By combining causal graphs and randomization inference, a formal justification for Mendelian randomization is given in the context of with-family studies.
Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel’s laws of inheritance and …
Mendelian randomization (MR) is a method for causal inference that utilizes the natural experiment in genetic inheritance. The idea of MR can be traced back to the dawn of modern statistics and genetics a century ago, although the terminology was not …
Mendelian randomization (MR) is a method for causal inference that utilizes the natural experiment in genetic inheritance. The idea of MR can be traced back to the dawn of modern statistics and genetics a century ago, although the terminology was not …
Mendelian Randomization (MR) is a popular method in epidemiology and genetics that uses genetic variation as instrumental variables for causal inference. Existing MR methods usually assume most genetic variants are valid instrumental variables that …
Sparsity is often used to improve the interpretability of a statistical analysis and/or reduce the variance of a statistical estimator. This talk will explore another aspect—the utility of sparsity in model identifiability through two problems …
A key assumption in Mendelian randomisation is that the relationship between the genetic instruments and the outcome is fully mediated by the exposure, known as the exclusion restriction assumption. However, in epidemiological studies, the exposure …