DCMA learns conditional generative models from observational data to reconstruct interventional outcome distributions via Monte Carlo simulation and derive error bounds for distributional mediation effects.
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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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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.