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Ilya Shpitser's avatar

You are confused. Dynamic treatment regimes necessitate a causal connection between the policy and the outcome. They are defined, ultimately, in terms of counterfactuals, see for instance:

http://www.stat.lsa.umich.e...

http://www.rss.org.uk/uploa...

etc.

EDT doesn't even know what those counterfactual things _are_. I am not sure you really understand the difference between CDT and EDT (there is more going on here than just "oh there is an expectation and a conditioning bar, therefore it's EDT"). So far, every clearcut example of the use of CDT (such as policy selection in dynamic treatment regimes, or actions based on randomized control trials) you classified as EDT. I can only conclude that the set of things under the heading of CDT to you is the empty set.

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Overcoming Bias Commenter's avatar

Read the "Mathematical foundation" paragraph of Wikipedia article you cited. That's the typical textbook version of the EDT formula.

The article mentions the difficulty of inducing the optimal policies from the data due to confounding variables, but it makes clear that this is an estimation problem.

You keep conflating estimation theory and decision theory. While actual algorithms may combine them, computing actions from data, estimation and decision are conceptually different problems.

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