Bayesian Hierarchical Penalized Spline Models for Immediate and Time-Varying Intervention Effects in Stepped Wedge Cluster Randomized Trials.

ABSTRACT: Stepped wedge cluster randomized trials (SWCRTs) often face challenges related to potential confounding by time. Traditional frequentist methods may not provide adequate coverage of an intervention's true effect using confidence intervals, whereas Bayesian approaches show potential for better coverage of intervention effects. However, Bayesian methods remain underexplored in the context of SWCRTs. To bridge this gap, we propose two innovative Bayesian hierarchical penalized spline models. Our first model accommodates large numbers of clusters and time periods, focusing on immediate intervention effects. To evaluate this approach, we compared this model to traditional frequentist methods. We then extend our approach to account for time-varying intervention effects, conducting a comprehensiv

SUBMITTER: Wu D 

PROVIDER: S-EPMC11835049 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature