Regression modelCausal
Mendelian Randomization
Mendelian randomization is a method for estimating causal effects of exposures on outcomes using genetic variants as instrumental variables. Introduced by George Davey Smith in the 1990s, it exploits Mendel's law of segregation to remove confounding bias. It has become a cornerstone technique in epidemiological causal inference.
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Sources
- Davey Smith, G., & Hemani, G. (2014). Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Human Molecular Genetics, 23(R1), R89-R98. DOI: 10.1093/hmg/ddu328 ↗
- Hemani, G., Bowden, J., & Davey Smith, G. (2018). Evaluating the potential role of pleiotropy in Mendelian randomization studies. European Journal of Epidemiology, 33(9), 867-876. DOI: 10.1007/s10654-018-0746-6 ↗
- Morrison, J., Knoblauch, N., Marcus, J. H., Stephens, M., & He, X. (2020). Mendelian randomization accounting for sample overlap. Nature Communications, 11(1), 574. DOI: 10.1038/s41467-019-13870-3 ↗