Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/2353
Title: Mendelian Randomization as an Instrumental Variable Approach to Causal Inference
Authors: Didelez, Vanessa
Sheehan, Nuala A.
First Published: 2007
Citation: Statistical Methods in Medical Research, 2007, 16 (4), pp.309-330
Abstract: In epidemiological research, the causal effect of a modifiable phenotype or exposure on a disease is often of public health interest. Randomized controlled trials to investigate this effect are not always possible and inferences based on observational data can be confounded. However, if we know of a gene closely linked to the phenotype without direct effect on the disease, it can often be reasonably assumed that the gene is not itself associated with any confounding factors — a phenomenon called Mendelian randomization. These properties define an instrumental variable and allow estimation of the causal effect, despite the confounding, under certain model restrictions. In this paper, we present a formal framework for causal inference based on Mendelian randomization and suggest using directed acyclic graphs to check model assumptions by visual inspection. This framework allows us to address limitations of the Mendelian randomization technique that have often been overlooked in the medical literature.
DOI Link: 10.1177/0962280206077743
ISSN: 0962-2802
Links: http://smm.sagepub.com/content/16/4/309
http://hdl.handle.net/2381/2353
Type: Article
Description: Metadata only entry
Appears in Collections:Published Articles, Dept. of Health Sciences
Published Articles, Dept. of Genetics

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