Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score

Abstract

We provide a comprehensive theoretical basis for two-sample summary-data Mendelian randomization. We find that horizontal pleiotropy is pervasive in MR studies. We propose a new method—robust adjusted profile score—that can consistently estimate the causal effect under pervasive balanced pleiotropy and is robust to occasional outliers.

Publication
Annals of Statistics (2020)
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