How to achieve model-robust inference in stepped wedge trials with model-based methods?

ABSTRACT: A stepped wedge design is an unidirectional crossover design where clusters are randomized to distinct treatment sequences. While model-based analysis of stepped wedge designs is a standard practice to evaluate treatment effects accounting for clustering and adjusting for covariates, their properties under misspecification have not been systematically explored. In this article, we focus on model-based methods, including linear mixed models and generalized estimating equations with an independence, simple exchangeable, or nested exchangeable working correlation structure. We study when a potentially misspecified working model can offer consistent estimation of the marginal treatment effect estimands, which are defined nonparametrically with potential outcomes and may be functions of calenda

SUBMITTER: Wang B 

PROVIDER: S-EPMC11536888 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature