32 citations · 53 across the 14 of their papers we have counts for
15 papers
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…
Differentially Private Two-Stage Empirical Risk Minimization with Applications to Individualized Treatment Rule
Joowon Lee, Guanhua Chen
Differential privacy provides a formal framework for releasing statistical estimators that limit how much any single observation can influence the output, by injecting calibrated r…
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…
Meta-analysis of individualized treatment rules via sign-coherency
Jay Jojo Cheng, Jared D. Huling, Guanhua Chen
Medical treatments tailored to a patient's baseline characteristics hold the potential of improving patient outcomes while reducing negative side effects. Learning individualized t…
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…
Minimum Resource Threshold Policy Under Partial Interference
Chan Park, Guanhua Chen, Menggang Yu +1
When developing policies for prevention of infectious diseases, policymakers often set specific, outcome-oriented targets to achieve. For example, when developing a vaccine allocat…
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…
More Generalizable Models For Sepsis Detection Under Covariate Shift
Jifan Gao, Philip L. Mar, Guanhua Chen
Sepsis is a major cause of mortality in the intensive care units (ICUs). Early intervention of sepsis can improve clinical outcomes for sepsis patients. Machine learning models hav…
Robust Sample Weighting to Facilitate Individualized Treatment Rule Learning for a Target Population
Rui Chen, Jared D. Huling, Guanhua Chen +1
Learning individualized treatment rules (ITRs) is an important topic in precision medicine. Current literature mainly focuses on deriving ITRs from a single source population. We c…
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…