Digital twins from outcome models trained on historical data can function as robust synthetic controls in single-arm trials, supported by doubly robust estimators, power formulas, and reanalyses in ALS and Huntington's disease.
X x µ1(x)p(x|A= 1) # = X x [EIF[µ1(x)]p(x|A= 1) +µ 1(x)EIF[p(x|A= 1)]], EIF[τ0] =EIF
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Including LLM predictions as covariates in standard regression adjustment for randomized experiments reduces variance with a do-no-harm property that reverts to the unadjusted estimator when predictions are uninformative.
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Digital Twins as Synthetic Controls in Single-Arm Trials
Digital twins from outcome models trained on historical data can function as robust synthetic controls in single-arm trials, supported by doubly robust estimators, power formulas, and reanalyses in ALS and Huntington's disease.
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AI-Assisted Variance Reduction in Randomized Experiments
Including LLM predictions as covariates in standard regression adjustment for randomized experiments reduces variance with a do-no-harm property that reverts to the unadjusted estimator when predictions are uninformative.