10 papers
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…
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…
Statistical inference with win statistics in cluster-randomized trials with composite outcomes
Xi Fang, Guangyu Tong, Yuan Huang +3
Win statistics have become increasingly popular for analyzing hierarchical composite endpoints in clinical trials, because they summarize treatment benefit through pairwise compari…
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…