11 papers · 1 filter
Calibrated Bayesian inference for overall and subgroup-specific causal effects in stepped-wedge cluster-randomized trials
Ruyi Liu, Yuki Ohnishi, Xi Fang +2
Stepped-wedge cluster-randomized trials (SW-CRTs) randomly assign clusters to sequences that determine when each cluster switches from control to intervention. Conventional Bayesia…
Doubly robust estimation of while-alive estimands in individually-randomized and cluster-randomized trials
Xi Fang, Da Zhao, Fan Li
Randomized trials in chronic disease settings often measure treatment benefit through recurrent non-fatal events that are truncated by death, where conventional summaries either di…
Statistical inference with win statistics in cluster-randomized trials with hierarchical composite outcomes
Xi Fang, Guangyu Tong, Yuan Huang +3
Win statistics have become increasingly popular for analyzing hierarchical composite endpoints in clinical trials. The win ratio, win odds, net benefit, and desirability of outcome…
Leveraging machine learning to estimate individualized treatment effects in cluster-randomized trials
Changjun Li, Xi Fang, Michael O. Harhay +4
Cluster-randomized trials (CRTs) are widely used to evaluate interventions delivered at the clinic, practice, or community level. Although standard analyses typically target averag…
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…
Doubly robust estimators of the restricted mean time in favor estimands in individual- and cluster-randomized trials
Xi Fang, Bingkai Wang, Guangyu Tong +3
Progressive multi-state survival outcomes are common in trials with recurrent or sequential events and require treatment effect estimands that remain interpretable without proporti…
Estimands and doubly robust estimation for cluster-randomized trials with survival outcomes
Xi Fang, Bingkai Wang, Liangyuan Hu +1
Cluster-randomized trials (CRTs) are experimental designs where groups or clusters of participants, rather than the individual participants themselves, are randomized to interventi…
Sample size determination for win statistics in cluster-randomized trials
Xi Fang, Zhiqiang Cao, Fan Li
Composite endpoints are increasingly used in clinical trials to capture treatment effects across multiple or hierarchically ordered outcomes. Although inference procedures based on…
Model-robust standardization in stepped wedge cluster randomized trials
Xi Fang, Xueqi Wang, Patrick J. Heagerty +2
Stepped-wedge cluster-randomized trials (SW-CRTs) are widely used in healthcare and implementation science, enabling all clusters to receive the intervention through a staggered ro…
Model-robust standardization in cluster-randomized trials
Fan Li, Jiaqi Tong, Xi Fang +3
In cluster-randomized trials, generalized linear mixed models and generalized estimating equations have conventionally been the default analytic methods for estimating the average…
While-alive regression analysis of composite survival endpoints
Xi Fang, Hajime Uno, Fan Li
Composite endpoints, which combine two or more distinct outcomes, are frequently used in clinical trials to enhance the event rate and improve the statistical power. In the recent…