The paper constructs minimax-bias estimators and uniformly valid confidence intervals for weighted estimands by bounding differences via parameter heterogeneity and weight distance.
Advances in data science and information engineering: proceedings from ICDATA 2020 and IKE 2020 , pages=
2 Pith papers cite this work. Polarity classification is still indexing.
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A meta-analytic framework estimates the resilience probability of a surrogate marker to the surrogate paradox in a new study by modeling deviations from functional relationships observed in completed trials.
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Robust Inference for Weighted Estimands
The paper constructs minimax-bias estimators and uniformly valid confidence intervals for weighted estimands by bounding differences via parameter heterogeneity and weight distance.
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A Functional-Class Meta-Analytic Framework for Quantifying Surrogate Resilience
A meta-analytic framework estimates the resilience probability of a surrogate marker to the surrogate paradox in a new study by modeling deviations from functional relationships observed in completed trials.