36 citations · 38 across the 4 of their papers we have counts for
8 papers · 1 filter
A Framework for Understanding Selection Bias in Real-World Healthcare Data
Ritoban Kundu, Xu Shi, Jean Morrison +2
Using administrative patient-care data such as Electronic Health Records (EHR) and medical/ pharmaceutical claims for population-based scientific research has become increasingly c…
The Effect of Alcohol intake on Brain White Matter Microstructural Integrity: A New Causal Inference Framework for Incomplete Phenomic Data
Chixiang Chen, Shuo Chen, Zhenyao Ye +3
Although substance use, such as alcohol intake, is known to be associated with cognitive decline during aging, its direct influence on the central nervous system remains incomplete…
Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls
Erich Kummerfeld, Jaewon Lim, Xu Shi
Negative control variables are increasingly used to adjust for unmeasured confounding bias in causal inference using observational data. They are typically identified by subject ma…
Data Integration in Causal Inference
Xu Shi, Ziyang Pan, Wang Miao
Integrating data from multiple heterogeneous sources has become increasingly popular to achieve a large sample size and diverse study population. This paper reviews development in…
An Introduction to Proximal Causal Learning
Eric J Tchetgen Tchetgen, Andrew Ying, Yifan Cui +2
A standard assumption for causal inference from observational data is that one has measured a sufficiently rich set of covariates to ensure that within covariate strata, subjects a…
A general approach to detect gene (G)-environment (E) additive interaction leveraging G-E independence in case-control studies
Eric J. Tchetgen Tchetgen, Xu Shi, Tamar Sofer +1
It is increasingly of interest in statistical genetics to test for the presence of a mechanistic interaction between genetic (G) and environmental (E) risk factors by testing for t…