Assessing Treatment Effects in Observational Data With Missing Confounders: A Comparative Study of Practical Doubly-Robust and Traditional Missing Data Methods
评估存在缺失混杂因素的观察性数据中的治疗效果:实用双重稳健缺失数据方法与传统缺失数据方法的比较研究
期刊:Statistics in Medicine
影响因子:1.8
doi:10.1002/sim.70366
Williamson, Brian D; Krakauer, Chloe; Johnson, Eric; Gruber, Susan; Shepherd, Bryan E; van der Laan, Mark J; Lumley, Thomas; Lee, Hana; Hernández-Muñoz, José J; Zhao, Fengyu; Dutcher, Sarah K; Desai, Rishi; Simon, Gregory E; Shortreed, Susan M; Nelson, Jennifer C; Shaw, Pamela A