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MalteKurz avatar MalteKurz commented on May 20, 2024

Hi @brgordon1,

thanks for your remark. Let me try to clarify this: In the field obj_dml$se you find the asymptotic standard error, i.e.,
formula4.
It is the standard error from the asymptotic normal distribution scaled with the square-root of the number of observations. We know that
image
with
image
If you now for example want to construct a confidence interval for your parameter estimate, you get the following expression
image
So the asymptotic variance of your parameter estimate is formula4
and the standard error that we return in obj_dml$se is the square-root of it.
In the referenced code line, we compute the asymptotic variance (i.e., before taking the square-root but already with the additional scaling with N):

sigma2_hat = 1 / n_obs * mean(psi^2) / (J^2)

I hope this helps you. We btw also mention this for example here https://docs.doubleml.org/stable/guide/se_confint.html (see screenshot).
image

However, I fully agree that this could be made clearer at some places in the documentation, e.g., the API doc here: https://docs.doubleml.org/r/stable/reference/DoubleML.html#public-fields.

Thanks,
Malte

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brgordon1 avatar brgordon1 commented on May 20, 2024

Thank you, @MalteKurz. Very helpful and I appreciate the quick reply. I should really have caught that myself by looking at the expression for the confidence interval. I'm glad it now makes sense.

Regards,
Brett

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MalteKurz avatar MalteKurz commented on May 20, 2024

No worries, thanks for the feedback 👍. I think your point was valid and we could make the documentation clearer in this regard.

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