论文标题
在不完美的随机实验中的因果效应的非参数界限
Nonparametric bounds for causal effects in imperfect randomized experiments
论文作者
论文摘要
即使在设计良好的随机实验中，也可能发生不可贬低的缺失和不合规性，从而使实验旨在估计不可识别的干预效果。非参数因果界限提供了一种方法，可以缩小以最小的假设的非识别因果效应的可能值范围。我们在因各种机制而导致的不可贬低的遗失性和不合规性的随机实验中，为二元结果和干预的因果风险差异而得出了新的界限。我们说明了在我们激励的数据示例中使用花生消费量对婴儿过敏的发展示例的使用。
Nonignorable missingness and noncompliance can occur even in well-designed randomized experiments making the intervention effect that the experiment was designed to estimate nonidentifiable. Nonparametric causal bounds provide a way to narrow the range of possible values for a nonidentifiable causal effect with minimal assumptions. We derive novel bounds for the causal risk difference for a binary outcome and intervention in randomized experiments with nonignorable missingness caused by a variety of mechanisms and with or without noncompliance. We illustrate the use of the proposed bounds in our motivating data example of peanut consumption on the development of peanut allergies in infants.
