On PC Adjustments for High Dimensional Association Studies

Rajarshi Mukherjee – Harvard University


We consider 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 asymptotically precise understanding of when such PC adjustments are supposed to work. We also verify these results through extensive numerical experiments.

These results are based on joint work with Sohom Bhattacharya (Stanford University) and Rounak Dey (Harvard T.H. Chan School of Public Health).