Multi-Level Modeling of Dyadic Data in Sport Sciences: Conceptual,Statistical, and Practical Issues |
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| Authors: | Patrick Gaudreau Marie-Claude Fecteau Stéphane Perreault |
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| Institution: | 1. School of Psychology , University of Ottawa , Ottawa, Ontario, Canada pgaudrea@uottawa.ca;3. School of Psychology , University of Ottawa , Ottawa, Ontario, Canada;4. Département des Lettres et de Communication Sociale , Université du Québec à Trois-Rivières, Trois-Rivières , Québec, Canada |
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| Abstract: | The goal of this article is to present a series of conceptual, statistical, and practical issues in the modeling of multi-level dyadic data. Distinctions are made between distinguishable and undistinguishable dyads and several types of independent variables modeled at the dyadic level of analysis. Multi-level modeling equations are explained in a non-technical manner. A database of 66 athletes regrouped in 33 undistinguishable dyads is used to illustrate the steps from initial preparation of multi-level databases to the interpretations of output files. The data are used to examine null, intercept-as-outcome, and slope-as-outcome models, as well as to present a formula to calculate percentage of variance explained at different levels of analysis. A simple slopes procedure is showed to probe significant cross-level interactions (slope-as-outcome model) in a manner consistent with the approach generally used in ordinary least square regression. Potential extensions and limitations of this multi-level approach are presented in the discussion. |
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| Keywords: | dyads hierarchical linear modeling multi-level |
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