PermuCATE applies conditional permutation importance to CATE estimation, claiming lower variance and higher statistical power than LOCO on simulated and health datasets.
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Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence
PermuCATE applies conditional permutation importance to CATE estimation, claiming lower variance and higher statistical power than LOCO on simulated and health datasets.