activity
20142022
most citedEfficient augmentation and relaxation learning for individualized treatment rules using observational data

78 citations · 206 across the 26 of their papers we have counts for

collaborators

28 papers

stat.ME2022

Two-stage Hypothesis Tests for Variable Interactions with FDR Control

Jingyi Duan, Yang Ning, Xi Chen +1

In many scenarios such as genome-wide association studies where dependences between variables commonly exist, it is often of interest to infer the interaction effects in the model.…

stat.ME2022★ 1 cited

Inference in High-dimensional Multivariate Response Regression with Hidden Variables

Xin Bing, Wei Cheng, Huijie Feng +1

This paper studies the inference of the regression coefficient matrix under multivariate response linear regressions in the presence of hidden variables. A novel procedure for cons…

stat.ML2021★ 1 cited

Optimal Variable Clustering for High-Dimensional Matrix Valued Data

Inbeom Lee, Siyi Deng, Yang Ning

Matrix valued data has become increasingly prevalent in many applications. Most of the existing clustering methods for this type of data are tailored to the mean model and do not a…

stat.ME2021★ 4 cited

Optimal Covariate Balancing Conditions in Propensity Score Estimation

Jianqing Fan, Kosuke Imai, Inbeom Lee +3

Inverse probability of treatment weighting (IPTW) is a popular method for estimating the average treatment effect (ATE). However, empirical studies show that the IPTW estimators ca…

stat.ME2021

Test of Significance for High-dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference

Huijie Feng, Jingyi Duan, Yang Ning +1

This work is motivated by learning the individualized minimal clinically important difference, a vital concept to assess clinical importance in various biomedical studies. We formu…

math.ST2021★ 1 cited

On the global identifiability of logistic regression models with misclassified outcomes

Rui Duan, Yang Ning, Jiasheng Shi +3

In the last decade, the secondary use of large data from health systems, such as electronic health records, has demonstrated great promise in advancing biomedical discoveries and i…