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Below is my code to estimate treatment effects. There is a much wider confidence interval of ATT (i.e., [-200k, 900k]) by Causal Forest DML model, compared to that calculated by linear DML model (i.e,…
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I was running "Example Usage with Binary Treatment Synthetic Data" in the Causal Forest Notebook (https://github.com/py-why/EconML/blob/main/notebooks/Causal%20Forest%20and%20Orthogonal%20Random%20For…
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Defining a treatment effect for the causal random survival forest requires specification of a horizon timepoint.
Should we use the same horizon for all datasets in our main analysis or use data-spe…
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Hi Stephan,
I was just thinking, would it make sense / be feasible to include splitting rules and/or "honesty" as described in `S. Athey, J. Tibshirani, and S. Wager. Generalized random forests. The …
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Hello,
Thank you for developing `grf`. It's great!
Would it be feasible to allow `Y.hat` to be an input for causal survival forests? I see from code in `causal_survival_forest` that a couple of…
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Hi,
Thanks for your work.
I am a student currently learning about causal forest and have some questions regarding the variable types and `test_calibration` Interpretation in causal forest.
1. D…
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implemented but not yet released in grf
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Hi guys,
and thank you for your amazing work.
I am writing to ask a couple of key questions on the use of causal forests in a setting with panel data, binary outcome, and a continuous, plausibly …
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Hi Keith,
@kbattocchi
I had a follow-up question on the SingleTreePolicyInterpreter (causal forest) Interpreter in general. My questions are:
1. If I have 3 Y-variables (i.e. sales, retention,…
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Hey,
I have a question regarding how you implemented the multilevel Bayesian Causal Forest in your National Study of Learning Mindsets paper. I looked at the code that is kindly provided (ED Fig.3.R)…