Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Include moderators that are no confounders #849

Open
FlorianNachtigall opened this issue Feb 12, 2024 · 1 comment
Open

Include moderators that are no confounders #849

FlorianNachtigall opened this issue Feb 12, 2024 · 1 comment

Comments

@FlorianNachtigall
Copy link

Hi!

Is it possible to include variables that only moderate but do not confound the relationship between T and Y?

Using the CausalForestDML, I would like to include an additional moderator to explain the heterogeneity of the treatment effect, but since it is also a mediator, I can't include it in X. I hope this makes sense.

Any thoughts and workarounds would be greatly appreciated. Thanks in advance!

@kbattocchi
Copy link
Collaborator

If you want to use it for heterogeneity you could still add it to X while changing your model_t to something like a pipeline where the first step is a ColumnTransformer that drops that column and the second step is your actual model.

However, if the variable is downstream of T, then such a CATE model will probably not be of much use in a policy setting, for example, because you can't make treatment decisions based on the unknown value of that variable at treatment time.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants