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Power for Detecting Treatment by Moderator Effects in Two- and Three-Level Cluster Randomized Trials

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Listed:
  • Jessaca Spybrook

    (Western Michigan University)

  • Benjamin Kelcey

    (University of Cincinnati)

  • Nianbo Dong

    (University of Missouri–Columbia)

Abstract

Recently, there has been an increase in the number of cluster randomized trials (CRTs) to evaluate the impact of educational programs and interventions. These studies are often powered for the main effect of treatment to address the “what works†question. However, program effects may vary by individual characteristics or by context, making it important to also consider power to detect moderator effects. This article presents a framework for calculating statistical power for moderator effects at all levels for two- and three-level CRTs. Annotated R code is included to make the calculations accessible to researchers and increase the regularity in which a priori power analyses for moderator effects in CRTs are conducted.

Suggested Citation

  • Jessaca Spybrook & Benjamin Kelcey & Nianbo Dong, 2016. "Power for Detecting Treatment by Moderator Effects in Two- and Three-Level Cluster Randomized Trials," Journal of Educational and Behavioral Statistics, , vol. 41(6), pages 605-627, December.
    • Handle: RePEc:sae:jedbes:v:41:y:2016:i:6:p:605-627
    DOI: 10.3102/1076998616655442
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