A Markov equivalence class refers to a set of directed acyclic graphs (DAGs) that encode the same conditional independence relationships among a set of variables. This concept is crucial in understanding how different causal structures can represent the same statistical information, leading to challenges in causal inference. In this context, multiple DAGs can be considered equivalent if they imply the same conditional independence statements, which has important implications for model selection and data interpretation.
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