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20242026
most citedAnalysis of cohort stepped wedge cluster-randomized trials with non-ignorable dropout via joint modeling

4 citations · 5 across the 17 of their papers we have counts for

collaborators

18 papers

stat.ME2026

Heterogeneous survivor average causal effects beyond monotonicity: Applications to a clinical trial evaluating mechanical ventilation strategies

Zihan Zhu, Guangyu Tong, Fernando Godinho Zampieri +3

Clinical trials in critical care often evaluate outcomes that are truncated by death, such as time to discharge alive, for which treatment effects are not well defined among patien…

stat.ME2026

Cluster randomized crossover trials with very few clusters but multiple periods: which analyses for continuous outcomes should be used?

Guangyu Tong, Qianzhe Sun, Jessica Kasza +3

Cluster randomized crossover (CRXO) trials are often used when individual randomization is impractical and the number of available clusters is limited. However, statistical analysi…

stat.ME2026

Saturation in G: simple & robust causal inference in cluster randomized trials with informative cluster sizes

Kenneth M. Lee, Michael O. Harhay, Fan Li

Cluster randomized trials (CRTs) can exhibit informative cluster sizes (ICS) where cluster size is associated with outcomes and/or treatment effects. Under ICS, the individual and…

stat.ME2026

Who's Winning? Clarifying Estimands Based on Win Statistics in Cluster Randomized Trials

Kenneth M. Lee, Xi Fang, Fan Li +1

Treatment effect estimands based on win statistics, including the win ratio, win odds, and win difference are increasingly popular targets for summarizing endpoints in clinical tri…

stat.AP2025

Uncovering Treatment Effect Heterogeneity in Pragmatic Gerontology Trials

Changjun Li, Heather Allore, Michael O. Harhay +2

Detecting heterogeneity in treatment response enriches the interpretation of gerontologic trials. In aging research, estimating the effect of the intervention on clinically meaning…

stat.ME2025

Evaluating Informative Cluster Size in Cluster Randomized Trials

Bryan S. Blette, Zhe Chen, Brennan C. Kahan +3

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 siz…

stat.ME2025

Randomization inference for stepped-wedge designs with noncompliance with application to a palliative care pragmatic trial

Jeffrey Zhang, Zhe Chen, Xinyuan Chen +5

While palliative care is increasingly commonly delivered to hospitalized patients with serious illnesses, few studies have estimated its causal effects. Courtright et al. (2016) ad…

stat.ME2025

Sample size calculations for multilevel factorial longitudinal cluster randomised trials

Rhys Bowden, Rebecca Walwyn, Jessica Kasza +4

Typically, trials investigate the impact of either an individual-level intervention on participant outcomes, or the impact of a cluster-level intervention on participant outcomes.…

stat.ME2025

Bayesian inference for cluster-randomized trials with multivariate outcomes subject to both truncation by death and missingness

Guangyu Tong, Chenxi Li, Eric Velazquez +2

Cluster-randomized trials (CRTs) on fragile populations frequently encounter complex attrition problems where the reasons for missing outcomes can be heterogeneous, with participan…

stat.ME2025★ 1 cited

What is estimated in cluster randomized crossover trials with informative sizes? -- A survey of estimands and common estimators

Kenneth M. Lee, Andrew B. Forbes, Jessica Kasza +5

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

stat.ME2025

A Bayesian approach to the survivor average causal effect in cluster-randomized crossover trials

Dane Isenberg, Michael O. Harhay, Andrew B. Forbes +3

In cluster-randomized crossover (CRXO) trials, groups of individuals are randomly assigned to two or more sequences of alternating treatments. Since clusters serve as their own con…

stat.ME2025

Time-varying treatment effect models in stepped-wedge cluster-randomized trials with multiple interventions

Zhe Chen, Wei Wang, Yingying Lu +4

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

stat.ME2025

On Anticipation Effect in Stepped Wedge Cluster Randomized Trials

Hao Wang, Xinyuan Chen, Katherine R. Courtright +4

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 linea…

stat.ME2025

A tutorial on conducting sample size and power calculations for detecting treatment effect heterogeneity in cluster randomized trials with linear mixed models

Mary Ryan Baumann, Monica Taljaard, Patrick J. Heagerty +4

Cluster-randomized trials (CRTs) are a well-established class of designs for evaluating community-based interventions. An essential task in planning these trials is determining the…

stat.ME2025

Semiparametric principal stratification analysis beyond monotonicity

Jiaqi Tong, Brennan Kahan, Michael O. Harhay +1

Intercurrent events, common in clinical trials and observational studies, affect the existence or interpretation of final outcomes. Principal stratification addresses this challeng…

stat.ME2024

Doubly robust estimation and sensitivity analysis with outcomes truncated by death in multi-arm clinical trials

Jiaqi Tong, Chao Cheng, Guangyu Tong +2

In clinical trials, the observation of participant outcomes may frequently be hindered by death, leading to ambiguity in defining a scientifically meaningful final outcome for thos…

stat.ME2024

Weighting methods for truncation by death in cluster-randomized trials

Dane Isenberg, Michael Harhay, Nandita Mitra +1

Patient-centered outcomes, such as quality of life and length of hospital stay, are the focus in a wide array of clinical studies. However, participants in randomized trials for el…

stat.ME2024★ 4 cited

Analysis of cohort stepped wedge cluster-randomized trials with non-ignorable dropout via joint modeling

Alessandro Gasparini, Michael J. Crowther, Emiel O. Hoogendijk +2

Stepped wedge cluster-randomized trial (CRTs) designs randomize clusters of individuals to intervention sequences, ensuring that every cluster eventually transitions from a control…