Amit Sharma

yeah, the reason is misalignment between `effect_modifier_names` and the data `effect_modifiers`. We could follow @andresmor-ms recommendation, but I wonder if that can affect other estimators. Also, `effect_modifier_names` is supposed to...

Thanks for raising this @wxl112 . We do not currently support this parameter for econml estimators. Will plan to add it for the next release. For now, you may discretize...

@bloebp can you take a look? We can aim to do a release that supports 3.12

Thanks for the edits, @rahulbshrestha There is a build error due to config issue with econml tests. I will resolve that and merge this PR after that.

Thanks you @rahulbshrestha for adding these tests. sorry for the delay in fixing the econml dependencies!

Thanks for raising this. We will update the documentation in the next few weeks. Meanwhile, here's the answer. * random common cause: adds a randomly generated common cause. Estimated effect...

> That means random_common_cause_refutor only change the graph structure by adding a new nodes as a confounder, and the value of treatment and outcome remain unchanged, right? Yes. > So...

Yeah, the new effect is almost the same in both cases, so the estimator is okay. Not sure why you are getting a p-value of 0 for the bootstrap refuter....

Thanks for raising this @krz. Can you give more details on how scikit-learn supports polars DFs? Do they have a common API that can support both pandas and polars (if...

We do not explicitly process text, but rather use existing python libraries to for text processing that support non-english languages. So non-English languages should be supported too. Can you share...