51 citations · 95 across the 12 of their papers we have counts for
10 papers · 1 filter
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…
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…
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…
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…
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…
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…
Demystifying estimands in cluster-randomised trials
Brennan C Kahan, Bryan Blette, Michael Harhay +4
Estimands can help clarify the interpretation of treatment effects and ensure that estimators are aligned to the study's objectives. Cluster randomised trials require additional at…
Using modified intention-to-treat as a principal stratum estimator for failure to initiate treatment
Brennan C Kahan, Ian R White, Mark Edwards +1
Background: A common intercurrent event affecting many trials is when some participants do not begin their assigned treatment. Many trials use a modified intention-to-treat (mITT)…
Leveraging baseline covariates to analyze small cluster-randomized trials with a rare binary outcome
Angela Y. Zhu, Nandita Mitra, Karla Hemming +2
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 a…
On the mixed-model analysis of covariance in cluster-randomized trials
Bingkai Wang, Michael O. Harhay, Jiaqi Tong +3
In the analyses of cluster-randomized trials, mixed-model analysis of covariance (ANCOVA) is a standard approach for covariate adjustment and handling within-cluster correlations.…