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Cluster randomized trials (CRTs) are studies where treatment is randomized at the cluster level but outcomes are typically collected at the individual level. When CRTs are employed in pragmatic settings, baseline population characteristics…

统计方法学 · 统计学 2023-06-22 Mary M. Ryan , Denise Esserman , Fan Li

Evaluating heterogeneity of treatment effects (HTE) across subgroups is common in both randomized trials and observational studies. Although several statistical challenges of HTE analyses including low statistical power and multiple…

统计方法学 · 统计学 2024-07-10 Noorie Hyun , Abisola E. Idu , Andrea J. Cook , Jennifer F. Bobb

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…

统计方法学 · 统计学 2026-04-16 Changjun Li , Xi Fang , Michael O. Harhay , Andrew B. Forbes , F. Perry Wilson , Guangyu Tong , Fan Li

Heterogeneous treatment effects (HTEs) are commonly identified during randomized controlled trials (RCTs). Identifying subgroups of patients with similar treatment effects is of high interest in clinical research to advance precision…

机器学习 · 计算机科学 2022-12-06 Peniel N. Argaw , Elizabeth Healey , Isaac S. Kohane

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,…

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…

统计方法学 · 统计学 2022-12-05 Kendra Davis-Plourde , Monica Taljaard , Fan Li

Accurately estimating the intra-class correlation coefficient (ICC) is crucial for adequately powering clustered randomized trials (CRTs). Challenges arise due to limited prior data on the specific outcome within the target population,…

统计方法学 · 统计学 2025-04-23 Chen Yang , Márcio A. Diniz , Deukwoo Kwon , Madhu Mazumdar

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…

统计方法学 · 统计学 2022-09-07 Xueqi Wang , Elizabeth L. Turner , John S. Preisser , Fan Li

Cluster or group randomized trials (CRTs) are increasingly used for both behavioral and system-level interventions, where entire clusters are randomly assigned to a study condition or intervention. Apart from the assigned cluster-level…

统计方法学 · 统计学 2024-11-19 Shubhadeep Chakraborty , Bo Wang , Ram Tiwari , Samiran Ghosh

Pragmatic trials evaluating health care interventions often adopt cluster randomization due to scientific or logistical considerations. Previous reviews have shown that co-primary endpoints are common in pragmatic trials but infrequently…

统计方法学 · 统计学 2022-05-03 Siyun Yang , Mirjam Moerbeek , Monica Taljaard , Fan Li

Statistical inference of heterogeneous treatment effects (HTEs) across predefined subgroups is challenging when units interact because treatment effects may vary by pre-treatment variables, post-treatment exposure variables (that measure…

计量经济学 · 经济学 2024-10-02 Julius Owusu

Multi-period cluster randomized trials (CRTs) are increasingly used for the evaluation of interventions delivered at the group level. While generalized estimating equations (GEE) are commonly used to provide population-averaged inference in…

统计计算 · 统计学 2022-05-31 Ying Zhang , John S. Preisser , Fan Li , Elizabeth L. Turner , Paul J. Rathouz

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…

统计方法学 · 统计学 2025-10-02 Bryan S. Blette , Zhe Chen , Brennan C. Kahan , Andrew Forbes , Michael O. Harhay , Fan Li

Estimating heterogeneous treatment effects (HTEs) is crucial for precision medicine. While multiple studies can improve the generalizability of results, leveraging them for estimation is statistically challenging. Existing approaches often…

统计方法学 · 统计学 2025-12-22 Cathy Shyr , Boyu Ren , Prasad Patil , Giovanni Parmigiani

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…

统计方法学 · 统计学 2026-04-21 Yongdong Ouyang , Monica Taljaard , James P. Hughes , Fan Li

Learning heterogeneous treatment effects (HTEs) is an important problem across many fields. Most existing methods consider the setting with a single treatment arm and a single outcome metric. However, in many real world domains, experiments…

机器学习 · 计算机科学 2022-06-13 Leon Yao , Caroline Lo , Israel Nir , Sarah Tan , Ariel Evnine , Adam Lerer , Alex Peysakhovich

Exploration of treatment effect heterogeneity (TEH) is an increasingly important aspect of modern statistical analysis for stratified medicine in randomised controlled trials (RCTs) as we start to gather more information on trial…

统计方法学 · 统计学 2019-01-14 Chieh-Hsi Wu , Chris C. Holmes

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…

统计方法学 · 统计学 2025-11-25 Avi Kenny , Emily C. Voldal , Fan Xia , Kwun Chuen Gary Chan , Patrick J. Heagerty , James P. Hughes

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…

统计方法学 · 统计学 2026-01-21 Jale Basten , Katja Ickstadt , Nina Timmesfeld

Developing tools for estimating heterogeneous treatment effects (HTE) and individualized treatment effects has been an area of active research in recent years. While these tools have proven to be useful in many contexts, a concern when…

统计方法学 · 统计学 2025-03-07 Mahsa Ashouri , Nicholas C. Henderson
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