71 citations · 115 across the 10 of their papers we have counts for
10 papers
Regularized regression on compositional trees with application to MRI analysis
Bingkai Wang, Brian S. Caffo, Xi Luo +4
A compositional tree refers to a tree structure on a set of random variables where each random variable is a node and composition occurs at each non-leaf node of the tree. As a gen…
Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors
Yi Zhao, Bingkai Wang, Chin-Fu Liu +4
Brain segmentation at different levels is generally represented as hierarchical trees. Brain regional atrophy at specific levels was found to be marginally associated with Alzheime…
Principal Regression for High Dimensional Covariance Matrices
Yi Zhao, Brian S. Caffo, Xi Luo
This manuscript presents an approach to perform generalized linear regression with multiple high dimensional covariance matrices as the outcome. Model parameters are proposed to be…
B-Value and Empirical Equivalence Bound: A New Procedure of Hypothesis Testing
Yi Zhao, Brian S. Caffo, Joshua B. Ewen
In this study, we propose a two-stage procedure for hypothesis testing, where the first stage is conventional hypothesis testing and the second is an equivalence testing procedure…
Multimodal Neuroimaging Data Integration and Pathway Analysis
Yi Zhao, Lexin Li, Brian S. Caffo
With fast advancements in technologies, the collection of multiple types of measurements on a common set of subjects is becoming routine in science. Some notable examples include m…
Sparse Principal Component based High-Dimensional Mediation Analysis
Yi Zhao, Martin A. Lindquist, Brian S. Caffo
Causal mediation analysis aims to quantify the intermediate effect of a mediator on the causal pathway from treatment to outcome. With multiple mediators, which are potentially cau…
Functional Mediation Analysis with an Application to Functional Magnetic Resonance Imaging Data
Yi Zhao, Xi Luo, Martin Lindquist +1
Causal mediation analysis is widely utilized to separate the causal effect of treatment into its direct effect on the outcome and its indirect effect through an intermediate variab…
Granger Mediation Analysis of Multiple Time Series with an Application to fMRI
Yi Zhao, Xi Luo
It becomes increasingly popular to perform mediation analysis for complex data from sophisticated experimental studies. In this paper, we present Granger Mediation Analysis (GMA),…
Pathway Lasso: Estimate and Select Sparse Mediation Pathways with High Dimensional Mediators
Yi Zhao, Xi Luo
In many scientific studies, it becomes increasingly important to delineate the causal pathways through a large number of mediators, such as genetic and brain mediators. Structural…
Estimating Causal Mediation Effects under Correlated Errors
Yi Zhao, Xi Luo
Causal mediation analysis usually requires strong assumptions, such as ignorability of the mediator, which may not hold in many social and scientific studies. Motivated by a multil…