27 citations · 41 across the 8 of their papers we have counts for
8 papers
Multilevel Regression Modeling of Covariance Matrix Outcomes
Michelle Murphy Green, Xi Luo, Brian S. Caffo +1
Covariance matrix outcomes arise naturally in neuroimaging experiments to study brain functional connectivity. It is also of interest to understand how brain network organization v…
Longitudinal regression of covariance matrix outcomes
Yi Zhao, Brian S. Caffo, Xi Luo
In this study, a longitudinal regression model for covariance matrix outcomes is introduced. The proposal considers a multilevel generalized linear model for regressing covariance…
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…
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),…