Affiliation: University of North Carolina at Chapel Hill
Other Affiliation: University of Cincinnati
Other Affiliation: Western Michigan University
Past research has demonstrated that treatment effects frequently vary across sites (e.g., schools) and that such variation can be explained by site-level or individual-level variables (e.g., school size or gender). The purpose of this study is to develop a statistical framework and tools for the effective and efficient design of multisite randomized trials (MRTs) probing moderated treatment effects. The framework considers three core facets of such designs: (a) Level 1 and Level 2 moderators, (b) random and nonrandomly varying slopes (coefficients) of the treatment variable and its interaction terms with the moderators, and (c) binary and continuous moderators. We validate the formulas for calculating statistical power and the minimum detectable effect size difference with simulations, probe its sensitivity to model assumptions, execute the formulas in accessible software, demonstrate an application, and provide suggestions in designing MRTs probing moderated treatment effects.