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The instrumental variable (IV) method can remove bias because of unobserved confounding, but it is unclear to what extent the choice of the IV may affect the results.
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Instrumental variable methods are becoming increasingly popular because they seem to overcome the problem of unobserved confounding in observational studies [ 25].
However, this still leaves the possibility of unobserved confounding.
Thus, we did not find any plausible evidence of this particular form of unobserved confounding.
Negative controls are sometimes used in epidemiologic practice to detect the presence of unobserved confounding.
Some degree of unobserved confounding is almost certainly present in most observational studies.
Although this assumption may suffice to detect the presence of unobserved confounding, it does not suffice to identify the causal effect of A on Y.
Secondly, we assessed the strength of unobserved confounding that would be required to alter our findings in relation to a dichotomised version of the our primary endpoint.
To have missed such a reduction, the amount of unobserved confounding would have had to be greater than is realistic for clinical variables.
For many IV specifications, the corresponding OLS estimates differ appreciably, consistent with the presence of unobserved confounding and homophily bias in the OLS specifications.
Third, as with all observational studies, the relationship observed between mortality and unstable housing may be under the influence of unobserved confounding.
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