Experiment-selector cross-validated targeted maximum likelihood estimator for hybrid RCT-external data studies
用于随机试验与外部数据混合研究的实验选择交叉验证 TMLE
Augmenting a randomized controlled trial (RCT) with external data may increase power at the risk of introducing bias. To select and analyze the experiment (RCT alone or combined with external data) with the optimal bias-variance tradeoff, we develop a novel experiment-selector cross-validated targeted maximum likelihood estimator for randomized-external data studies (ES-CVTMLE). This estimator utilizes two estimates of bias to determine whether to integrate external data…