Instrumental variable analysis is a research method that uses naturally occurring variation to estimate causal effects of interventions on outcomes from observational data. This method requires three key assumptions: relevance, independence, and exclusion restriction. Instruments must be associated with the intervention, have no uncontrolled common causes with the outcome, and only affect the outcome through the intervention. Different types of instruments can be used, such as physician preferences, access, or random assignment. Assessing the plausibility of these assumptions is crucial in determining the validity of instrumental variable studies. Various estimators, such as two-stage least squares or Wald estimator, can be used to estimate the average treatment effects. Ultimately, instrumental variable analysis provides a reliable alternative for researching causal effects in clinical practice.
Source link
Reading and conducting instrumental variable studies: guide, glossary, and checklist
