Designing three-level cluster randomized trials to assess treatment effect heterogeneity.

ABSTRACT: Cluster randomized trials often exhibit a three-level structure with participants nested in subclusters such as health care providers, and subclusters nested in clusters such as clinics. While the average treatment effect has been the primary focus in planning three-level randomized trials, interest is growing in understanding whether the treatment effect varies among prespecified patient subpopulations, such as those defined by demographics or baseline clinical characteristics. In this article, we derive novel analytical design formulas based on the asymptotic covariance matrix for powering confirmatory analyses of treatment effect heterogeneity in three-level trials, that are broadly applicable to the evaluation of cluster-level, subcluster-level, and participant-level effect modifiers a

SUBMITTER: Li F 

PROVIDER: S-EPMC10583727 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature