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VOLUME 54 | NUMBER 3 | JUNE 2019


Instrumental variables: Don't throw the baby out with the bathwater

Confounding by indication is a critical challenge in evaluating the effectiveness of medical interventions. It is widely understood that randomization to treatment is the best analytic technique for addressing confounding by indication. The primary alternative to randomized trials is to assume that there are no unmeasured confounders. In economics, this is often referred to as “selection on observables” to indicate that selection into the treatment must be based on observed data only. Under this assumption, the investigator assumes there are no unobservable differences between the treated and control groups. While this assumption may be plausible in some settings, in health services research, treatments are purposefully chosen and administrative datasets do not record all the reasons why a particular treatment was administered or withheld.

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