Recently, Wang and Tchetgen Tchetgen (2018) showed that the global average treatment effect is identifiable even in the presence of unmeasured confounders so long as they do not modify the instrument’s additive effect on the treatment. We use a simple and direct method to show that this no-interaction assumption allows identification of the entire outcome distribution, which leads to multiply robust estimation procedures for nonlinear functionals like the quantile and Mann–Whitney treatment effects. Similarly, we can bound these causal estimands through the outcome distribution in sensitivity analysis against confounder–instrument interaction.

最近，Wang 和 Tchetgen Tchetgen (2018) 表明，即使存在未测量的混杂因素，只要它们不改变仪器对治疗的累加效应，全球平​​均治疗效果也是可以识别的。我们使用一种简单而直接的方法来表明这种无交互假设允许识别整个结果分布，从而导致对分位数和 Mann-Whitney 处理效果等非线性函数的多重稳健估计程序。同样，我们可以通过针对混杂因素-仪器交互的敏感性分析中的结果分布来限制这些因果估计。