| authors | Martens, E.P.; Pestman, W.R.; Boer, A. de; Belitser, S.; Klungel, O.H. |
| source | Epidemiology, Volume: 17, Issue: 3 (2006), pp. 260-267 |
| full text | [Full text]
|
| publisher | Lippincott Williams & Wilkins |
| URL publisher | [Website publisher]
|
| document type | Article |
| version | Publisher version |
| disciplines | Biologie, Farmacie |
| abstract | To correct for confounding, the method of instrumental
variables (IV) has been proposed. Its use in medical literature is still
rather limited because of unfamiliarity or inapplicability. By introducing
the method in a nontechnical way, we show that IV in a
linear model is quite easy to understand and easy to apply once an
appropriate instrumental variable has been identified. We also point
out some limitations of the IV estimator when the instrumental
variable is only weakly correlated with the exposure. The IV
estimator will be imprecise (large standard error), biased when
sample size is small, and biased in large samples when one of the
assumptions is only slightly violated. For these reasons, it is advised
to use an IV that is strongly correlated with exposure. However, we
further show that under the assumptions required for the validity of
the method, this correlation between IV and exposure is limited. Its
maximum is low when confounding is strong, such as in case of
confounding by indication. Finally, we show that in a study in which
strong confounding is to be expected and an IV has been used that
is moderately or strongly related to exposure, it is likely that the
assumptions of IV are violated, resulting in a biased effect estimate.
We conclude that instrumental variables can be useful in case of
moderate confounding but are less useful when strong confounding
exists, because strong instruments cannot be found and assumptions
will be easily violated. |
| keywords | biomedische technologie en medicijnen, epidemiology, farmacie(FARM), public health, ziekenhuisstructuur en organisatie van de gezondheidszorg |
| ISSN | 1044-3983 |
