An Introduction to Instrumental Variables – Part 2: Mendelian Randomisation
نویسندگان
چکیده
منابع مشابه
An introduction to instrumental variables--part 2: Mendelian randomisation.
In the first part of this series, it was highlighted how even though randomised controlled trials can provide robust evidence for therapeutic interventions, for many types of exposure it may not be either practical or ethical to randomise patients to such studies (see part 1). Instrumental variables (IV) analyses have been increasingly employed in recent times in epidemiology to investigate the...
متن کاملAn Introduction to Instrumental Variables Analysis: Part 1
There are several examples in the medical literature where the associations of treatment effects predicted by observational studies have been refuted by evidence from subsequent large-scale randomised trials. This is because of the fact that non-experimental studies are subject to confounding – and confounding cannot be entirely eliminated even if all known confounders have been measured in the...
متن کاملAn introduction to instrumental variables analysis: part 1.
There are several examples in the medical literature where the associations of treatment effects predicted by observational studies have been refuted by evidence from subsequent large-scale randomised trials. This is because of the fact that non-experimental studies are subject to confounding - and confounding cannot be entirely eliminated even if all known confounders have been measured in the...
متن کاملAn Introduction to Instrumental Variables
Instrumental variables (IVs) are used to control for confounding and measurement error in observational studies. They allow for the possibility of making causal inferences with observational data. Like propensity scores, IVs can adjust for both observed and unobserved confounding effects. Other methods of adjusting for confounding effects, which include stratification, matching and multiple reg...
متن کاملAn introduction to instrumental variables for epidemiologists.
Instrumental-variable (IV) methods were invented over 70 years ago, but remain uncommon in epidemiology. Over the past decade or so, non-parametric versions of IV methods have appeared that connect IV methods to causal and measurement-error models important in epidemiological applications. This paper provides an introduction to those developments, illustrated by an application of IV methods to ...
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ژورنال
عنوان ژورنال: Neuroepidemiology
سال: 2010
ISSN: 1423-0208,0251-5350
DOI: 10.1159/000321179