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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

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":…

Hybrid studies allow investigators to simultaneously study an intervention effectiveness outcome and an implementation research outcome. In particular, type 2 hybrid studies support research that places equal importance on both outcomes…

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

A practical limitation of cluster randomized controlled trials (cRCTs) is that the number of available clusters may be small, resulting in an increased risk of baseline imbalance under simple randomization. Constrained randomization…

Methodology · Statistics 2022-01-19 Yunji Zhou , Elizabeth L. Turner , Ryan A. Simmons , Fan Li

Analyses of cluster randomized trials (CRTs) can be complicated by informative missing outcome data. Methods such as inverse probability weighted generalized estimating equations have been proposed to account for informative missingness by…

Methodology · Statistics 2023-04-13 Chia-Rui Chang , Rui Wang

Background: Stepped wedge cluster randomized trials (SW-CRTs) involve sequential measurements within clusters over time. Initially, all clusters start in the control condition before crossing over to the intervention on a staggered…

Methodology · Statistics 2026-01-21 Jale Basten , Katja Ickstadt , Nina Timmesfeld

Cluster algorithms are increasingly popular in biomedical research due to their compelling ability to identify discrete subgroups in data, and their increasing accessibility in mainstream software. While guidelines exist for algorithm…

Machine Learning · Statistics 2021-05-26 E. S. Dalmaijer , C. L. Nord , D. E. Astle

Cluster-level dynamic treatment regimens can be used to guide sequential, intervention or treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level DTR, the…

Methodology · Statistics 2016-07-15 Timothy NeCamp , Amy Kilbourne , Daniel Almirall

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,…

Longitudinal cluster randomized trials (L-CRTs) are increasingly used to evaluate the cost-effectiveness of healthcare interventions across multiple assessment periods, yet design methods for powering these trials remain underdeveloped.…

Methodology · Statistics 2026-03-20 Hao Wang , Jingxia Liu , Drew B. Cameron , Jiaqi Tong , Donna Spiegelman , Daniella Meeker , Fan Li

In many scientific problems, researchers try to relate a response variable $Y$ to a set of potential explanatory variables $X = (X_1,\dots,X_p)$, and start by trying to identify variables that contribute to this relationship. In statistical…

Statistics Theory · Mathematics 2020-10-07 Wenshuo Wang , Lucas Janson

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…

In cluster-randomized trials (CRTs), there is emerging interest in exploring the causal mechanism in which a cluster-level treatment affects the outcome through an intermediate outcome. The majority of existing causal mediation methods are…

Methodology · Statistics 2026-01-12 Chao Cheng , Fan Li

We address estimation of intervention effects in experimental designs in which (a) interventions are assigned at the cluster level; (b) clusters are selected to form pairs, matched on observed characteristics; and (c) intervention is…

Methodology · Statistics 2014-11-24 Zhenke Wu , Constantine E. Frangakis , Thomas A. Louis , Daniel O. Scharfstein

Two-stage randomized experiments are becoming an increasingly popular experimental design for causal inference when the outcome of one unit may be affected by the treatment assignments of other units in the same cluster. In this paper, we…

Methodology · Statistics 2022-10-21 Zhichao Jiang , Kosuke Imai , Anup Malani

Educational research often studies subjects that are in naturally clustered groups of classrooms or schools. When designing a randomized experiment to evaluate an intervention directed at teachers, but with effects on teachers and their…

Applications · Statistics 2009-08-17 Brenda Jenney , Sharon Lohr

The parallel cluster randomized trial with baseline (PB-CRT) is a common variant of the standard parallel cluster randomized trial (P-CRT). We define two natural estimands in the context of PB-CRTs with informative cluster sizes, the…

Methodology · Statistics 2025-05-01 Kenneth Menglin Lee , Fan Li

Most cluster randomized trials (CRTs) randomize fewer than 30-40 clusters in total. When performing inference for such ``small'' CRTs, it is important to use methods that appropriately account for the small sample size. When the generalized…

Methodology · Statistics 2025-12-01 Shifeng Sun , Xueqi Wang , Zhuoran Hou , Elizabeth L. Turner

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