas D. Myers, Ahnalee M. Brincks, Mark R. Beauchamp

Research output: Contribution to journalReview articlepeer-review

6 Scopus citations

Abstract

The primary purpose of this tutorial is to succinctly review some options for, and consequences of, centering Level 1 predictors in commonly applied cross-sectional two-level models. It is geared toward both practitioners and researchers. A general understanding of multilevel modeling is necessary prior to understanding the subtleties of centering decisions. A review of some high-quality journals within the broad discipline of exercise science provides evidence that multilevel modeling is used relatively infrequently in this field. Therefore, a secondary purpose is to introduce Measurement in Physical Education and Exercise Science readers to some core facets of multilevel modeling within the framework of this tutorial. A relevant dataset is used to demonstrate potential consequences of different centering decisions within a multilevel model. Depending on the model and the data, different centering decisions can exert non-trivial influence on the meaning of some model parameters, results from fitting the model, and subsequent conclusions.

Original languageEnglish (US)
Pages (from-to)275-294
Number of pages20
JournalMeasurement in Physical Education and Exercise Science
Volume14
Issue number4
DOIs
StatePublished - Oct 1 2010

Keywords

  • centering within cluster
  • grand mean centering
  • group mean centering
  • hierarchical linear modeling
  • multilevel modeling
  • raw score

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine
  • Physical Therapy, Sports Therapy and Rehabilitation

Fingerprint Dive into the research topics of 'A tutorial on centering in cross-sectional two-level models'. Together they form a unique fingerprint.

Cite this