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1−ˆe +τ Y (ˆπS,λ −π S,λ) ≲∥ˆe−e∥ 2 · ∥ˆµ1 −µ 1∥2 +∥ˆe−e∥ 2 · ∥ˆµ0 −µ 0∥2 +E P |τY (ˆπS,λ −π S,λ)| =o P(n−1/2) where we used Lemma S3, Lemma S4, Lemma S5, Lemma S6, Lemma S8, the boundedness ofτ Y · 2020

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stat.ME 1

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2025 1

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Evaluating Surrogates in Individualized Treatment Rules

stat.ME · 2025-11-29 · unverdicted · novelty 7.0

Introduces surrogate regret, gain, and efficiency measures plus AIPW estimators to evaluate the decision-making value of surrogates for learning budget-constrained individualized treatment rules.

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  • Evaluating Surrogates in Individualized Treatment Rules stat.ME · 2025-11-29 · unverdicted · none · ref 10

    Introduces surrogate regret, gain, and efficiency measures plus AIPW estimators to evaluate the decision-making value of surrogates for learning budget-constrained individualized treatment rules.