Bounds on causal effects in $ 2^{K} $ factorial experiments with noncompliance
针对因子实验中单位不依从分配因素的问题，在更温和的假设下，为有界结果变量给出了依从者平均处理效应的界，帮助研究者识别因果效应。
Summary Factorial experiments are ubiquitous in the social and biomedical sciences, but when units fail to comply with each assigned factor, identification and estimation of the average treatment effects become impossible without strong assumptions. Leveraging an instrumental variables approach, previous studies have shown how to define and estimate the causal effect of treatment uptake among respondents who comply with treatment. A major caveat is that these results rely on strong assumptions on the effect of randomization on treatment uptake. This work shows how to bound these complier average treatment effects for bounded outcomes under milder assumptions on noncompliance.