A0874
Title: On PC adjustments for high dimensional association studies
Authors: Rajarshi Mukherjee - Harvard T.H. Chan School of Public Health (United States) [presenting]
Abstract: The focus is on the effect of Principal Component (PC) adjustments while inferring the effects of variables on outcomes. This is motivated by the EIGENSTRAT procedure in genetic association studies where one performs PC adjustment to account for population stratification. We consider simple statistical models to obtain an asymptotically precise understanding of when such PC adjustments are supposed to work. We also verify these results through extensive numerical experiments.
