Iinterference and/or spillover effect
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Description
Hello, I am a fan of EconML, but I will be extremely happy if you develop an ML model to perform an estimation of overall, direct, and indirect causal effects for single time point interventions in network-dependent (non-IID) data in the presence of interference and/or spillover, as in: Auto-G-Computation of Causal Effects on a Network. Tchetgen Tchetgen et al. Journal of the American Statistical Association, Volume 116, 2021 - Issue 534
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No file, test, or entry point is named. Start by reading the referenced Auto-G-Computation paper and comparing its overall, direct, and indirect effect estimands with EconML’s existing treatment-effect algorithms. Done would require an agreed design and support for single-time interventions with network dependence, interference, and spillover effects.
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
- Needs clarification
- Newbie friendliness
- 25/100