An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings | Zendy

Eleanor Sanderson | Zendy; George Davey Smith | Zendy; Frank Windmeijer | Zendy; Jack Bowden | Zendy

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An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings

Author(s) -

Eleanor Sanderson,

George Davey Smith,

Frank Windmeijer,

Jack Bowden

Publication year - 2018

Publication title -

international journal of epidemiology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.406

H-Index - 208

eISSN - 1464-3685

pISSN - 0300-5771

DOI - 10.1093/ije/dyy262

Subject(s) - mendelian randomization , confounding , collider , causal inference , multivariable calculus , instrumental variable , econometrics , sample (material) , statistics , sample size determination , biobank , medicine , causality (physics) , range (aeronautics) , bioinformatics , mathematics , biology , genetics , genetic variants , engineering , physics , chemistry , chromatography , quantum mechanics , control engineering , gene , genotype , nuclear physics , aerospace engineering

Mendelian randomization (MR) is a powerful tool in epidemiology that can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilizing genetic variants that are instrumental variables (IVs) for the exposure. This has been extended to multivariable MR (MVMR) to estimate the effect of two or more exposures on an outcome.

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