Skepticism about the assumption of no unmeasured confounding, also known as exchangeability, is often warranted in making causal inferences from observational data; because exchangeability hinges on an investigator's ability to accurately measure covariates that capture all potential sources of confounding. In practice, the most one can hope for is that covariate measurements are at best proxies of the true underlying confounding mechanism operating in a given observational study. In this paper, we consider the framework of proximal causal inference introduced by Miao et al. (2018); Tchetgen Tchetgen et al. (2020), which while explicitly acknowledging covariate measurements as imperfect proxies of confounding mechanisms, offers an opportunity to learn about causal effects in settings where exchangeability on the basis of measured covariates fails. We make a number of contributions to proximal inference including (i) an alternative set of conditions for nonparametric proximal identification of the average treatment effect; (ii) general semiparametric theory for proximal estimation of the average treatment effect including efficiency bounds for key semiparametric models of interest; (iii) a characterization of proximal doubly robust and locally efficient estimators of the average treatment effect. Moreover, we provide analogous identification and efficiency results for the average treatment effect on the treated. Our approach is illustrated via simulation studies and a data application on evaluating the effectiveness of right heart catheterization in the intensive care unit of critically ill patients.

翻译：假设不存在无法测量的混乱,也称为可互换性,这种假设的怀疑性往往是从观测数据中得出因果关系推断的依据;因为互换性取决于调查员准确测量所有潜在混乱来源的共变能力;在实践中,最希望的是,共变测量最多只能是某一观测研究中运行的真正根本共变机制的替代物。在本文中,我们认为米奥等人(2018年)引入的预估因果密集推断框架;Tchetgen Tchetgen等人(202020年)明确承认共变测量是混结机制的不完善替代物,同时承认共变测量是准确测量所有潜在混乱来源的共变异性。在测量的共变异性失败基础上进行互换的环境下,人们最希望的是,共变的测度测量最多只能是真实的,其中包括:(一) 确定平均治疗效果的不对准正正数的准确度; (二) 对平均治疗效果的预估估测结果,包括精度的常数度的测度的测度测度的测度测测度的测度,为我们当地测算结果的测算结果; (三) 我们的测测测测测测测测测测度的测测测测测测测测测测测测度的测测度的精度的精度的精度的精度的精度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度结果的测度的测度的测度,是,对当地测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度,是的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度,是的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测度的测