Choosing models with distinct covariates
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Description
Hi,
I wonder if there is a way to compare the performance of causal models that use different set of covariates.
I understand that you developed methods for comparing algorithms (score of second stage model on a validation set) and I would like to know if these methods are also valid for choosing which set of covariates to include in the model.
One concern is the fact that adding variables may induce missing values and thus change the set of observations used for estimation.
Thank you.
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Research direction
The issue names no files, tests, or entry points. Start by determining whether EconML already supports comparing causal models with different covariate sets, then clarify how missing observations should be handled and what implementation or documentation outcome would count as done.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100