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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Framework using potential outcomes and within-treatment regression models to estimate plot-level SOC sequestration potentials from covariates and approximate optimal policies, demonstrated on California rangeland data where targeting low-baseline-SOC plots improves outcomes over uniform policies.
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Evaluating Surrogates in Individualized Treatment Rules
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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Estimating soil carbon sequestration potential and approximating optimal management policies
Framework using potential outcomes and within-treatment regression models to estimate plot-level SOC sequestration potentials from covariates and approximate optimal policies, demonstrated on California rangeland data where targeting low-baseline-SOC plots improves outcomes over uniform policies.