Mendelian Randomisation as an Instrumental Variable Approach to Causal Inference
Vanessa Didelez (University of Bristol)
Friday 28th October, 2011 15:00-16:00 Maths 203
In epidemiology we often want to estimate the causal effect of an exposure on a health outcome based on observational data, where the possibility of unobserved confounding cannot be excluded. To deal with this problem, it has recently become popular to use a technique called Mendelian randomisation, where it is exploited that the exposure is associated with a genetic variant, which can be assumed to be unaffected by the same confounding factors and which makes it suitable as a so-called instrumental variable. In my talk, this technique is illustrated with various examples, in particular with the effect of alcohol consumption on blood pressure / hypertension. Different methods of using an instrumental variable to estimate the causal effect on a binary outcome are compared based on their theoretical properties as well as by simulation. Finally, it will be discussed if a Bayesian approach is useful in the context of Mendelian randomisation.
Didelez and Sheehan (2007). Mendelian randomisation as an instrumental variable approach to causal inference, Statistical Methods in Medical Research, 16, 309-330.
Didelez, Meng and Sheehan (2010). Assumptions of IV methods for observational epidemiology, Statistical Science, 25, 22-40.
Palmer, Sterne, Harbord, Lawlor, Sheehan, Meng, Granell, Davey Smith, Didelez (2011). Instrumental variable estimation of causal risk ratios and causal odds ratios in Mendelian randomization analyses, The American Journal of Epidemiology, 173 (12).