Surrogate Variable Analysis for Multivariate Functional Responses in Imaging Data

Chao Huang, PhD, Candiate, Biostatistics, University of North Carolina at Chapel Hill

With the rapid growth of modern technology, many large-scale biomedical studies, e.g., Alzheimer's disease neuroimaging initiative (ADNI) study, have been conducted to collect massive datasets with large volumes of complex information from increasingly large cohorts.  Despite the numerous successes of biomedical studies, the imaging heterogeneity has posed many challenges in both data intergration and disease etiology.  Specifically, imaging heterogeneity often represents at three different levels: subject level, group level, and study level.  This talk mainly focuses on the heterogeneity at study level.