Difference between X and W
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Description
Hi! Can you explain what the difference between confounders and controls in Double ML? Shouldn't we consider all the features as X because confounders (W) influence on Y and therefore should be in the final model?
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- Read the whole issue, then the project's contributing guide.
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Research direction
No file, test, or entry point is identified in the issue. Start by locating the project’s Double ML documentation and the definitions of X, W, confounders, and controls; done means adding a clear explanation that resolves whether W belongs in X and how the variables are used.
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Assessment
- Tech stack
- machine-learning
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 18/100