activity
20182026
most citedHigh Dimensional M-Estimation with Missing Outcomes: A Semi-Parametric Framework

8 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2026

Assessment of evidence against homogeneity in exhaustive subgroup treatment effect plots

Björn Bornkamp, Jiarui Lu, Frank Bretz

Exhaustive subgroup treatment effect plots are constructed by displaying all subgroup treatment effects of interest against subgroup sample size, providing a useful overview of the…

stat.AP2024★ 3 cited

WATCH: A Workflow to Assess Treatment Effect Heterogeneity in Drug Development for Clinical Trial Sponsors

Konstantinos Sechidis, Sophie Sun, Yao Chen +8

This paper proposes a Workflow for Assessing Treatment effeCt Heterogeneity (WATCH) in clinical drug development targeted at clinical trial sponsors. WATCH is designed to address t…

stat.ME2019★ 8 cited

High Dimensional M-Estimation with Missing Outcomes: A Semi-Parametric Framework

Abhishek Chakrabortty, Jiarui Lu, T. Tony Cai +1

We consider high dimensional -estimation in settings where the response is possibly missing at random and the covariates can be high dimensiona…

stat.ME2019

Hypothesis Testing in High-Dimensional Instrumental Variables Regression with an Application to Genomics Data

Jiarui Lu, Hongzhe Li

Gene expression and phenotype association can be affected by potential unmeasured confounders from multiple sources, leading to biased estimates of the associations. Since genetic…

stat.ME2018★ 6 cited

Generalized Linear Models with Linear Constraints for Microbiome Compositional Data

Jiarui Lu, Pixu Shi, Hongzhe Li

Motivated by regression analysis for microbiome compositional data, this paper considers generalized linear regression analysis with compositional covariates, where a group of line…