New orthogonal risk functions are derived for conditional OR and RR, with simulations and NHANES data showing nonparametric estimators reduce bias compared to parametric alternatives in complex settings.
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A framework defining new causal estimands for adaptive designs and using TMLE to enable online selection among designs, including surrogate-guided ones, while handling data dependence.
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Orthogonal machine learning for conditional odds and risk ratios
New orthogonal risk functions are derived for conditional OR and RR, with simulations and NHANES data showing nonparametric estimators reduce bias compared to parametric alternatives in complex settings.
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An Online Meta-Level Adaptive Design Framework with Targeted Learning Inference: Applications to Evaluating and Utilizing Surrogate Outcomes in Adaptive Designs
A framework defining new causal estimands for adaptive designs and using TMLE to enable online selection among designs, including surrogate-guided ones, while handling data dependence.