activity
20102026
most citedEfficient and Adaptive Linear Regression in Semi-Supervised Settings

86 citations · 307 across the 40 of their papers we have counts for

collaborators

41 papers

stat.ME2026

Calibrated Estimation and Inference for Semiparametric Regression Models

Yuming Zhang, Yanyuan Ma, Tianxi Cai +2

We consider a broad class of semiparametric regression models in which the conditional distribution of the response takes the form , kno…

stat.ME2022★ 1 cited

Using a Surrogate with Heterogeneous Utility to Test for a Treatment Effect

Layla Parast, Tianxi Cai, Lu Tian

The primary benefit of identifying a valid surrogate marker is the ability to use it in a future trial to test for a treatment effect with shorter follow-up time or less cost. Howe…

stat.AP2022

Assessing the Most Vulnerable Subgroup to Type II Diabetes Associated with Statin Usage: Evidence from Electronic Health Record Data

Xinzhou Guo, Waverly Wei, Molei Liu +3

There have been increased concerns that the use of statins, one of the most commonly prescribed drugs for treating coronary artery disease, is potentially associated with the incre…

stat.ME2021★ 9 cited

Adaptive Combination of Randomized and Observational Data

David Cheng, Tianxi Cai

Data from both a randomized trial and an observational study are sometimes simultaneously available for evaluating the effect of an intervention. The randomized data typically allo…

math.ST2021

Finding the Optimal Dynamic Treatment Regime Using Smooth Fisher Consistent Surrogate Loss

Nilanjana Laha, Aaron Sonabend-W, Rajarshi Mukherjee +1

Large health care data repositories such as electronic health records (EHR) open new opportunities to derive individualized treatment strategies for complicated diseases such as se…

stat.ME2021★ 1 cited

Efficient and Robust Semi-supervised Estimation of ATE with Partially Annotated Treatment and Response

Jue Hou, Rajarshi Mukherjee, Tianxi Cai

A notable challenge of leveraging Electronic Health Records (EHR) for treatment effect assessment is the lack of precise information on important clinical variables, including the…