Mendelian Randomization with a Continuous Outcome

Introduction This module computes the sample size and power of the causal effect in Mendelian randomization studies with a continuous outcome. This analysis is used in observational studies where clinical trials are not possible. Analogous to randomized clinical trials (RCT), Mendelian randomization (MR) divides subjects into two or more groups. However, MR uses a genetic variable, such as the state of a certain gene, to form the groups. The state of the gene is assumed to be random. Using two-stage least squares and making several assumptions, the causal impact of an exposure variable on the outcome variable can be measured. For further reading, we recommend the book by Burgess and Thompson (2015) which is completely devoted to this topic. We have used the paper by Brion, Shakhbazov, and Visscher (2013) for sample size formulas. We also recommend the papers by Burgess (2014) and Freeman, Cowling, and Schooling (2013).