2 citations · 4 across the 10 of their papers we have counts for
8 papers · 1 filter
Bayesian thresholded modeling for integrating brain node and network predictors
Zhe Sun, Wanwan Xu, Tianxi Li +3
Progress in neuroscience has provided unprecedented opportunities to advance our understanding of brain alterations and their correspondence to phenotypic profiles. With data colle…
Bayesian pathway analysis over brain network mediators for survival data
Xinyuan Tian, Fan Li, Li Shen +2
Technological advancements in noninvasive imaging facilitate the construction of whole brain interconnected networks, known as brain connectivity. Existing approaches to analyze br…
Inference-based statistical network analysis uncovers star-like brain functional architectures for internalizing psychopathology in children
Selena Wang, Yunhe Liu, Wanwan Xu +2
To improve the statistical power for imaging biomarker detection, we propose a latent variable-based statistical network analysis (LatentSNA) that combines brain functional connect…
Mediation Analysis with Graph Mediator
Yixi Xu, Yi Zhao
This study introduces a mediation analysis framework when the mediator is a graph. A Gaussian covariance graph model is assumed for graph representation. Causal estimands and assum…
Density-on-Density Regression
Yi Zhao, Abhirup Datta, Bohao Tang +2
In this study, a density-on-density regression model is introduced, where the association between densities is elucidated via a warping function. The proposed model has the advanta…
Bayesian mixed model inference for genetic association under related samples with brain network phenotype
Xinyuan Tian, Yiting Wang, Selena Wang +2
Genetic association studies for brain connectivity phenotypes have gained prominence due to advances in non-invasive imaging techniques and quantitative genetics. Brain connectivit…
Covariance-on-Covariance Regression
Yi Zhao, Yize Zhao
A Covariance-on-Covariance regression model is introduced in this manuscript. It is assumed that there exists (at least) a pair of linear projections on outcome covariance matrices…
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…