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Power Analysis for Moderator Effects in Longitudinal Cluster Randomized Designs.

Wei Li1, Spyros Konstantopoulos2

  • 1University of Florida, Gainesville, USA.

Educational and Psychological Measurement
|January 5, 2023
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This study offers statistical power analysis methods for moderator effects in longitudinal cluster randomized trials. These methods account for complex design features to improve the accuracy of intervention effect evaluation.

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longitudinal cluster randomized designsmoderator effectsmultilevel modelingpower analysis

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Area of Science:

  • Biostatistics
  • Longitudinal Data Analysis
  • Cluster Randomized Trials

Background:

  • Longitudinal cluster randomized trials (CRTs) frequently measure outcomes repeatedly over time.
  • Researchers examine intervention effects and their modification by individual or cluster-level moderators.

Purpose of the Study:

  • To provide methods for statistical power analysis of moderator effects in two- and three-level longitudinal CRTs.
  • To enhance the design and interpretation of studies investigating moderated intervention effects over time.

Main Methods:

  • Developed statistical power analysis for moderator effects in longitudinal CRTs.
  • Incorporated factors like clustering, repeated measures, sample sizes, covariates, and moderator variance.
  • Utilized two- and three-level longitudinal cluster randomized designs.

Main Results:

  • Presented methods for calculating statistical power for moderator effects in complex longitudinal CRTs.
  • Demonstrated the influence of various design parameters on power.
  • Provided practical guidance for researchers.

Conclusions:

  • The proposed methods enable accurate statistical power analysis for moderator effects in longitudinal CRTs.
  • Facilitates robust study design and interpretation of intervention effects.
  • Applicable to diverse research settings with longitudinal clustered data.