A0512
Title: Controlling false discovery rate for mediator selection using knockoff method
Authors: Runqiu Wang - University of Nebraska Medical Center (United States)
Ran Dai - University of Nebraska Medical Center (United States)
Jieqiong Wang - University of Nebraska Medical Center (United States)
Cheng Zheng - University of Nebraska Medical Center (United States) [presenting]
Abstract: There is a challenge in selecting high-dimensional mediators when the mediators have complex correlation structures and interactions. The high-dimensional mediator selection problem is framed into a series of hypothesis tests with composite nulls, and a powerful method is developed to control the false discovery rate (FDR) that has mild assumptions on the mediation model. The theoretical guarantee that the proposed method and algorithm achieve FDR control is shown. Extensive simulation results are presented to demonstrate the power and finite sample performance compared with existing methods. Lastly, the method is demonstrated for analyzing Alzheimer's Disease Neuroimaging Initiative (ADNI) data, in which the proposed method selects the volume of the hippocampus and amygdala, as well as some other important MRI-derived measures as mediators for the relationship between gender and dementia progression.
