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Causal Inference With Instrumental Variables

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CIFW01 - Foundations of causal inference

In observational studies, ignorability or conditional exchangeability is often an untenable assumption because of unmeasured confounders, pre-treamtent variables that affect both the treatment and the outcome. In this lecture, we discuss one of the most popular approaches to identify causal effects when ignorability fails: instrumental variables (IVs). Briefly, IVs require finding a variable , called an instrument, that satisfy certain assumptions. We cover two ways to formalize these assumptions, one based on monotonicity and another based on no additive interactions.

This talk is part of the Isaac Newton Institute Seminar Series series.

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