Design Considerations in Multisite Randomized Trials Probing Moderated Treatment Effects
Author(s) -
Nianbo Dong,
Benjamin Kelcey,
Jessaca Spybrook
Publication year - 2020
Publication title -
journal of educational and behavioral statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.066
H-Index - 59
eISSN - 1935-1054
pISSN - 1076-9986
DOI - 10.3102/1076998620961492
Subject(s) - statistical power , multilevel model , sample size determination , randomized controlled trial , treatment effect , psychology , interaction , statistics , random effects model , research design , randomized experiment , computer science , econometrics , mathematics , meta analysis , medicine , surgery , traditional medicine
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.
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