8 papers
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…
Sharp bounds for population and principal effects under latent sequential ignorability
Yuki Ohnishi
Treatment decisions are often sequential and depend on information absent from the recorded history. Latent sequential ignorability models such assignment by assuming that baseline…
The Resolution of Causal Heterogeneity
Yuki Ohnishi, Fan Li
Causal subgroup analyses often report a small number of groups summarizing treatment effect heterogeneity, as if that number were a well-defined estimand. Outside genuinely latent…
Calibrated Bayes analysis of cluster-randomized trials
Ruyi Liu, Joshua L. Warren, Yuki Ohnishi +3
In cluster-randomized trials (CRTs), entire clusters of individuals are randomized to treatment, and outcomes within a cluster are typically correlated. While frequentist approache…
Identification and estimation of causal mechanisms in cluster-randomized trials with post-treatment confounding using Bayesian nonparametrics
Yuki Ohnishi, Michael J. Daniels, Lei Yang +1
Causal mediation analysis in cluster-randomized trials (CRTs) is essential for explaining how cluster-level interventions affect individual outcomes, yet it is complicated by inter…
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…
A Bayesian nonparametric approach to mediation and spillover effects with multiple mediators in cluster-randomized trials
Yuki Ohnishi, Fan Li
Cluster randomized trials (CRTs) with multiple unstructured mediators present significant methodological challenges for causal inference due to within-cluster correlation, interfer…
Differentially Private Covariate Balancing Causal Inference
Yuki Ohnishi, Jordan Awan
Differential privacy is the leading mathematical framework for privacy protection, providing a probabilistic guarantee that safeguards individuals' private information when publish…