SUMMARY In recent years, real-world external controls have grown in popularity as a tool to empower randomized placebo-controlled trials, particularly in rare diseases or cases where balanced randomization is unethical or impractical. However, as external controls are not always comparable to the trials, direct borrowing without scrutiny may heavily bias the treatment effect estimator. Our paper proposes a data-adaptive integrative framework capable of preventing unknown biases of the external controls. The adaptive nature is achieved by dynamically sorting out a comparable subset of the external controls via bias penalization. Our proposed method can simultaneously achieve (a) the semiparametric efficiency bound when the external controls are comparable and (b) selective borrowing that mitigates the impact of the existence of incomparable external controls. Furthermore, we establish statistical guarantees, including consistency, asymptotic distribution, and inference, providing type-I error control and good power. Extensive simulations and two real-data applications show that the proposed method leads to improved performance over the trial-only estimator across various bias-generating scenarios.

Chenyin Gao

Shu Yang

Mingyang Shan

Wenyu Y E

Ilya Lipkovich

Douglas Faries

Biometrika

BIOMETRIKA 主要是一本统计学杂志，其中重点放在包含在应用中具有直接或潜在价值的原始理论贡献的论文上。不时还会发表一些边缘领域的论文。

Biometrika is a journal primarily focused on statistics, particularly papers that present original theoretical contributions with direct or potential value in applications. Occasionally, it also publishes research from peripheral areas.

《Biometrika》是一本主要关注统计学的期刊，特别是那些在应用中具有直接或潜在价值的原创理论贡献的论文。此外，期刊偶尔也会发表一些边缘领域的研究成果。

Category	Quartile
数学	2
数学, 数学与计算生物学	1
数学, 生物学	2
数学, 统计学与概率论	2

Improving randomized controlled trial analysis via data-adaptive borrowing

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Journal Info

Category	Quartile
STATISTICS & PROBABILITY	1