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Mendelian Randomisation and Causal Inference in Observational Epidemiology

Author

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  • Nuala A Sheehan
  • Vanessa Didelez
  • Paul R Burton
  • Martin D Tobin

Abstract

Nuala Sheehan and colleagues describe how Mendelian randomization provides an alternative way of dealing with the problems of observational studies, especially confounding.

Suggested Citation

  • Nuala A Sheehan & Vanessa Didelez & Paul R Burton & Martin D Tobin, 2008. "Mendelian Randomisation and Causal Inference in Observational Epidemiology," PLOS Medicine, Public Library of Science, vol. 5(8), pages 1-6, August.
    • Handle: RePEc:plo:pmed00:0050177
    DOI: 10.1371/journal.pmed.0050177
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    Cited by:

    1. Nicola Barban & Elisabetta De Cao & Sonia Oreffice & Climent Quintana-Domeque, 2016. "Assortative Mating on Education: A Genetic Assessment," Working Papers 2016-034, Human Capital and Economic Opportunity Working Group.
    2. Noémi Kreif & Richard Grieve & M. Zia Sadique, 2013. "Statistical Methods For Cost‐Effectiveness Analyses That Use Observational Data: A Critical Appraisal Tool And Review Of Current Practice," Health Economics, John Wiley & Sons, Ltd., vol. 22(4), pages 486-500, April.
    3. Lilah M. Besser & Willa D. Brenowitz & Oanh L. Meyer & Serena Hoermann & John Renne, 2021. "Methods to Address Self-Selection and Reverse Causation in Studies of Neighborhood Environments and Brain Health," IJERPH, MDPI, vol. 18(12), pages 1-19, June.
    4. Siqi Xu & Peng Wang & Wing Kam Fung & Zhonghua Liu, 2023. "A novel penalized inverse‐variance weighted estimator for Mendelian randomization with applications to COVID‐19 outcomes," Biometrics, The International Biometric Society, vol. 79(3), pages 2184-2195, September.
    5. Tanica Lyngdoh & Philippe Vuistiner & Pedro Marques-Vidal & Valentin Rousson & Gérard Waeber & Peter Vollenweider & Murielle Bochud, 2012. "Serum Uric Acid and Adiposity: Deciphering Causality Using a Bidirectional Mendelian Randomization Approach," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-8, June.
    6. Ciarrah Barry & Junxi Liu & Rebecca Richmond & Martin K Rutter & Deborah A Lawlor & Frank Dudbridge & Jack Bowden, 2021. "Exploiting collider bias to apply two-sample summary data Mendelian randomization methods to one-sample individual level data," PLOS Genetics, Public Library of Science, vol. 17(8), pages 1-26, August.
    7. Xiaobo Li & Yuqiong Li & Bei Song & Shujie Guo & Shaoli Chu & Nan Jia & Wenquan Niu, 2012. "Hematopoietically-Expressed Homeobox Gene Three Widely-Evaluated Polymorphisms and Risk for Diabetes: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-10, November.
    8. Barban, Nicola & De Cao, Elisabetta & Oreffice, Sonia & Quintana-Domeque, Climent, 2021. "The effect of education on spousal education: A genetic approach," Labour Economics, Elsevier, vol. 71(C).
    9. Lina Zgaga & Felix Agakov & Evropi Theodoratou & Susan M Farrington & Albert Tenesa & Malcolm G Dunlop & Paul McKeigue & Harry Campbell, 2013. "Model Selection Approach Suggests Causal Association between 25-Hydroxyvitamin D and Colorectal Cancer," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-11, May.
    10. Leandro Fornias Machado de Rezende & Maurício Rodrigues Lopes & Juan Pablo Rey-López & Victor Keihan Rodrigues Matsudo & Olinda do Carmo Luiz, 2014. "Sedentary Behavior and Health Outcomes: An Overview of Systematic Reviews," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-7, August.
    11. Black, Nicole & Hughes, Robert & Jones, Andrew M., 2018. "The health care costs of childhood obesity in Australia: An instrumental variables approach," Economics & Human Biology, Elsevier, vol. 31(C), pages 1-13.

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