Robust inference for risk heterogeneity under group imbalance
The paper proposes a robust framework using Neyman orthogonality to infer risk heterogeneity between groups, even when one group is underrepresented. It introduces a debiased estimator that is less sensitive to errors from baseline model misspecification and regularization bias compared to standard methods.