Experimental Power for Mediation Effects in Multisite Studies (Poster 6)

• In Event: Innovations in Statistical Power, Intervention Planning and Design, and Causal Effects

Abstract

Multisite mediation studies represent an analytic cornerstone in the development and assessment of theories across a broad array of disciplines because they can critically map out development processes and create opportunities to learn how context constrains or facilitates mediating mechanisms. Despite their widespread use, a notable missing component is methods for predicting statistical power and sample sizes that position studies to detect such effects. Yet literature has emphasized the importance of complementing main effect power analyses with mediation effect power analyses (even if considered a secondary objective) because they frequently suggest different designs, sample sizes, and resource allocations. In this study, we develop formulas and an R ShinyApp to predict power and guide the design of multisite studies probing mediation.

Authors

• Fangxing Bai, Montana State University

• Benjamin Kelcey, University of Cincinnati

• Amota Ataneka, University of Cincinnati

• Yanli Xie, Florida State University

• Nianbo Dong, University of North Carolina - Chapel Hill