Mediation Analysis with the Mediator and Outcome Missing Not at Random
研究了中介变量和结果变量非随机缺失时直接和间接效应的可识别性，提出了可解释的缺失机制，并通过模拟和美国国家职业军团研究数据验证了方法。
Mediation analysis is widely used for investigating direct and indirect causal pathways through which an effect arises. However, many mediation analysis studies are challenged by missingness in the mediator and outcome. In general, when the mediator and outcome are missing not at random, the direct and indirect effects are not identifiable without further assumptions. We study the identifiability of the direct and indirect effects under some interpretable mechanisms that allow for missing not at random in the mediator and outcome. We evaluate the performance of statistical inference under those mechanisms through simulation studies and illustrate the proposed methods via the National Job Corps Study.