倾向得分匹配
协变量
随机对照试验
统计
贝叶斯概率
计算机科学
推论
贝叶斯推理
计量经济学
医学
数学
人工智能
外科
作者
Nelson Lu,Chenguang Wang,Wei‐Chen Chen,Heng Li,Changhong Song,Ram C. Tiwari,Yunling Xu,Lilly Q. Yue
标识
DOI:10.1080/10543406.2021.1998098
摘要
In this paper, a propensity score-integrated power prior approach is developed to augment the control arm of a two-arm randomized controlled trial (RCT) with subjects from multiple external data sources such as real-world data (RWD) and historical clinical studies containing subject-level outcomes and covariates. The propensity scores for the subjects in the external data sources versus the subjects in the RCT are first estimated, and then subjects are placed in different strata based on their estimated propensity scores. Within each propensity score stratum, a power prior is formulated with the information contributed by the external data sources, and Bayesian inference on the treatment effect is obtained. The proposed approach is implemented under the two-stage study design framework utilizing the outcome-free principle to ensure the integrity of a study. An illustrative example is provided to demonstrate the implementation of the proposed approach.
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