1 Questions
Define the Conditional Independence Assumption (CIA) and explain its significance in causal analysis.
The CIA assumption states that, given a set of covariates X, the potential outcomes Y(0) and Y(1) are independent of the treatment assignment D. Formally, {Y(0),Y(1)}⊥D∣X. This assumption helps to identify causal effects from observational data and ensures that only the treatment leads to differences in outcomes between treated and untreated group.
Understand the Conditional Independence Assumption (CIA) and its importance in causal analysis. Learn how CIA helps in identifying causal relationships between variables.
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