Journal Article

Sensitivity Analysis and Power for Instrumental Variable Studies

Wang, Xuran, Small, Dylan S., Zhang, Nancy R., Jiang, Yang

2018

Overview

In observational studies to estimate treatment effects, unmeasured confounding is often a concern. The instrumental variable (IV) method can control for unmeasured confounding when there is a valid IV. To be a valid IV, a variable needs to be independent of unmeasured confounders and only affect the outcome through affecting the treatment. When applying the IV method, there is often concern that a putative IV is invalid to some degree. We present an approach to sensitivity analysis for the IV method which examines the sensitivity of inferences to violations of IV validity. Specifically, we consider sensitivity when the magnitude of association between the putative IV and the unmeasured confounders and the direct effect of the IV on the outcome are limited in magnitude by a sensitivity parameter. Our approach is based on extending the Anderson-Rubin test and is valid regardless of the strength of the instrument. A power formula for this sensitivity analysis is presented. We illustrate its usage via examples about Mendelian randomization studies and its implications via a comparison of using rare versus common genetic variants as instruments.

• Publisher: Wiley-Blackwell,Blackwell Publishing Ltd
• Subject: Anderson–Rubin test / Bias / BIOMETRIC METHODOLOGY / biometry / Biometry - methods / Confounding Factors (Epidemiology) / Genetic diversity / Genetic Variation / Humans / Instrumental variable (IV) / Linear IV regression model / Measure of IV strength / Mendelian Randomization Analysis - methods / observational studies / Observational Studies as Topic / Outcome Assessment (Health Care) / Parameter sensitivity / Power function / Root Cause Analysis - methods / Sensitivity analysis