插补(统计学)
辍学(神经网络)
缺少数据
事件数据
比例危险模型
计算机科学
统计
计量经济学
数据挖掘
数学
机器学习
分析
作者
Jiwei He,Roberto Crackel,William Jen Hoe Koh,Ling-Wan Chen,Feng Li,Jialü Zhang,Mark D. Rothmann
标识
DOI:10.1080/10543406.2022.2118763
摘要
Recently, retrieved-dropout-based multiple imputation has been used in some therapeutic areas to address the treatment policy estimand, mostly for continuous endpoints. In this approach, data from subjects who discontinued study treatment but remained in study were used to construct a model for multiple imputation for the missing data of subjects in the same treatment arm who discontinued study. We extend this approach to time-to-event endpoints and provide a practical guide for its implementation. We use a cardiovascular outcome trial dataset to illustrate the method and compare the results with those from Cox proportional hazard and reference-based multiple imputation methods.
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