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In stepped wedge cluster randomized trials (SW-CRTs), observations collected under the control condition are, on average, from an earlier time than observations collected under the intervention condition. In a cohort design, participants…

Methodology · Statistics 2023-02-23 Jale Basten , Katja Ickstadt , Nina Timmesfeld

Linear mixed models are commonly used in analyzing stepped-wedge cluster randomized trials (SW-CRTs). A key consideration for analyzing a SW-CRT is accounting for the potentially complex correlation structure, which can be achieved by…

Methodology · Statistics 2024-08-21 Yongdong Ouyang , Monica Taljaard , Andrew B Forbes , Fan Li

Stepped-wedge cluster randomized trials (SW-CRTs) evaluate interventions rolled out across clusters over time. Standard analyses typically use immediate-treatment (IT) models, which assume effects begin at crossover and remain constant…

Methodology · Statistics 2026-04-21 Yongdong Ouyang , Monica Taljaard , James P. Hughes , Fan Li

Stepped-wedge cluster randomised trials (SW-CRTs) increasingly evaluate complex interventions, yet methodological guidance for analysing composite endpoints using generalized pairwise comparisons (GPC)remains limited. This work investigates…

Stepped wedge cluster randomized trials (SWCRTs) often face challenges with potential confounding by time trends. Traditional frequentist methods can fail to provide adequate coverage of the intervention's true effect using confidence…

Methodology · Statistics 2024-02-02 Danni Wu , Hyung G. Park , Corita R. Grudzen , Keith S. Goldfeld

In stepped wedge cluster randomized trials (SW-CRTs), the intervention is rolled out to clusters over multiple periods. A standard approach for analyzing SW-CRTs utilizes the linear mixed model, where the treatment effect is only present…

Stepped wedge cluster randomized trials (SW-CRTs) have become increasingly popular and are used for a variety of interventions and outcomes, often chosen for their feasibility advantages. SW-CRTs must account for time trends in the outcome…

Methodology · Statistics 2024-07-16 Lee Kennedy-Shaffer , Victor De Gruttola , Marc Lipsitch

Multivariate outcomes are common in pragmatic cluster randomized trials. While sample size calculation procedures for multivariate outcomes exist under parallel assignment, none have been developed for a stepped wedge design. In this…

Methodology · Statistics 2022-12-05 Kendra Davis-Plourde , Monica Taljaard , Fan Li

Stepped-wedge cluster randomized trials (SW-CRTs) are traditionally analyzed with models that assume an immediate and sustained treatment effect. Previous work has shown that making such an assumption in the analysis of SW-CRTs when the…

Methodology · Statistics 2025-04-08 Kenneth M. Lee , Elizabeth L. Turner , Avi Kenny

The traditional model specification of stepped-wedge cluster-randomized trials assumes a homogeneous treatment effect across time while adjusting for fixed-time effects. However, when treatment effects vary over time, the constant effect…

Mediation analysis has been comprehensively studied for independent data but relatively little work has been done for correlated data, especially for the increasingly adopted stepped wedge cluster randomized trials (SW-CRTs). Motivated by…

Methodology · Statistics 2025-04-03 Zhiqiang Cao , Fan Li

In stepped wedge cluster randomized trials (SW-CRTs), interventions are sequentially rolled out to clusters over multiple periods. It is common practice to analyze SW-CRTs using discrete-time linear mixed models, in which measurements are…

Methodology · Statistics 2025-11-25 Hao Wang , Guangyu Tong , Heather Allore , Monica Taljaard , Fan Li

Stepped wedge cluster-randomized trial (CRTs) designs randomize clusters of individuals to intervention sequences, ensuring that every cluster eventually transitions from a control period to receive the intervention under study by the end…

Staggered rollout cluster randomized experiments (SR-CREs) involve sequential treatment adoption across clusters, requiring analysis methods that address a general class of dynamic causal effects, anticipation, and non-ignorable…

Methodology · Statistics 2026-02-02 Xinyuan Chen , Fan Li

Stepped wedge designs (SWDs) are increasingly used to evaluate longitudinal cluster-level interventions but pose substantial challenges for valid inference. Because crossover times are randomized, intervention effects are intrinsically…

Methodology · Statistics 2026-05-12 Fan Xia , K. C. Gary Chan , Emily Voldal , Avi Kenny , Patrick J. Heagerty , James P. Hughes

Stepped wedge cluster randomized controlled trials are typically analyzed using models that assume the full effect of the treatment is achieved instantaneously. We provide an analytical framework for scenarios in which the treatment effect…

Methodology · Statistics 2025-09-25 Avi Kenny , Emily Voldal , Fan Xia , Patrick J. Heagerty , James P. Hughes

Stepped wedge cluster randomized trials (SW-CRTs) have historically been analyzed using immediate treatment (IT) models, which assume the effect of the treatment is immediate after treatment initiation and subsequently remains constant over…

Stepped wedge cluster randomized trials (SW-CRTs) with binary outcomes are increasingly used in prevention and implementation studies. Marginal models represent a flexible tool for analyzing SW-CRTs with population-averaged interpretations,…

Methodology · Statistics 2021-01-05 Fan Li , Hengshi Yu , Paul J. Rathouz , Elizabeth L. Turner , John S. Preisser

Recently, methodology was presented to facilitate the incorporation of interim analyses in stepped-wedge (SW) cluster randomised trials (CRTs). Here, we extend this previous discussion. We detail how the stopping boundaries, allocation…

Methodology · Statistics 2018-03-28 Michael Grayling , David Robertson , James Wason , Adrian Mander

Stepped-wedge cluster-randomized trials (SW-CRTs) are widely used in healthcare and implementation science, providing an ethical advantage by ensuring all clusters eventually receive the intervention. The staggered rollout of treatment…

Methodology · Statistics 2026-04-03 Xi Fang , Xueqi Wang , Patrick J. Heagerty , Bingkai Wang , Fan Li
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