Data Aggregation in Team Research: Theoretical Considerations and Practical Recommendations

This is the authors' abstract. We don't add key points for this paper.

Studying teams comes with notable theoretical and analytical challenges. One major challenge is data aggregation, the process of bringing a variable that was measured at the individual level to the team level of analysis. We provide an accessible resource about data aggregation that integrates theoretical and empirical insights, dispels common misconceptions, and provides practical guidelines for researchers. We stress that decisions about aggregation should be based on theoretical considerations about the nature of variables and their interrelations. Based on the logic of latent variable models, we distinguish reflective and formative team constructs. For reflective team constructs, we discuss issues of within-team agreement and the notion of the conceptual mean. For formative team constructs, we distinguish between well-defined and ill-defined constructs, and offer guidelines for their aggregation. This discussion results in twelve concrete guidelines that can be used by researchers, reviewers, and editors in the design and evaluation of team studies.