40 citations · 70 across the 14 of their papers we have counts for
14 papers
Efficient Estimation of Average Treatment Effect on the Treated under Endogenous Treatment Assignment
Trinetri Ghosh, Jiawei Shan, Menggang Yu +1
In this paper, we consider estimation of average treatment effect on the treated (ATT), an interpretable and relevant causal estimand to policy makers when treatment assignment is…
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…
Sufficient Dimension Reduction for Populations with Structured Heterogeneity
Jared D. Huling, Menggang Yu
A key challenge in building effective regression models for large and diverse populations is accounting for patient heterogeneity. An example of such heterogeneity is in health sys…
Policy Learning for Optimal Individualized Dose Intervals
Guanhua Chen, Xiaomao Li, Menggang Yu
We study the problem of learning individualized dose intervals using observational data. There are very few previous works for policy learning with continuous treatment, and all of…
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…
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…
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…
Studentized Permutation Method for Comparing Restricted Mean Survival Times with Small Sample from Randomized Trials
Marc Ditzhaus, Menggang Yu, Jin Xu
Recent observations, especially in cancer immunotherapy clinical trials with time-to-event outcomes, show that the commonly used proportial hazard assumption is often not justifiab…
Relative Contrast Estimation and Inference for Treatment Recommendation
Muxuan Liang, Menggang Yu
When there are resource constraints, it is important to rank or estimate treatment benefits according to patient characteristics. This facilitates prioritization of assigning diffe…
Subgroup Identification Using the personalized Package
Jared D. Huling, Menggang Yu
A plethora of disparate statistical methods have been proposed for subgroup identification to help tailor treatment decisions for patients. However a majority of them do not have c…
A Semiparametric Approach to Model Effect Modification
Muxuan Liang, Menggang Yu
One fundamental statistical question for research areas such as precision medicine and health disparity is about discovering effect modification of treatment or exposure by observe…
Group variable selection via convex Log-Exp-Sum penalty with application to a breast cancer survivor study
Zhigeng Geng, Sijian Wang, Menggang Yu +3
In many scientific and engineering applications, covariates are naturally grouped. When the group structures are available among covariates, people are usually interested in identi…
Asymptotic theory for the semiparametric accelerated failure time model with missing data
Bin Nan, John D. Kalbfleisch, Menggang Yu
We consider a class of doubly weighted rank-based estimating methods for the transformation (or accelerated failure time) model with missing data as arise, for example, in case-coh…