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

International Journal of Epidemiology · 2018 · Vol. 48(3) · pp. 713–727
Eleanor SandersonGeorge Davey SmithFrank WindmeijerJack Bowden

Abstract

MVMR analysis consistently estimates the direct causal effect of an exposure, or exposures, of interest and provides a powerful tool for determining causal effects in a wide range of scenarios with either individual- or summary-level data.

Genetic Associations and EpidemiologyAdvanced Causal Inference TechniquesObesity, Physical Activity, DietMendelian randomizationConfoundingColliderCausal inferenceMultivariable calculusInstrumental variableEconometricsSample (material)StatisticsSample size determination

MeSH terms

AdultAgedCognitionEducational StatusFemaleHumansMaleMiddle AgedBody Mass IndexMultivariate AnalysisLeast-Squares AnalysisModels, EconometricMendelian Randomization Analysis

Funding

  • University of Bristol
  • Medical Research Council
Citations
1,128
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