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相关论文: Emulating Stepped-Wedge Cluster Randomized Trials …

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Staggered treatment adoption arises in the evaluation of policy impact and implementation in many settings, including both randomized stepped-wedge trials and non-randomized quasi-experiments with panel data. In both settings, getting an…

统计方法学 · 统计学 2024-10-14 Lee Kennedy-Shaffer

Background: When planning a cluster randomized trial, evaluators often have access to an enumerated cohort representing the target population of clusters. Practicalities of conducting the trial, such as the need to oversample clusters with…

统计方法学 · 统计学 2024-09-19 Sarah E. Robertson , Jon A. Steingrimsson , Issa J. Dahabreh

A stepped wedge design is a unidirectional crossover design where clusters are randomized to distinct treatment sequences. While model-based analysis of stepped wedge designs is standard practice to evaluate treatment effects accounting for…

统计方法学 · 统计学 2024-09-13 Bingkai Wang , Xueqi Wang , Fan Li

Numerous publications have now addressed the principles of designing, analyzing, and reporting the results of, stepped-wedge cluster randomized trials. In contrast, there is little research available pertaining to the design and analysis of…

统计方法学 · 统计学 2018-06-29 Michael Grayling , Adrian Mander , James Wason

While palliative care is increasingly commonly delivered to hospitalized patients with serious illnesses, few studies have estimated its causal effects. Courtright et al. (2016) adopted a cluster-randomized stepped-wedge design to assess…

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…

统计方法学 · 统计学 2026-05-12 Fan Xia , K. C. Gary Chan , Emily Voldal , Avi Kenny , Patrick J. Heagerty , James P. Hughes

A stepped wedge cluster randomized trial is a type of longitudinal cluster design that sequentially switches clusters to intervention over time until all clusters are treated. While the traditional posttest-only parallel design requires…

应用统计 · 统计学 2021-01-05 Fan Li

The Stepped Wedge Design (SWD) is a form of cluster randomized trial, usually comparing two treatments, which is divided into time periods and sequences, with clusters allocated to sequences. Typically all sequences start with the standard…

统计方法学 · 统计学 2020-11-06 John N. S. Matthews

Adaptive sample size re-estimation, early stopping, and trial re-design at interim analyses can reduce expected sample sizes in randomised trials. Cluster randomised trials, in which groups of participants are randomly allocated to…

统计方法学 · 统计学 2026-03-09 Samuel I. Watson , James Martin

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…

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…

统计方法学 · 统计学 2025-04-22 Zhe Chen , Wei Wang , Yingying Lu , Scott D. Halpern , Katherine R. Courtright , Fan Li , Michael O. Harhay

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…

统计方法学 · 统计学 2024-07-16 Lee Kennedy-Shaffer , Victor De Gruttola , Marc Lipsitch

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…

统计方法学 · 统计学 2025-02-19 Alessandro Gasparini , Michael J. Crowther , Emiel O. Hoogendijk , Fan Li , Michael O. Harhay

A randomized trial and an analysis of observational data designed to emulate the trial sample observations separately, but have the same eligibility criteria, collect information on some shared baseline covariates, and compare the effects…

统计方法学 · 统计学 2022-03-29 Issa J. Dahabreh , Jon A. Steingrimsson , James M. Robins , Miguel A. Hernán

Under a generalised estimating equation analysis approach, approximate design theory is used to determine Bayesian D-optimal designs. For two examples, considering simple exchangeable and exponential decay correlation structures, we compare…

统计方法学 · 统计学 2024-02-16 Laura Etfer , James M. S. Wason , Michael J. Grayling

Background: In settings where proof-of-principle trials have succeeded but the effectiveness of different forms of implementation remains uncertain, trials that not only generate information about intervention effects but also provide…

定量方法 · 定量生物学 2017-05-16 Guy Harling , Rui Wang , Jukka-Pekka Onnela , Victor De Gruttola

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…

统计方法学 · 统计学 2018-03-28 Michael Grayling , David Robertson , James Wason , Adrian Mander

Cluster-randomized experiments are widely used due to their logistical convenience and policy relevance. To analyze them properly, we must address the fact that the treatment is assigned at the cluster level instead of the individual level.…

统计方法学 · 统计学 2021-08-06 Fangzhou Su , Peng Ding

There are multiple cluster randomised trial designs that vary in when the clusters cross between control and intervention states, when observations are made within clusters, and how many observations are made at that time point. Identifying…

统计方法学 · 统计学 2023-07-20 Samuel I. Watson , Alan Girling , Karla Hemming

Technological advancements in the field of mobile devices and wearable sensors have helped overcome obstacles in the delivery of care, making it possible to deliver behavioral treatments anytime and anywhere. Increasingly the delivery of…

应用统计 · 统计学 2017-11-13 Walter Dempsey , Peng Liao , Santosh Kumar , Susan A. Murphy
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