Comments (6)
Thanks for your comment @MaximilianFranz ! Yes, synth-validation is an exciting idea. We are also exploring other methods for doing validation, such as bayesian model criticism and methods that introduce an interpretable parameter for confounding and then rerun the estimates.
Curious to hear your thoughts on these as we prioritize next steps for DoWhy.
And thanks for building out an R implementation of Synth-validation. Would love to integrate it with DoWhy. I am not an expert at RPy---Would you mind adding a Jupyter notebook that shows how to use the R implementation in python?
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@MaximilianFranz Wanted to share that we just released a roadmap for dowhy's development. Of course, synth-validation and related refutation methods are a high priority. Are you still interested in contributing to the repo?
Would also appreciate your feedback on the roadmap here: https://github.com/microsoft/dowhy/wiki/Roadmap
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Thanks for letting me know. I haven't forgotten about Synth-Validation, but the colleague who translated the code into R isn't sure about publishing it to the DoWhy repository yet. I will check again with him and our supervisor for further information.
If I am not mistaken, the result of their evaluation was that the Synth-Validation method is not as effective as proposed, once the setting becomes more realistic. I'll keep you posted!
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Ah, alright! Thanks for the update @MaximilianFranz. Curious to hear more about the evaluation, that sounds really interesting. Would you be comfortable sharing the results?
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Late reply, sorry for that.
My last information was that the institute was not comfortable publishing the R version of SynthValidation, as it might not be identical and is not robust.
I am currently busy with implementing a framework for academic method evaluation using parametric DGPs (JustCause), so I won't be able to work on Synth-Validation anytime soon, though it would be cool to have!
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Ah, alright. Thanks for the update @MaximilianFranz. Wow, JustCause looks cool---evaluation of causal models is super important! If you think that there are ways DoWhy and JustCause can work together, let me know!
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Related Issues (20)
- Support polars data frames HOT 2
- What is the purpose of providing observation data in gcm.conventional_samples()?
- Python 3.12 support HOT 9
- Clarify the differences among refute methods HOT 11
- Feature relevance/Influence HOT 26
- Graphviz installation : --include-path not recognized anymore HOT 4
- Does this package support non-English languages? HOT 3
- Question about Dummy Outcome Refuter HOT 2
- Inconsistency in the placebo_treatment_refuter when using estimate_effect of IV HOT 1
- numpy.dual is dropped but it still occurs in dowhy HOT 2
- NetworkXError: graph should be directed acyclic HOT 4
- Refutation & Overlap Error ("data_subset_refuter", "add_unobserved_common_cause", assess_support_and_overlap_overrule) HOT 2
- No Backdoor Path Available
- Clarification on how to use gcm properly for confounders adjustment HOT 5
- Can you provide code demo for each function? HOT 2
- How is propensity score matching implemented? HOT 2
- Interpreting mean while using logistic regression to estimate causal effect. HOT 1
- model.estimate_effect and model.refute_astimate throws 'A column-vector y was passed ...' error
- RuntimeWarning: divide by zero encountered in divide when using evaluate_causal_model HOT 3
- Auto assign_causal_mechanisms is taking so much time in gcm HOT 11
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