activity
20222024
most citedInference-based statistical network analysis uncovers star-like brain functional architectures for internalizing psychopathology in children

2 citations · 4 across the 10 of their papers we have counts for

collaborators

10 papers

stat.AP2024★ 1 cited

Cost efficiency of fMRI studies using resting-state vs task-based functional connectivity

Xinzhi Zhang, Leslie A Hulvershorn, Todd Constable +2

We investigate whether and how we can improve the cost efficiency of neuroimaging studies with well-tailored fMRI tasks. The comparative study is conducted using a novel network sc…

stat.AP2024

Supervised brain node and network construction under voxel-level functional imaging

Wanwan Xu, Selena Wang, Chichun Tan +5

Recent advancements in understanding the brain's functional organization related to behavior have been pivotal, particularly in the development of predictive models based on brain…

stat.ME2024

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…

stat.ME2023

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…

stat.ME2023★ 2 cited

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…

stat.ME2023★ 1 cited

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…

stat.ME2023

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…

stat.ME2023

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…

stat.ME2022

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…

stat.ME2022

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…