Mendelian Randomization, 2nd Edition

5

Estimating a causal effect from summarized data

In the previous chapter, we showed that the ratio method for a single genetic variant could be performed using summarized data on genetic associations with the exposure and with the outcome. In this chapter, we introduce the inverse-variance weighted method, which combines summarized data for multiple variants into a single causal estimate. We show that estimates from the inverse-variance weighted method are the same as those obtained from the two-stage method, and hence most efficiently combine information from multiple valid instrumental variables.

5.1 Motivating example: interleukin-1 and cardiovascular diseases

In 2015, Daniel Freitag was the lead author for a Mendelian randomization ...