Instrumental variable
An instrumental variable is a variable that affects a treatment or exposure while influencing an outcome only through that treatment or exposure, under causal identifying assumptions.
Causal Inference for Data Science
An instrument is a variable that directly influences treatment while being unrelated to confounders and not directly influencing the outcome.
- How it is used
- Estimates treatment effects when unobserved confounders prevent adjustment, using independent variation in an instrument.
- How deep it goes
- Develops assumptions, linear and partially linear models, formulas, two-stage estimation, software application, and weak-instrument limitations.
- Examples
- Uses chatbot uptake in an A/B test, noncompliant clinical trials, and a synthetic binary-treatment dataset.
- What you can do after
- Apply it via R and Python packages to estimate causal effects and interpret IV results under stated assumptions.
Read how Causal Inference for Data Science explains instrumental variable →
Causal AI
An instrumental variable is a variable that affects an exposure or treatment and influences an outcome only through that exposure or treatment under specified causal assumptions.
- How it is used
- Uses candidate instruments to estimate a treatment’s causal effect when building and analyzing a causal DAG.
- How deep it goes
- Defines validity through as-if-random and exclusion, adds instrument strength and linear estimation, but does not derive the estimand.
- Examples
- Uses side-quest group assignment and customization level for gaming purchases, with DoWhy estimates and wide confidence intervals.
- What you can do after
- Apply it via DoWhy to estimate an average treatment effect and assess whether a weak instrument makes the estimate too uncertain.
Related concepts
- causal adjustmentalternative to · Causal adjustment estimates a causal effect by conditioning on variables that block noncausal pathways and averaging over their target-population distribution.
- weak instrumentincludes · A weak instrument is an instrumental variable with a weak effect on treatment, producing imprecise or high-variance causal effect estimates.
- DoubleMLused by · DoubleML is an open-source software library for estimating causal effects with double machine learning and related methods in R and Python.
- treatment effectmeasures · A treatment effect is the difference in an outcome attributable to receiving an intervention or exposure rather than a comparison condition.
- synthetic datauses · Synthetic data is data generated artificially rather than collected directly from the target process, often to approximate its properties or meet specified requirements.
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