Individual Treatment Effects
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Description
Hi @kbattocchi ,
I used the following code to calculate the ATE for my panel data (around ~$18).
dml = DynamicDML(model_y=outcome_model,
model_t=treatment_model,
cv=2, discrete_treatment=True)
dml.fit(Y=Y, T=T, X=None, W=X, groups=groups)
Is it possible to get individual treatment effects too? Ie how much causal impact the treatment would gave in the outcome variable for each row of my data?
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Research direction
The issue names DynamicDML and its fit call; start by locating that estimator's implementation and existing treatment-effect prediction APIs. Check whether row-level effects are already supported or what interface and tests would define them, with completion requiring individual effects for the stated panel-data workflow.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100