6 citations · 11 across the 6 of their papers we have counts for
7 papers
Estimate Time-Varying Exposure Effects via Ensemble Learning-based Marginal Structural Model with Application to Adolescent Cognitive Development Study
Zhiwei Zhao, Chixiang Chen, Shuo Chen
Evaluating the effects of time-varying exposures is essential for longitudinal studies. The effect estimation becomes increasingly challenging when dealing with hundreds of time-de…
A New Integrative Learning Framework for Integrating Multiple Secondary Outcomes into Primary Outcome Analysis: A Case Study on Liver Health
Daxuan Deng, Peisong Han, Shuo Chen +2
In the era of big data, secondary outcomes have become increasingly important alongside primary outcomes. These secondary outcomes, which can be derived from traditional endpoints…
Modeling Interconnected Modules in Multivariate Outcomes: Evaluating the Impact of Alcohol Intake on Plasma Metabolomics
Yifan Yang, Chixiang Chen, Hwiyoung Lee +2
Alcohol consumption has been shown to influence cardiovascular mechanisms in humans, leading to observable alterations in the plasma metabolomic profile. Regression models are comm…
Hypothesis testing under uniform-block covariance structures
Yifan Yang, Shuo Chen, Ming Wang
A block covariance structure is widely observed across large-scale and high-dimensional datasets in diverse fields such as biology, medicine, engineering, economics, and finance. T…
An Efficient Data Integration Scheme for Synthesizing Information from Multiple Secondary Datasets for the Parameter Inference of the Main Analysis
Chixiang Chen, Ming Wang, Shuo Chen
Many observational studies and clinical trials collect various secondary outcomes that may be highly correlated with the primary endpoint. These secondary outcomes are often analyz…
Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior
Shuoli Chen, Kejun He, Shiyuan He +2
Tensor regression methods have been widely used to predict a scalar response from covariates in the form of a multiway array. In many applications, the regions of tensor covariates…
Covariance Matrix Estimation for High-Throughput Biomedical Data with Interconnected Communities
Yifan Yang, Chixiang Chen, Shuo Chen
Estimating a covariance matrix is central to high-dimensional data analysis. Empirical analyses of high-dimensional biomedical data, including genomics, proteomics, microbiome, and…