9 papers
Design-based nested instrumental variable analysis
Zhe Chen, Xinran Li, Michael O. Harhay +1
Two binary instrumental variables (IVs) are nested if individuals who comply under one binary IV also comply under the other. This situation often arises when the two IVs represent…
Principal stratification with recurrent events truncated by a terminal event: A nested Bayesian nonparametric approach
Yuki Ohnishi, Michael O. Harhay, Guangyu Tong +1
Recurrent events often serve as key endpoints in clinical studies but may be prematurely truncated by terminal events such as death, creating selection bias and complicating causal…
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…
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…
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…
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…