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Weak‐instrument robust tests in two‐sample summary‐data Mendelian randomization
Author(s) -
Wang Sheng,
Kang Hyunseung
Publication year - 2022
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.13524
Subject(s) - mendelian randomization , instrumental variable , sample size determination , estimator , statistics , econometrics , type i and type ii errors , statistical power , sample (material) , computer science , statistical hypothesis testing , mathematics , genetic variants , biology , genetics , chemistry , chromatography , gene , genotype
Mendelian randomization (MR) has been a popular method in genetic epidemiology to estimate the effect of an exposure on an outcome using genetic variants as instrumental variables (IV), with two‐sample summary‐data MR being the most popular. Unfortunately, instruments in MR studies are often weakly associated with the exposure, which can bias effect estimates and inflate Type I errors. In this work, we propose test statistics that are robust under weak‐instrument asymptotics by extending the Anderson–Rubin, Kleibergen, and the conditional likelihood ratio test in econometrics to two‐sample summary‐data MR. We also use the proposed Anderson–Rubin test to develop a point estimator and to detect invalid instruments. We conclude with a simulation and an empirical study and show that the proposed tests control size and have better power than existing methods with weak instruments.