Using a two-parameter sensitivity analysis framework to efficiently combine randomized and nonrandomized studies
用双参数敏感性分析整合随机与非随机研究
Abstract Causal inference is vital for informed decision-making across fields such as biomedical research and social sciences. Randomized controlled trials (RCTs) are considered the gold standard for internal validity of inferences, whereas observational studies (OSs) often provide the opportunity for greater external validity. However, both data sources have inherent limitations preventing their use for broadly valid statistical inferences: RCTs may lack generalizability…