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  "body": "\n## Summary\n\nThe Rubin causal model, or potential outcomes framework, defines causal effects by comparing the outcomes that the same unit would have under different treatments.\nEach unit has one potential outcome for each treatment, but only the one for the treatment actually received is observed.\nCausal effects such as the average treatment effect are then parameters of the joint distribution of potential outcomes.\nThe framework goes back to Jerzy Neyman's work on experiments and was developed by Donald Rubin for observational studies.\nIt is a basic language of [[causal inference|V3QJFN5800]].\n\n## Explanations\n\n### L1 human\n\nFor a patient, think of two versions of the future: one in which she takes the drug and one in which she does not.\nThe effect of the drug for her is the difference between the two outcomes.\nWe can only ever see one of these futures, so individual effects are never observed directly.\nAverages over many patients can still be learned, for example when a coin flip decides who gets the drug.\n",
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