Elastic integrative analysis of randomised trial and real-world data for treatment heterogeneity estimation
提出一种基于检验的弹性整合方法，结合随机试验和真实世界数据估计治疗异质性，通过检验决定是否使用真实世界数据，并给出自适应阈值选择和弹性置信区间。
We propose a test-based elastic integrative analysis of the randomised trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers. When the real-world data are not subject to bias, our approach combines the trial and real-world data for efficient estimation. Utilising the trial design, we construct a test to decide whether or not to use real-world data. We characterise the asymptotic distribution of the test-based estimator under local alternatives. We provide a data-adaptive procedure to select the test threshold that promises the smallest mean square error and an elastic confidence interval with a good finite-sample coverage property.