Thomas Lumley • 7/2/2013

Problems with faithfulness and the causal Markov property (I)

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This technical article analyzes foundational problems in causal inference, specifically the causal Markov property and the faithfulness assumption. It details how measurement error—broadly defined to include imperfect proxies and single-measurement averages—can break the conditional independence relationships these properties require, complicating the accurate representation of causal structures.

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#statistics #Causal Inference #Measurement Error
Problems with faithfulness and the causal Markov property (I)

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