A Bayesian adaptive design approach for stepped-wedge cluster randomized trials.

ABSTRACT:

Background

The Bayesian group sequential design has been applied widely in clinical studies, especially in Phase II and III studies. It allows early termination based on accumulating interim data. However, to date, there lacks development in its application to stepped-wedge cluster randomized trials, which are gaining popularity in pragmatic trials conducted by clinical and health care delivery researchers.

Methods

We propose a Bayesian adaptive design approach for stepped-wedge cluster randomized trials, which makes adaptive decisions based on the predictive probability of declaring the intervention effective at the end of study given interim data. The Bayesian models and the algorithms for posterior inference and trial conduct are presented.

Results

We present how t

SUBMITTER: Wang J 

PROVIDER: S-EPMC11261240 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature