8 papers
Orthogonal double residual learning for optimal individualized treatment rules
Jiaqi Tong, Fan Li
Individualized treatment rules (ITRs) map baseline characteristics to treatment recommendations, with the optimal ITR maximizing expected reward or policy welfare. Indirect methods…
Doubly cross-fit debiased machine learning of heterogeneous treatment effects under principal stratification
Jiaqi Tong, Fan Li
Principal stratification provides a foundational framework for causal inference with intermediate outcomes by defining causal effects within subpopulations, yet existing work has l…
Causal mediation in cluster-randomized trials with multiple mediators: spillover-aware decomposition, identification, and semiparametric efficient inference
Jiaqi Tong, Chao Cheng, Fan Li
Causal mediation analysis in cluster-randomized trials (CRTs) is complicated by the presence of multiple mediators, intracluster correlation, and within-cluster interference. Exist…
Optimal Sample Size Calculation in Cost-Effectiveness Longitudinal Cluster Randomized Trials
Hao Wang, Jingxia Liu, Drew B. Cameron +4
Longitudinal cluster randomized trials (L-CRTs) are increasingly used to evaluate the cost-effectiveness of healthcare interventions across multiple assessment periods, yet design…
On the permutation equivariance principle for causal estimands
Jiaqi Tong, Fan Li
In many causal inference problems, multiple action variables, such as factors, mediators, or network units, often share a common causal role yet lack a natural ordering. To avoid a…
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…