32 citations · 53 across the 14 of their papers we have counts for
10 papers · 1 filter
Sliced Distributional Balancing
Haoran Zhang, Guanhua Chen, Chan Park
A popular class of causal inference methods addresses confounding through weighting, which reweights treated and control groups to balance their covariate distributions without usi…
Causal Generalization of Continuous Treatment Effects under Covariate Shift
Jay Jojo Cheng, Guanhua Chen
Average dose-response functions are widely used to summarize causal effects of continuous treatments, but most existing methods assume that the observed sample represents the targe…
A reluctant additive model framework for interpretable nonlinear individualized treatment rules
Jacob M. Maronge, Jared D. Huling, Guanhua Chen
Individualized treatment rules (ITRs) for treatment recommendation is an important topic for precision medicine as not all beneficial treatments work well for all individuals. Inte…
Personalized Two-sided Dose Interval
Chan Park, Guanhua Chen, Menggang Yu
In fields such as medicine and social sciences, the goal of treatment is often to maintain the outcome of interest within a desirable range rather than to optimize its value. To ac…
Entropy Balancing for Causal Generalization with Target Sample Summary Information
Rui Chen, Guanhua Chen, Menggang Yu
In this paper, we focus on estimating the average treatment effect (ATE) of a target population when individual-level data from a source population and summary-level data (e.g., fi…
Independence weights for causal inference with continuous treatments
Jared D. Huling, Noah Greifer, Guanhua Chen
Studying causal effects of continuous treatments is important for gaining a deeper understanding of many interventions, policies, or medications, yet researchers are often left wit…
A Generalizability Score for Aggregate Causal Effect
Rui Chen, Guanhua Chen, Menggang Yu
Scientists frequently generalize population level causal quantities such as average treatment effect from a source population to a target population. When the causal effects are he…
Causal inference methods for combining randomized trials and observational studies: a review
Bénédicte Colnet, Imke Mayer, Guanhua Chen +6
With increasing data availability, causal effects can be evaluated across different data sets, both randomized controlled trials (RCTs) and observational studies. RCTs isolate the…
Constructing Stabilized Dynamic Treatment Regimes for Censored Data
Ying-Qi Zhao, Ruoqing Zhu, Guanhua Chen +1
Stabilized dynamic treatment regimes are sequential decision rules for individual patients that not only adaptive throughout the disease progression but also remain consistent over…
Biclustering Via Sparse Clustering
Qian Liu, Guanhua Chen, Michael R. Kosorok +1
In many situations it is desirable to identify clusters that differ with respect to only a subset of features. Such clusters may represent homogeneous subgroups of patients with a…