Computes Robustness Values for Debiased Machine Learning — robustness

This function computes the robustness value of a target parameter estimated via debiased machine learning.

The robustness value describes the minimum strength of association (parameterized in terms of R2) that omitted variables would need to have both with the outcome and with the Riesz Representer so that the confidence bounds for the target parameter includes zero (or another threshold of interest).

robustness_value(model, ...)

# S3 method for dml
robustness_value(model, theta = 0, alpha = 0.05, ...)

# S3 method for dml.bounds
robustness_value(model, theta = 0, alpha = 0.05, ...)

Arguments

model: an object of class dml or dml.bounds.
...: arguments passed to other methods.
theta: the null hypothesis of interest for the target parameter theta. Default is theta =0 (zero null hypothesis).
alpha: significance level. Default is alpha = 0.05.