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.
