86 citations · 307 across the 40 of their papers we have counts for
25 papers · 1 filter
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…
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…
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…
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…
Semi-supervised Approach to Event Time Annotation Using Longitudinal Electronic Health Records
Liang Liang, Jue Hou, Hajime Uno +3
Large clinical datasets derived from insurance claims and electronic health record (EHR) systems are valuable sources for precision medicine research. These datasets can be used to…
On the Evaluation of Surrogate Markers in Real World Data Settings
Larry Han, Xuan Wang, Tianxi Cai
Shortcomings of randomized clinical trials are pronounced in urgent health crises, when rapid identification of effective treatments is critical. Leveraging short-term surrogates i…
A new weighting method when not all the events are selected as cases in a nested case-control study
Qian M. Zhou, Xuan Wang, Yingye Zheng +1
Nested case-control (NCC) is a sampling method widely used for developing and evaluating risk models with expensive biomarkers on large prospective cohort studies. The biomarker va…
Risk Prediction with Imperfect Survival Outcome Information from Electronic Health Records
Stephanie F. Chan, Jue Hou, Xuan Wang +1
Readily available proxies for time of disease onset such as time of the first diagnostic code can lead to substantial risk prediction error if performing analyses based on poor pro…
Augmented Transfer Regression Learning with Semi-non-parametric Nuisance Models
Molei Liu, Yi Zhang, Katherine P Liao +1
In contemporary statistical learning, covariate shift correction plays an important role in transfer learning when distribution of the testing data is shifted from the training dat…
Integrative High Dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints
Molei Liu, Yin Xia, Kelly Cho +1
Identifying informative predictors in a high dimensional regression model is a critical step for association analysis and predictive modeling. Signal detection in the high dimensio…
Prior Adaptive Semi-supervised Learning with Application to EHR Phenotyping
Yichi Zhang, Molei Liu, Matey Neykov +1
Electronic Health Records (EHR) data, a rich source for biomedical research, have been successfully used to gain novel insight into a wide range of diseases. Despite its potential,…
Optimal Statistical Inference for Individualized Treatment Effects in High-dimensional Models
Tianxi Cai, Tony Cai, Zijian Guo
The ability to predict individualized treatment effects (ITEs) based on a given patient's profile is essential for personalized medicine. We propose a hypothesis testing approach t…
Individual Data Protected Integrative Regression Analysis of High-dimensional Heterogeneous Data
Tianxi Cai, Molei Liu, Yin Xia
Evidence-based decision making often relies on meta-analyzing multiple studies, which enables more precise estimation and investigation of generalizability. Integrative analysis of…
Spherical Regression under Mismatch Corruption with Application to Automated Knowledge Translation
Xu Shi, Xiaoou Li, Tianxi Cai
Motivated by a series of applications in data integration, language translation, bioinformatics, and computer vision, we consider spherical regression with two sets of unit-length…
Multi-view Banded Spectral Clustering with Application to ICD9 Clustering
Luwan Zhang, Katherine Liao, Issac Kohane +1
Despite recent development in methodology, community detection remains a challenging problem. Existing literature largely focuses on the standard setting where a network is learned…
Robust and Efficient Semi-Supervised Estimation of Average Treatment Effects with Application to Electronic Health Records Data
David Cheng, Ashwin Ananthakrishnan, Tianxi Cai
We consider the problem of estimating the average treatment effect (ATE) in a semi-supervised learning setting, where a very small proportion of the entire set of observations are…
Variance Components Genetic Association Test for Zero-inflated Count Outcomes
Matthew Goodman, Lori Chibnik, Tianxi Cai
Commonly in biomedical research, studies collect data in which an outcome measure contains informative excess zeros; for example when observing the burden of neuritic plaques in br…
Semi-Supervised Approaches to Efficient Evaluation of Model Prediction Performance
Jessica Gronsbell, Tianxi Cai
In many modern machine learning applications, the outcome is expensive or time-consuming to collect while the predictor information is easy to obtain. Semi-supervised learning (SSL…
Functional principal variance component testing for a genetic association study of HIV progression
Denis Agniel, Wen Xie, Myron Essex +1
HIV-1C is the most prevalent subtype of HIV-1 and accounts for over half of HIV-1 infections worldwide. Host genetic influence of HIV infection has been previously studied in HIV-1…
Estimating Average Treatment Effects with a Double-Index Propensity Score
David Cheng, Abhishek Chakrabortty, Ashwin N. Ananthakrishnan +1
We consider estimating average treatment effects (ATE) of a binary treatment in observational data when data-driven variable selection is needed to select relevant covariates from…
Surrogate Aided Unsupervised Recovery of Sparse Signals in Single Index Models for Binary Outcomes
Abhishek Chakrabortty, Matey Neykov, Raymond Carroll +1
We consider the recovery of regression coefficients, denoted by , for a single index model (SIM) relating a binary outcome to a set of possibly high dimensional…
Efficient and Adaptive Linear Regression in Semi-Supervised Settings
Abhishek Chakrabortty, Tianxi Cai
We consider the linear regression problem under semi-supervised settings wherein the available data typically consists of: (i) a small or moderate sized 'labeled' data, and (ii) a…
Evaluating Surrogate Marker Information using Censored Data
Layla Parast, Tianxi Cai, Lu Tian
Given the long follow-up periods that are often required for treatment or intervention studies, the potential to use surrogate markers to decrease the required follow-up time is a…
Estimation and testing for multiple regulation of multivariate mixed outcomes
Denis Agniel, Katherine P. Liao, Tianxi Cai
Considerable interest has recently been focused on studying multiple phenotypes simultaneously in both epidemiological and genomic studies, either to capture the multidimensionalit…