Ignorability, often referred to in the context of causal inference and statistical modeling, refers to a condition under which the treatment assignment in an observational study can be considered as if it were randomized. This concept is crucial for identifying causal effects from observational data, as it allows researchers to make valid inferences about treatment effects without the biases typically associated with non-randomized studies.
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