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Cluster-randomized trials (CRTs) are widely used to evaluate group-level interventions and increasingly collect multiple outcomes capturing complementary dimensions of benefit and risk. Investigators often seek a single global summary of…

Methodology · Statistics 2026-01-22 Xinyuan Chen , Fan Li

In the analysis of cluster randomized trials (CRTs), previous work has defined two meaningful estimands: the individual-average treatment effect (iATE) and cluster-average treatment effect (cATE) estimand, to address individual and…

Paired cluster-randomized experiments (pCRTs) are common across many disciplines because there is often natural clustering of individuals, and paired randomization can help balance baseline covariates to improve experimental precision.…

Methodology · Statistics 2024-07-03 Charlotte Z. Mann , Adam C. Sales , Johann A. Gagnon-Bartsch

In cluster-randomized trials (CRTs), entire clusters of individuals are randomized to treatment, and outcomes within a cluster are typically correlated. While frequentist approaches are standard practice for CRT analysis, Bayesian methods…

Methodology · Statistics 2025-11-27 Ruyi Liu , Joshua L. Warren , Yuki Ohnishi , Donna Spiegelman , Liangyuan Hu , Fan Li

Cluster-randomized trials (CRTs) are widely used to evaluate interventions delivered at the clinic, practice, or community level. Although standard analyses typically target average treatment effects, such summaries mask potentially…

Methodology · Statistics 2026-04-16 Changjun Li , Xi Fang , Michael O. Harhay , Andrew B. Forbes , F. Perry Wilson , Guangyu Tong , Fan Li

In cluster randomized trials, the average treatment effect among individuals (i-ATE) can be different from the cluster average treatment effect (c-ATE) when informative cluster size is present, i.e., when treatment effects or participant…

Methodology · Statistics 2025-10-02 Bryan S. Blette , Zhe Chen , Brennan C. Kahan , Andrew Forbes , Michael O. Harhay , Fan Li

Across research disciplines, cluster randomized trials (CRTs) are commonly implemented to evaluate interventions delivered to groups of participants, such as communities and clinics. Despite advances in the design and analysis of CRTs,…

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…

Cluster-randomized trials (CRTs) involve randomizing entire groups of participants -- called clusters -- to treatment arms but are often comprised of a limited or fixed number of available clusters. While covariate adjustment can account…

Methodology · Statistics 2022-11-29 Angela Y. Zhu , Nandita Mitra , Karla Hemming , Michael O. Harhay , Fan Li

Clustering and dependence are common in trials. For example, in some cluster randomized trials (CRTs), pre-existing clusters are enrolled, randomized, and serve as the basis of intervention delivery. Such CRTs are "fully clustered":…

Cluster-randomized trials (CRTs) are experimental designs where groups or clusters of participants, rather than the individual participants themselves, are randomized to intervention groups. Analyzing CRT requires distinguishing between…

Methodology · Statistics 2025-10-10 Xi Fang , Bingkai Wang , Liangyuan Hu , Fan Li

In cluster-randomized trials, generalized linear mixed models and generalized estimating equations have conventionally been the default analytic methods for estimating the average treatment effect as routine practice. However, recent…

Methodology · Statistics 2025-09-19 Fan Li , Jiaqi Tong , Xi Fang , Chao Cheng , Brennan C. Kahan , Bingkai Wang

In a cluster-randomized experiment, treatment is assigned to clusters of individual units of interest--households, classrooms, villages, etc.--instead of the units themselves. The number of clusters sampled and the number of units sampled…

Methodology · Statistics 2020-02-20 Yeng Xiong , Michael J. Higgins

This article investigates the model-robustness of fixed-effects models for analyzing a broad class of longitudinal cluster trials (CTs) such as stepped-wedge, parallel-with-baseline and crossover designs, encompassing both randomized (CRTs)…

Methodology · Statistics 2026-04-10 Kenneth M. Lee , 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

Causal mediation analysis in cluster-randomized trials (CRTs) is complicated by the presence of multiple mediators, intracluster correlation, and within-cluster interference. Existing mediation methods often fall short in accommodating…

Methodology · Statistics 2026-04-14 Jiaqi Tong , Chao Cheng , Fan Li

Randomized trials are viewed as the benchmark for assessing causal effects of treatments on outcomes of interest. Nonetheless, challenges such as measurement error can undermine the standard causal assumptions for randomized trials. In…

Methodology · Statistics 2025-08-27 Dane Isenberg , Nandita Mitra , Steven C. Marcus , Rinad S. Beidas , Kristin A. Linn

In cluster randomized trials, patients are typically recruited after clusters are randomized, and the recruiters and patients may not be blinded to the assignment. This often leads to differential recruitment and consequently systematic…

Methodology · Statistics 2021-10-05 Fan Li , Zizhong Tian , Jennifer Bobb , Georgia Papadogeorgou , Fan Li

In this article, we develop methods for sample size and power calculations in four-level intervention studies when intervention assignment is carried out at any level, with a particular focus on cluster randomized trials (CRTs). CRTs…

Methodology · Statistics 2022-09-07 Xueqi Wang , Elizabeth L. Turner , John S. Preisser , Fan Li

Causal mediation analysis in cluster-randomized trials (CRTs) is essential for explaining how cluster-level interventions affect individual outcomes, yet it is complicated by interference, post-treatment confounding, and hierarchical…

Methodology · Statistics 2026-03-25 Yuki Ohnishi , Michael J. Daniels , Lei Yang , Fan Li
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