We have located links that may give you full text access.
Bias analysis of the instrumental variable estimator as an estimator of the average causal effect.
Contemporary Clinical Trials 2010 January
Noncompliance is a common problem in drawing causal inference in randomized trials. The instrumental variable (IV) method estimates the average causal effect in randomized trials with noncompliance. However, the IV estimator generally yields a biased estimate under a non-null hypothesis, although it can yield an unbiased estimate under a null hypothesis. Therefore, it is important to evaluate the potential bias of the IV estimate quantitatively. This paper provides such a quantitative method, which is an extension of bias analysis for unmeasured confounders using the confounding risk difference in the context of observational studies. The proposed method will help investigators to provide a realistic picture of the potential bias of the IV estimate. It is illustrated using a field trial for coronary heart disease.
Full text links
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app