4 papers
Bayesian Structured Mediation Analysis With Unobserved Confounders
Yuliang Xu, Shu Yang, Jian Kang
We explore methods to reduce the impact of unobserved confounders on the causal mediation analysis of high-dimensional mediators with spatially smooth structures, such as brain ima…
Scalable Bayesian Image-on-Scalar Regression for Population-Scale Neuroimaging Data Analysis
Yuliang Xu, Timothy D. Johnson, Thomas E. Nichols +1
Bayesian Image-on-Scalar Regression (ISR) provides flexible, uncertainty-aware neuroimaging analysis. However, applying ISR to large-scale datasets such as the UK Biobank is challe…
Scalable Scalar-on-Image Cortical Surface Regression with a Relaxed-Thresholded Gaussian Process Prior
Anna Menacher, Thomas E. Nichols, Timothy D. Johnson +1
In addressing the challenge of analysing the large-scale Adolescent Brain Cognition Development (ABCD) fMRI dataset, involving over 5,000 subjects and extensive neuroimaging data,…
Bayesian Image Mediation Analysis
Yuliang Xu, Timothy D Johnson, Mary Heitzeg +1
Mediation analysis aims to separate the indirect effect through mediators from the direct effect of the exposure on the outcome. It is challenging to perform mediation analysis wit…