Statistical Methods for Mendelian Randomization

DOI
  • Orihara Shunichiro
    Department of Health Data Science, Tokyo Medical University
  • Hirano Keita
    School of Human Health Science, Graduate School of Medicine, Kyoto University

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Other Title
  • メンデルランダム化研究の統計手法

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Description

<p>Instrumental variable (IV) methods are widely applied in biometrics and related fields, offering potential solutions to problems associated with unmeasured confounders. Particularly, Mendelian randomization (MR), which uses single nucleotide polymorphisms (SNPs) as IVs, has garnered significant attention in recent years. In this review, we introduce MR and the statistical methods used, categorizing them into two types: one-sample MR and two-sample MR, with some illustrative examples. In onesample MR, the two-stage least squares (2SLS) estimator is commonly applied, while in two-sample MR, the inverse-variance weighted method is used. We also explore the relationship between these methods. Additionally, we discuss unique problems of MR, such as the weak instrument problem and the issue of invalid IVs, and present some current solutions. Furthermore, we address biometrics-specific topics applicable to binary outcomes and concerns regarding the applicability of 2SLS.</p>

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Details 詳細情報について

  • CRID
    1390867133865133696
  • DOI
    10.5691/jjb.46.1
  • ISSN
    21856494
    09184430
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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