Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators.

ABSTRACT: Mendelian randomization (MR) is a method for estimating the causal relationship between an exposure and an outcome using a genetic factor as an instrumental variable (IV) for the exposure. In the traditional MR setting, data on the IV, exposure, and outcome are available for all participants. However, obtaining complete exposure data may be difficult in some settings, due to high measurement costs or lack of appropriate biospecimens. We used simulated data sets to assess statistical power and bias for MR when exposure data are available for a subset (or an independent set) of participants. We show that obtaining exposure data for a subset of participants is a cost-efficient strategy, often having negligible effects on power in comparison with a traditional complete-data analysis. The size

SUBMITTER: Pierce BL 

PROVIDER: S-EPMC3783091 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature